By now, you’ve probably heard that most Americans do not trust AI. This distrust is especially concerning given how deeply these systems are already shaping access to healthcare, education, housing, jobs, and public benefits. Too often, these decisions happen without transparency, oversight, or meaningful avenues for recourse. At the same time, confidence in both technology companies and government institutions to manage AI responsibly remains low.

The stakes are clear, and the policy choices we make today will make or break society’s view of AI. We are currently at a critical opportunity to shape how AI is governed before harmful practices and inequities become further entrenched. To meet this moment, the Federation of American Scientists, with the support of the Kapor Foundation, launched a policy sprint, which is an intensive, time-bound effort designed to tackle complex challenges quickly and collaboratively. Policy sprints bring together experts from across disciplines, from academics, technologists, advocates, and practitioners, to develop practical, actionable solutions.

For our SOURCE CODE  AI Trust and Fairness Sprint, we’ve developed  10 memos with  leading experts that are detailed, implementable policy solutions. We have delved into why fairness is so hard to define and implement, and what is needed to promote public trust in our essay that frames this new policy agenda. These memos are not exhaustive; we know the landscape of challenges and potential solutions is far broader. Instead, we offer them as a starting point: ideas that we hope will not only serve as smart and actionable tools for policymakers, but also inspire the community to build out and advance new, detailed approaches.

• Jae Yeon Kim and Aniket Kesari show how government procurement can be a powerful but underused lever to require transparency, fairness, and accountability in AI systems.
  
• Nicole Ozer and Brady Hirsch emphasize that in order for AI to work for the people, state leaders must adopt people-centered AI decision making frameworks. hey explain how to ask and answer foundational questions about why and whether to use AI before skipping to the how of implementation.
  
• JB Branch highlights similar risks in K–12 education, proposing procurement guardrails and impact assessments to protect students’ rights and safety.
  
• Liza Paudel advances Community Benefit Agreements as a tool for ensuring that communities, especially those disproportionately impacted, secure enforceable protections as AI-driven data center development accelerates.
  
• Wilneida Negrón examines the rise of “surveillance pay,” calling for stronger regulatory safeguards to protect workers from opaque, data-driven compensation systems.
  
• Anna Lenhart proposes embedding “Decision Subject Representatives” into AI governance, giving impacted individuals a formal role in shaping high-stakes systems.
  
• Y. Tony Yang focuses on Medicaid and safety-net healthcare, proposing community-centered oversight, nurse-led audits, and patient protections to ensure AI improves rather than undermines care.
  
• Ziwei Qi, Tatiana Lin, and Ayokunle Olagoke highlight the risks of “algorithmic invisibility” in rural communities and call for “rural AI proofing” to ensure these populations are not overlooked in AI system design, governance, and implementation.
  
• Jon M. Peha explores the risks of AI-generated police reports and proposes coordinated federal and local strategies that foster innovation and prevent unsafe deployments.
  
• Gaurav Laroia and Charlotte Slaiman argue that enforcers must look beyond standard monetary penalties to truly protect communities from algorithmic harms. They show how historic tech settlements can be transformed into an active defense, building societal resilience and preparing the public for the next wave of technological change.

To structure our policy agenda, we have considered how these ideas have employed targeted mechanisms, which we call policy levers, to ensure legitimate use, fair outcomes, and public trust in AI. These levers include government use of AI, public engagement, sectoral considerations, and redress in legal remedies; many of our policy ideas use several of them.

This work was shaped by a multidisciplinary advisory working group of 17 experts from academia, civil rights organizations, think tanks, and beyond. Their insights helped refine the project’s focus, identify the most pressing policy opportunities, and strengthen each memo through expert review. Advisory members provided input in an individual capacity; their participation does not imply endorsement of the findings or recommendations. We are grateful for their support and expertise throughout this process.

• Quinn Anex-Ries, Center for Democracy & Technology
• Alex Ault, Lawyers’ Committee for Civil Rights Under Law
• Annette Bernhardt, UC Berkeley Labor Center
• Miranda Bogen, Center for Democracy & Technology
• Leah Frazier, Lawyers’ Committee for Civil Rights Under Law
• Sanmi Koyejo, Stanford University
• Sarah Myers West, AI NOW
• Tejas N. Narechania, UC Berkeley School of Law
• Cathy O’Neil
• Asad Ramzanali, Vanderbilt Policy Accelerator 
• Cody Venzke, ACLU 
• Jonathan Walter, Leadership Conference on Civil and Human Rights

The ideas generated through this sprint are practical, actionable, and grounded in existing authority. They demonstrate that policymakers already have many of the tools needed to govern AI effectively; they simply need to be deployed with urgency and intention. There is a narrowing window to shape the integration of AI systems into society. With thoughtful policy action, it is still possible to build systems that are fair, transparent, and accountable, and to earn the public trust that will ultimately determine AI’s future. We hope policymakers are ready to act.

On May 29, the Office of Management and Budget (OMB) dropped a 108 page (single-spaced) proposed rule to “revise the Guidance for Federal Financial Assistance to improve government-wide policies and requirements related to the management of grants, cooperative agreements, and other forms of assistance.” If you are not a dyed-in-the-wool wonk, here’s a translation: this proposed rule would change the way the federal government funds scientific research. And state energy programs. And community health grants. And the local governments trying to modernize how they deliver services. Like a lot. 

Aside: there is something wrong with the way we fund science in this country — the list of flaws is long and we have to own them. We also have to build something durable, not treat our principles like a suicide pact.

Rule changes like this thrive in tall weeds: the language is arcane, esoteric even, meant to be understood by lawyers and policy experts. Here’s what’s actually in them.

How we got here

There is a crisis of trust in science. Trust in science is still lower than before the COVID-19 pandemic reshaped our reality, with trust in federal science lower still. This trust is also partisan: Democrats are more likely to have confidence in scientists than Republicans are. Many people struggle to trust scientific processes and activities, to have faith in government as an interpreter of scientific findings, to feel public science priorities represent their needs. The federal research funding apparatus feels distant from most people’s lives, and the connection between public investment and public benefit isn’t easily traceable by the people whose taxes make it happen.

The federal execution of science has real problems too. Administrative burden, convoluted workflows, a funding system that concentrates awards among the already-large and already-connected, a merit review process that has calcified in ways that make it slow and risk-averse. As a community we have to own that. The fish psilocybin study wasn’t taxpayer-funded, but some real head-scratchers were (for the record: some of them were worth it).

Backstopping all of this is a weakening of Congress’s role in R&D. While there is bipartisan support for research in Congress (like the many Democratic and Republican lawmakers who have championed investment across AI regulation, wildland fire, and on emerging technologies like biotech and quantum computing), Congress has been relegated to a rump when it comes to their fiduciary duty to scientific research. Money expressly authorized and appropriated by the people’s house is being held up, research agencies are being starved of their necessary funds, and there is hardly anyone left to do the work.  

In that context, the Trump administration has been establishing a policy lineage for major change in how the federal government invests in many areas, including R&D. The 2025 Restoring Gold Standard Science executive order directed political appointees to oversee agency scientific decisions and resolve GSS “violations,” inserting politics into processes where existing scientific integrity policies had specifically been designed to keep it out. Agency implementation plans followed across multiple science agencies. This proposed rule is the next step.

Back to these rules

How much have you heard the phrase “gold standard science” in the last year? As a concept, it was reaching for something important: accountability in how research dollars get spent, scrutiny of whether peer review had become a closed loop, a question about whether federally funded science was delivering for the public that funds it. What it became in practice is something different.

Is it, for example, the systemic weakening of career staff at science agencies to replace their blood-sweat-and-tears expertise with political appointees? Is it firing the National Science Board en masse over email on a weekend? Is it gagging the NSF watchdog meant to uncover research misconduct and fraud? This doesn’t begin to cover the politicking that has diminished our national public health apparatus, or the bed bugs in the Animal and Plant Inspection Service building. 

What gold standard science became in practice is a mechanism for political appointees to override scientific judgment and frame ideological interference as methodological rigor. This proposed rule puts that mechanism into binding regulation, government-wide: mandatory political review of every discretionary grant before it’s awarded, expanded authority to terminate awards mid-stream, new restrictions on what funded researchers can publish, say, or collaborate on internationally. 

Science is not the only thing at stake. The federal grants system funds an enormous range of what government actually does: states building out energy infrastructure, local health departments running maternal care programs, nonprofits delivering workforce services, cities trying to modernize how they serve residents. OMB’s proposed rule governs all of it: billions in federal grants, every dollar now subject to the same appointee review and presidential priority test. A political appointee gets to decide, mid-stream, that the work no longer matters. That’s not a grants system anyone can build anything ambitious in.

Replacing expert peer review with political appointees doesn’t make federal financial assistance of any kind more accountable to the public, it makes it accountable to whichever political team won the last election and their appointees’ desire to micromanage. Every grantee in America is now operating on that assumption.

The proposed change to §200.205 would formalize prior guidance for senior appointees – not career scientists, not program officers, not people who know how to do this thing – to review every discretionary grant before it’s awarded (science and beyond). 

For science specifically, it goes further: appointees expressly prohibited from deferring to peer review [read: experts] on the matter. Since WWII nearly every science agency has emphasized independent expert peer review as THE measure of scientific merit. Even your 8th grade science teacher emphasized this. Under the change to §200.205(d), a political appointee can override the scientific community’s judgment just because. Discretionary awards must also “advance the President’s policy priorities” – not national security, or public health, nor foundational science priorities. Presidential ones. 

Under current rules, terminating a grant requires a finding of noncompliance or fraud, which is a high bar because multi-year awards require multi-year commitments. You can’t build a cutting edge research program or radically transform a grid on a one-year horizon. The proposed change to §200.340(a)(2) drops that bar entirely. No finding required; termination is available whenever an award no longer aligns with agency priorities or the national interest. Yes that could mean almost anything. There are currently 150,000 active multi-year awards operating under the assumption that finishing what they started is possible. The chilling effect on applications may be as significant as the terminations themselves: why spend months on a competitive grant application, or structure your organization around a multi-year award, if the whole thing can evaporate at will?

Then there’s the elimination of fixed-amount awards. Smaller organizations, the ones without teams of grants managers and compliance lawyers, depend on fixed-amount awards because they’re manageable. Kill them and you’ve told a significant chunk of the grants ecosystem that they’re no longer in the running. 

Proposed changes to §200.421, §200.432, and §200.461 restrict the use of federal funds for publications, press communications, and conference attendance. For researchers, this directly conflicts with a longstanding OSTP mandate requiring federally funded research to be published open-access. You can’t comply with one federal requirement without violating another. But the restrictions aren’t limited to science: any federally funded practitioner sharing findings, any state agency presenting at a national conference, any nonprofit documenting what their grant actually accomplished runs into the same wall. In other words: you can’t do public work that the public can see and learn about. 

The proposed changes to §200.220 and§200.202(e) would require case-by-case approval for international research collaborations — a domestic-first framework that treats standard scientific practice as a special exception. (We did just bring a Canadian to the moon with us, for the record.) International cooperation is standard practice across many scientific disciplines; fruitful, peaceful scientific collaboration has been the norm with any number of countries (that we are already engaged in multilateral collaboration with)? A domestic-first framework that requires case-by-case approval would be detrimental to international public health efforts, where foreign scientists are leading research into treatments and containment. 

Changes to §200.206 look a lot like a loyalty test and not just for science. Any organization applying for a federal grant would be subject to eligibility review based on its affiliations, activities, and perceived alignment with administration priorities. Congress tried this one in 1949 when they tried to sneak in a loyalty test affidavit into the National Science Foundation Bill. We said it in 1949 and we’ll say it again: “Its sole justification for inclusion is concession to current fears and hysteria. Totally ineffective in detecting actual enemies of the U.S., it is significant only in its indication of the state of mind of the country – one of unreasoning insecurity and fear. To fail to oppose the provision is to accept this state of mind and permit it to go on to even more dangerous manifestations.” 

The provision that should worry everyone is in §200.202(a)(iii): a requirement that federal programs “align with administration policies and priorities.” Science funding has always been political and anyone telling you otherwise is selling something. Democratic legitimacy matters for public investment, and the federal government should be accountable to the people whose taxes fund it. But there’s a meaningful difference between federal priorities and administration priorities that this rule deliberately erases. The federal government is a massive institution with a general mandate to serve the public across generations. An administration comes and goes every four to eight years, with narrower ideological agendas and a much shorter time horizon. Requiring every grant dollar to align with the current administration’s priorities isn’t accountability, it’s a different thing entirely.

Two things can be true 

To be fair, a few things in this rule are worth having. NOFO streamlining and encouragement of multi-year awards are real improvements to a pre-award process that has frustrated applicants for years. The rule also comes down hard on merit review as a source of stagnation, and to an extent that’s not wrong. We’ll take those. (Further FAS insights into merit review are forthcoming, but traditionalists be forewarned: we make a many-pronged call for reform.) As a scientific community we have to own the current flaws. We also have to build something durable, not treat them like a suicide pact.

Step back from the individual provisions and the systemic problem becomes clear: this rule is a demand signal and institutions will respond to it rationally. Universities, nonprofits, state agencies, and local governments will look at these conditions — arbitrary termination authority, political pre-clearance, loyalty reviews — and make reasonable decisions about what’s worth pursuing. You cannot have loyalty tests and a scientific effort the size of the Manhattan Project or in new areas of discovery where the trajectory is unknown. Smaller institutions without the legal and administrative capacity to manage the new compliance burden will exit the market; larger ones will self-censor. The portfolio of federally funded work will get narrower because the risk calculus changed.

There’s an irony here for anyone who believes in competent government: a system that can override expert judgment at will has less use for experts. That’s a demand signal too. There is a world beyond merit review emerging, like the NSF X-Labs initiative, team science models, Tech Labs built on baked-in independence. Exciting constructions, none of them ready for prime time. We can’t throw the baby out with the bathwater. Better results from federal grants are a legitimate goal, and the path there isn’t complicated to describe: grants systems that actually reflect the communities and problems they’re meant to serve, and that are designed to learn from what happens after the money goes out the door. We don’t have that now and this proposed rule doesn’t get there either.

So what’s next

Many of our peers are outraged. AAAS CEO Sudip Parikh calls these proposed changes “a brazen power grab,” while Irene Ngun, Assistant Director of Policy and Advocacy at Stand Up For Science, plainly calls it a “weaponization.” Across the science and technology policy community, there is a feeling that this represents the final bell toll of an apocalyptic-level event for American science. Whether or not that is your read on the situation, this is as significant as a change as can be. Independence is the source of scientific integrity. (And those outside of this community should care too: OMB’s proposal would govern billions in federal grants. Every dollar everywhere will be subject to the same appointee review and need to meet presidential priorities.)

There is no question this is a Big Deal. If you are a university or research lab, or aspire to work in one, or are simply an enthusiast of federally-funded research (the kind that gave us the internet!), what’s next will matter. It is likely these changes will lead to litigation. When that time comes, we will offer dispassionate analysis, giving primacy to facts and figures. But before that, we are exploring every avenue available to us to revert this threat.

• We’re in constant contact with science advocacy groups, industry, scientists and innovators, and policymakers to stay on top of the latest dynamics and opportunities for action. 
• We’re reaching out to congress and the executive branch with substantive oversight priorities. We need members from both sides of the aisle to act on these. Raise your hand if this is you. Some of these include:
  • Conflicting mandates between this rule and other rules throughout government (like the Office of Science and Technology Policy’s open access publishing guidance), 
  • Clarification about how this rule affects existing and multi-year awards, and 
  • A Government Accountability Office study request. 
• We’re preparing a public comment and encourage you and your institution to do the same.

There is a growing community of people inside and around the federal government who believe we should apply the scientific method to science itself: how grants are awarded, how peer review works, how labs are organized, how R&D portfolios are built. In some circles this is called metascience, others it goes by science of science, or research on research. The label matters less than the conviction that how we fund and structure science isn’t fixed and that we could be doing it a lot better.

The political moment may be unusually open to acting on this conviction, as R&D institutions face pressures and disruptions not seen since the post-World War II era.

A quick orientation on where things stand: most metascience activity today is external researchers studying government R&D programs from the outside, and that community is growing. Inside the government, interest is picking up: a handful of agencies are starting to think seriously about what internal capacity might look like, with NSF’s proposed metascience unit in the FY2027 budget request as the most visible signal so far. Whether that momentum builds into something more structured, or stays scattered or administration-dependent, remains to be seen.

There’s no Evidence Act equivalent being seriously discussed, but it’s a great moment for laying the ingredients for what comes next. This piece is aimed at both audiences: researchers trying to make their work matter inside agencies, and the agency leaders and staff thinking about standing something up. 

I want to be a serious champion for building this capacity inside the government. But I also want to make sure we don’t sleepwalk into a set of traps that I watched swallow another reform movement — one I was part of! — over the last decade. The federal evidence community, which grew dramatically following the Foundations for Evidence-Based Policymaking Act of 2018, had serious ambitions and major accomplishments. It also made structural mistakes that a metascience community could easily repeat. Here’s my take on how we can learn from each other (and what you should steal).

What the evidence community got right (somewhat-evidence-based answer: quite a bit!)

The Evidence Act was a major achievement both as legislation and systems change that continues to make stronger policy possible. It normalized the idea that the government can admit knowledge gaps and curiosity. That agencies should be asking hard questions about whether their programs work, and that building the infrastructure to answer them is important (to me, this is a fundamental of democratic governance, something we owe the American people to maintain legitimacy). Asking “does this program actually do what we think it does?” could read as hostile or politically threatening. The Evidence Act made it standard management practice and that cultural shift, however incomplete, was not nothing!

The infrastructure that followed (Learning Agendas, Evaluation Officers, CDO Councils, OMB evaluation guidance) created shared vocabulary and accountability that hadn’t existed before. In the agencies where it took hold, it opened space for questions, roles, partnerships, and curiosity  that previously had no institutional home. Giving someone a title that made clear their role was to facilitate knowledge generation and translation in a bureaucracy that knows how to build on structural opportunity is a big step. Setting a standard process to collect questions needed for effective governance is huge, culturally and administratively. 

External accountability mattered too. OMB guidance, GAO oversight, and congressional interest created pressure that internal motivation alone couldn’t sustain. Compliance requirements work when someone is going to ask about them and care about the response (spoiler: I had to do this a lot, and occasionally explain the difference between, say, audits and evaluations). Where the evidence work shaped decisions, it was usually because someone with budget authority and leadership access wanted it. And because a community of practice built enough shared norms to carry the work across agencies and administrations.

What went wrong (or not as well as it should have) and why metascience can learn from our experiments 

Insert here tremendous respect and awe for the evaluation officers and their colleagues who fought the hard fight without the support they should have had. 

We built supply without equal attention to demand. Evaluation planning and learning agendas were sometimes produced because Congress and OMB required them, not just because program offices were always asking for answers. Carol Weiss has called this the “two communities” problem for ages: researchers and policymakers operating in parallel universes with different timelines, incentives, and languages. And while the community has iterated in that moniker and concept for a long time, we’ve never quite solved it. Too often the results landed in reports nobody read (if they were published at all!), or in inboxes where they became someone else’s problem, or on a timeline that didn’t match decisionmaking. The basic customer question — who needs this, and when, and in what form — wasn’t asked enough, and when it was, we didn’t have great leverage to change.

We got divorced from the workflow. Evaluations routinely finished after the budget cycles and policy windows they were meant to inform. The evidence community struggled to map its work to actual decision points: appropriations timelines, leadership transitions, program reauthorizations. While the evidence community would be well served by considering a range of flexible and timely evidence models, gold-standard evidence methods like Randomized Controlled Trials of major programs can and do take time (certainly more time than a single fiscal year).  Unsurprisingly, format mattered too: the people who needed to act, needed a two-pager, or, better, a conversation; more than a technical report delivered six months after the window had closed.

We (cringe) made ourselves hard to work with. The evidence community was often expert-centric rather than partner-centric, more focused on what constituted the highest quality legitimate evidence than on what would be useful, approachable, or on what timeline (see Jen Pahlka’s thinking on “stop energy” vs. “go energy”). The vocabulary was sometimes alienating and methodological gatekeeping was a real downer. More structurally, evaluation offices were sometimes poorly located organizationally, sitting outside program design and budget processes where leverage lived, and relationships upstream or downstream didn’t always come naturally.

We had a LOT of questions but buried them where no one could find them. On the other side of the equation, we too often made a reasonably good effort at compiling our research and evaluation questions in Learning Agendas and did the government equivalent of post and pray, launching a PDF deep on a federal website without requisite effort to connect it it to researchers who would’ve loved to follow up. There were great exceptions: outside the government, I participated in a “matchmaking” session on the President’s Management Agenda Learning agenda, connecting federal leaders with research teams excited to engage on their challenges.  The OMB evidence lead I was privileged to work with created a Learning Agenda Questions Dashboard (on evaluation.gov, RIP), and the “evidence project portal” to consolidate opportunities for outside researchers. 

We lost the hiring, funding, and buying battles. The Evidence Act directed OPM to develop a hiring classification to support building out the evaluation community. As the person at OMB responsible for pushing that effort (years after the deadline), I watched OPM’s underresourced and sometimes calcified approach to classification make this so challenging that colleagues described it as the worst professional experience of their careers. As an ongoing consequence, agencies defaulted to using generic job series for evidence functions that couldn’t elevate qualified people. Evaluation officers are frequently double and triple-hatted as performance managers, data scientists, and learning officers,  often with no dedicated staff, no protected budget, and no solid career path. Likewise, the paths to funding research were highly varied and full of dragons. I could not in good faith consistently tell an agency “here’s how to get your high priority research funded” because it was so variable across agencies. Likewise, unwieldy procurement vehicles added unnecessary burden to a process that already struggled to get RFPs out the door. 

We struggled with the theory of adoption. The simplistic foundational assumption was: create the requirement, do the study, policymakers use it; policymakers create a program, evidence is generated, change is made. It SOUNDS right but in practice so much was wrong in that chain because it didn’t consider incentives and timelines. Who needs this finding the most, and when? What would motivate them to change their behavior? What’s standing in their way? Am I asking a question they can act on? Even when the evidence was good, the pathway from finding to decision was assumed rather than designed.

We kept building administrative burden while assuming people wanted it. Learning Agendas and Annual Evaluation Plans and Policies are great concepts and valuable ways to bring learning and policy communities together. But even in the best of worlds these were still compliance requirements layered on top of staff who were already stretched, and in the worst, when done badly, they overcomplicated what should have been a culture changing moment. A metascience function that responds to that history by adding more reporting requirements would be its own kind of failure. The goal should be fewer dragons and headaches on on the path from question to useful answer.

And we struggled with politics. The truth is that many policy leaders don’t want to know if their idea won’t work or didn’t work. Publishing work that shows waste to taxpayers is politically costly, and that problem doesn’t disappear because a law requires evaluation plans. Likewise, sometimes programs do work well and the evidence shows it brilliantly, but politics means that success is less desirable to advertise. 

But failures weren’t all inside the government. The academic communities best positioned to do rigorous, policy-relevant evaluation work faced their own incentive problems. Publishing in top journals rewards novelty, methodological elegance, and positive findings (even if you have to p-hack your way there); relevance to a policymaker’s actual questions is less important. The researcher who produces a technically brilliant study and never engages with the agency whose program they studied is likely more fully rewarded by their institution than those supporting policy design. Fortunately, there are researchers across disciplines who care about public impact, and there are organizations like the Evidence-to-Impact Collaborative at Penn State doing serious work to build the infrastructure that makes researcher-policymaker relationships function. But consistently orienting the research community toward the questions that matter inside agencies is a question metascience will inherit too.

Hark! There is a Fork in the Road! 

The emerging federal metascience community is asking fascinating questions that are equally vital for democratic legitimacy: beyond “did this program work” to “how does the federal R&D enterprise itself work, and how could it work better?” 

But it faces the same fork in the road and even more disruptive moment. The metascience community is also trying to do this work in a volatile moment, where the institutions being studied are changing fast, and where interest in metascience inside the government is emerging alongside real disruption to the research enterprise. That combination is an argument for urgency: the window to shape how internal metascience capacity gets built may be shorter than anyone expected. A unit stood up quickly, without a protected budget or independent authority, narrowly focused on politically convenient questions, and with no plan for continuity — that’s a real risk. The design choices that prevent it aren’t complicated, but they have to happen early. 

A metascience function that produces insights about peer review and grant mechanisms without building serious demand from program officers is the evidence community’s supply problem in a new form. A “Metascience Officer” role with no potential for career path or growth, no protected budget, no customer or audience, and competing responsibilities is the Evaluation Officer problem with a different name. Learning agenda questions about R&D mechanisms that nobody follows up on become checkboxes. Evidence that never reaches the room where program design decisions happen, regardless of its quality, has no impact.

Part of what makes institutional design so hard is that the distance between “we produced amazing insights” and “that knowledge changed anything” can be enormous. Experts at the Institutional Architecture Lab have a great framework here. They distinguish between institutions that produce knowledge (authoritative but loosely coupled to action), institutions that have knowledge formally embedded in decision processes (where findings must be engaged), and institutions where specific evidence thresholds trigger changes in practice. The Evidence Act was designed for the middle category and often ended up in the first. 

Before we tell you where to go next, a note that applies to both communities: the questions metascience is asking aren’t exactly new inside agencies. Learning Agendas have been wrestling with peer review design, funding mechanisms, and portfolio effectiveness for years: imperfectly, under-resourced, but with real interest and curiosity. Arriving like you’re the first person to notice the building is on fire is a real pattern in the good governance world, and it’s one the evidence community sometimes got too good at before metascience got here. Ask what’s already been tried before you propose what’s next. It’s faster and it might save you from reinventing something that already didn’t work.

What to do instead: a checklist we wish we’d had

• Start with demand AND supply. Map the actual decisions agency leadership faces, like peer review redesigns, new funding mechanisms, portfolio rebalancing, and build the research agenda around those decisions instead of around what the metascience community finds most interesting. Before you build anything, build relationships with the people who will act on what you find. Understand what questions keep them up at night.
  
• Master the workflow problem. Know the decision calendar and what inputs people will actually read, in what format, and when. A finding that arrives after the window has closed doesn’t exist for practical purposes.
  
• Embed partnership in the working model. Co-design questions with program officers and make their success your success. Whether metascience becomes a resource people seek out or an office people avoid is something you can shape now.
  
• Take incentives seriously. Just because a metascience function exists doesn’t mean program officers will care, or that agency leaders will act on what it produces, or Congress will be curious. What are program officers actually rewarded for? What are agency leaders trying to protect? What would make peer reviewers engage differently with evidence about their own processes?
  
• Develop in-house capacity in addition to solid relationships with the outside.  While it’s vital to find consistent and reliable communication paths between government and external research institutions, the government also needs some internal capacity to help be more responsive, flexible, and secure on time sensitive and issue sensitive questions.
  
• Design the talent model with purpose instead of happenstance. Is this a destination or a waystation? A fixed-term appointment that makes people more attractive when they leave, building an alumni network that carries the practice forward? Or a permanent career function that builds institutional memory? Both have a role: pure rotation and you lose institutional memory; pure permanence and you lose touch with the field.Think about where people come from, where they go, and what signal the function sends about whether this is meaningful work or a backwater.
  
• Build for durability. External accountability, cross-agency benchmarking, champions in OMB and Congress are what keeps a function alive across administrations. Build them early, when you have momentum and goodwill (by the way, though evidence work is still doing democracy good across government, the Evidence Team I led at OMB doesn’t exist anymore).
  
• Invest in relationships before you need them. One of the deepest structural failures in the evidence community was treating researcher-policymaker relationships as something that happened naturally, or that individual researchers could maintain on their own. Individual researchers can’t track decision-makers across election cycles, persist through staff turnover, or stay useful for years before they need anything back. And FAS research on local governments shows that policymakers often struggle to find the “front door” into research partnerships, even when they do want to build those relationships. The result is that academic engagement with policy tends to be episodic: it activates when someone needs something, fades when the grant or policy window ends, and depends entirely on who happens to know whom (there’s also interesting research by Max Crowley and colleagues that suggest all these ties are better built early in careers and levels of influence, on all sides). A well-designed metascience function has the ability to solve that “front door” problem – but should treat relationship-building as a core function, rather than assuming it will happen automatically, and invest in presence before anyone needs help.

The steps taken over the last several years to build federal evaluation capacity were good ones. The people who did that work were serious, and they built something real under difficult conditions. We hope this piece lands as what it’s meant to be: a love letter to that work, and a friendly peer review of the structural choices that will determine whether metascience does better

It’s been a little over a month since the Federation of American Scientists’ (FAS) inaugural panel on Climate Interventions at DC Climate Week, hosted alongside the Chesapeake Climate Action Network…and I’m still thinking about it. 

Why? Because with our climate rapidly deteriorating, the idea that there’s an underresearched suite of technologies that could buy us more time to decarbonize and save countless lives is one that sticks with you. 

Sure, shooting particles into the stratosphere to reflect sunlight back into space, or spraying seawater on glaciers to stop them from falling into the ocean, sound like ideas from a science fiction novel. But so does New Orleans falling into the ocean, or extreme heat making parts of the world unlivable, or (more nerdily) Atlantic meridional overturning circulation (AMOC) collapse. These things are all now in the realm of the possible – or already happening. So what do we do about it? 

For one, I think we hear out the experts that take these technologies, collectively known as “climate interventions” or “climate stabilization” approaches, seriously. Some of those experts spoke on the DC Climate Week panel and gave me the brain worm that is this blog.

• Andrew Light, Former Assistant Secretary of Energy for International Affairs and Distinguished Fellow at the University of Chicago Institute for Climate and Sustainable Growth
• Shuchi Talati, Executive Director of Alliance for a Just Deliberation on Solar Geoengineering
• Natasha Vidangos, Associate Vice President, Innovation and Technology, at the Environmental Defense Fund
• FAS’ very own Hannah Safford, Associate Director of Climate and Environment

The panelists made one thing loud and clear: we need better tools to respond to the climate crisis, as well as transparent, equitable research governance frameworks for developing them. 

Climate Interventions 101

If you’re new to the climate intervention space, welcome! The TL;DR: if we can’t stop the most catastrophic impacts of climate change with current tools quickly enough, then we need a bigger toolbox.

To put it another way, think of climate interventions as a life jacket instead of a rescue boat. In this metaphor, the rescue boat is continued clean energy deployment and carbon capture, entrepreneurial re-thinking of our climate laws and policies, and a holistic approach to decarbonization that’s grounded in transparency, equity, and legitimacy. Climate interventions are what keep you afloat long enough for the real help to arrive.

The panelists focused on one specific type of climate intervention: solar geoengineering, also called Solar Radiation Modification (SRM). SRM aims to artificially lower global temperatures by reflecting incoming sunlight back into space, thereby potentially stalling the worst impacts of climate change. There are three main types of SRM approaches: Stratospheric Aerosol Injection (SAI), Marine Cloud Brightening (MCB), and Cirrus Cloud Thinning (CCT). SAI is usually the subject of most conversation given that it has by far the greatest potential to affect temperatures on a global scale.

Research ≠ Deployment 

The panelists were clear that talking about the need for SRM research isn’t the same as calling for deployment (i.e., ultimate large-scale use of SRM techniques). Take hurricanes – Meteorologists study hurricane patterns not because they want a hurricane to make landfall, but to understand what might happen if it does. You can support the research without being pro-hurricane. Same idea here.

Since there’s no world in which we don’t benefit from learning all we can about these technologies and their potential risks and benefits, research should be nonnegotiable. 

The Big Deal About Research Governance 

The next question is: who’s in charge and gets to make the decisions about how we do said research? That’s what “research governance” is about. Research governance sounds like one of those abstract terms that elites use to confuse people but really just refers to the nuts and bolts of how research into SRM (and other climate interventions) gets done – what the regulations are, who’s involved, and what principles inform decision making.

The panelists felt strongly that the “who” of research governance is almost as important as the “what.” A global intervention needs global involvement in the research design. Impacted countries and communities need a seat at the table to shape the work and think collectively about how research moves forward.

Whether impacted communities are involved can be the difference between success and failure. Two attempted outdoor experiments, SCoPOx (at Harvard) and SPICE (in the UK), failed to secure public buy-in from the beginning. Both were shut down and became unnecessarily politicized. Australia offers a counter-example. That country has successfully carried out MCB research without much backlash because it prioritized public engagement and targeted something tangible the public cares about (protecting the Great Barrier Reef) in its outreach. When you hit people in their hearts, they’re more likely to listen. 

Multilateral Action, Please!

SRM is global in nature, so it matters how other countries are approaching (or ignoring) this issue. As of now, there’s no multilateral governance framework for climate interventions, or even an appropriate forum for developing one. Which is a little crazy considering there seems to be a multilateral group for almost everything. Given this, a path forward may be for small groups (or “clubs”) of countries to begin setting norms, standards, and research frameworks together, similar to other international science coordination. For example, the Global Methane Pledge is a coalition of countries that agree to take voluntary action to reduce global methane emissions. A similar research coalition could form around SRM, or climate interventions more broadly. 

Research requires money. Currently, only the United Kingdom (UK) funds climate interventions research at any significant scale. And even the UK’s program, structured under their Advanced Research and Invention Agency (ARIA), has a budget of only about $76 million USD – a minuscule amount compared to other critical research areas. Multiple countries working together could pool resources to increase the amount of funding in climate intervention research, and probably should, given what I’ll call “The Stardust Situation”. That situation is the reality that when the government leaves gaps, the private sector sometimes fills them. And in the SRM space, an American-Israeli private company called Stardust is developing its own particles for SAI to fill the gap. Stardust has raised about $60 million to date – almost the entire budget of ARIA. 

One could argue that private-sector innovation is good, and there’s some truth to that. But as Hannah Safford put it recently, we might also “not like the choices” that the private sector makes without any guardrails or shared goals and norms around SRM research and experimentation. After all, few people these days are loving our unregulated AI overlords. But, and I’ll quote Hannah again, the United States “government has shown more interest in banning climate science than in thoughtfully governing emerging technology.” The panel agreed it’s past time for this to change.

Building Something New

To sum it up: research can’t responsibly proceed without governance, but governance shouldn’t strangle research. Figuring out that balance is the work ahead in the SRM space. The path is filled with tough questions, but the exciting thing is that we have an opportunity to respond right the first time, since we already know what doesn’t work. So many policy areas are either deeply politicized and/or cluttered with outdated laws or old, creaky institutions. This isn’t the case for climate interventions. Here, we can build new frameworks for climate interventions research and governance that have equity, transparency, and legitimacy baked in from the start. We don’t have to fit a square peg into a round hole. That’s something I won’t stop thinking about anytime soon. 

Interested in FAS’ or CCAN’s work on climate interventions? Visit the FAS & CCAN websites.

It’s here! After months of delay, the council tasked by President Trump to review the Federal Emergency Management Agency (FEMA) released its final report earlier this month. 

If you’re not a disaster policy nerd like we are, here’s some quick background.

Up until the founding of FEMA in 1979 under President Jimmy Carter, disaster response in the United States was largely disorganized and reactive. The agency has since gone through several major updates. Passage of the Robert T. Stafford Act in 1988 established the formal mechanism for disaster declarations and federal disaster response, while in the years following the 9/11 attacks FEMA transitioned from an independent cabinet agency to part of the newly established Department of Homeland Security. 

Recently, FEMA has come under intense scrutiny from the second Trump administration for being seen as ineffective, bureaucratic, and in some cases politically biased against him. While FEMA has had issues in the past related to delayed response times and survivors receiving aid (and criticism with how it handled Hurricane Maria), reports show that many of these issues may be related to an increase in major disasters due to climate change, as well as a lack of regular training, sufficient funding, and adequate staffing – rather than structural issues with the agency. In addition, traditionally “red” states (like Texas, Louisiana, and Florida) typically receive more FEMA funding due to the amount of disasters they experience, so claims of political bias are largely unfounded. 

Yet when Trump took office for the second time, there were calls to get rid of FEMA altogether. However, after pushback from citizens and lawmakers and several major disasters, the aforementioned council has opted to avoid recommending completely dismantling the agency. Instead, the council proposes major changes to the way FEMA operates (the council repeatedly refers to a “transformed agency”), via ten general recommendations. Here’s our quick snapshot of the good, the bad, and the ugly of these recommendations, with more detail below:

• The Good: An emphasis on mitigation and streamlining the application process for disaster survivors, along with a focus on getting money to states and survivors quicker.
• The Bad: Shrinking and privatizing most of the National Flood Insurance Program (NFIP), while slashing overall federal funding for disaster response and recovery.
• The Ugly: An unrealistically short timeline for implementing recommendations in the report, as well as a reductionist approach to how disasters enact damage.

Also, a quick note on the United States’ approach to disasters: there is generally an overemphasis on acute economic impacts, and not what they do to systems as a whole long-term. As many disaster researchers will tell you, while hazards can be natural, disasters are not. Disasters are the result of hazards adversely impacting people and their communities due to decisions that increase vulnerability and risk exposure. If we limit our approach to disaster recovery to include only economies and infrastructure, we’ll tend to overlook other critical factors, like public health, social connection, and community wellbeing, that contribute to these vulnerabilities. Just because a house has been rebuilt or power has been restored does not mean recovery has been achieved. Before we implement sweeping changes to the agency responsible for disaster response, it’s important that we as a nation consider this in our approach to disasters.

With that aside, onto the deeper dive into the good, the bad, and the ugly of the review council’s report.

The Good

First, the council re-emphasizes FEMA’s core mission of “[reducing] the loss of life and property and [protecting] the Nation from all hazards”, with the guiding principle of disaster response being “locally executed, state or tribally managed, and federally supported”. This is in line with the survivor-led response approach that many local recovery groups have recommended. Communities have the local knowledge and boots-on-the-ground presence needed to ensure that recovery efforts are appropriate for their situations and contexts, but often lack the funding to implement tailored solutions. The council suggests that FEMA strengthen regional coordination, which could in turn support community- and survivor-led response. 

Another positive is the council’s emphasis on rapid mitigation and hardening support to increase efficiency and prevent damage from future disasters. This includes modernizing the federal disaster response by implementing the National Resilience Strategy and updating flood risk information and land use to prevent building in flood plains, both common-sense solutions that can prevent the worst damage from disasters before they even occur. They additionally recommend a two-phase program that would replace the Hazard Grant Mitigation Program (HGMP) with a new program designed to more rapidly distribute federal funding to states (the first 5% of federal funds within the first 30 days following a disaster declaration, followed by an additional 10% within six months). The council calls this new program the “Refined Risk Reduction” Program (R3P), and could potentially address issues survivors have brought up with administrative burden around disaster aid, such as by modifying the Individual Assistance Program and consolidating relief applications into a single direct payment program. There are also specific relief allocations for renters (who often get left out of recovery discussions), including the equivalent of three to six months of rent.

Finally, a recommendation could be either positive or negative (depending at least partially on the details of implementation) is changing how surviving homeowners get reimbursed for individual assistance, including how the amounts are calculated. Currently, home repair assistance payments are capped at $25,000 and based on loss estimates, regardless of property value. The council suggests changing this cap to no more than 15% of the home valuation (so a home valued at $250,000 would qualify for a maximum payment of $37,500), but expanding the purpose of such payments to cover everything from home repairs to funeral costs – i.e., requiring the payments to stretch further than they do currently. Another issue is that FEMA funding has been found to favor wealthier individuals, and basing funding on home valuation has the potential to further drive disparities in aid. Supplemental funding opportunities and/or proactive aid and assistance for lower-income families could potentially reduce this risk.

The Bad

Perhaps the most concerning recommendation of the council is its call for a “lean FEMA workforce”. While the council is less aggressive overall in demanding FEMA staffing reductions than previous drafts (and now just calls for a strategic review of requirements to “determine appropriate staffing levels”), further staffing reductions could exacerbate issues we’re already seeing with FEMA from previous personnel cuts. Disaster survivors have also condemned further FEMA staffing cuts. The council also suggests adjusting how insurance rates are calculated under the National Flood Insurance Program (NFIP) and shifting more flood insurance policies to private markets, which could prohibitively increase premiums, decrease regulation, and lead to more uninsurance and underinsurance in risk-prone areas unless there are appropriate safety measures in place. 

Finally, the council recommends decreasing the overall federal share of disaster assistance funding from 75–100% to 50–75% of costs, with states expected to cover the rest. Many states do not have resources to cover the difference – at least in the near term. With a sufficient transition period, though, more heavily weighting state responsibility for disaster aid may increase sustainability in the long term given that the Disaster Relief Fund repeatedly runs low on funds, and that there are concerns with fund depletion as disasters continue to increase in frequency and severity. Another concern is the council’s prioritization of “high performing states”. While this would encourage more states to have hazard mitigation plans in place, it could result in biased decision-making that would favor certain states, and may leave states with fewer financial resources or rare disaster occurrence with less support when it’s most needed.

The Ugly

The biggest overall issue with the council’s suggestions is that they recommend a 2–3 year timeline for states and tribal governments to prepare their fiscal and physical resources to lead disaster response efforts (rather than relying on FEMA). This is an unrealistic timeline, as many states do not currently have sufficient emergency management resources, legislation to establish and support relief funding, or identified revenue streams to pay for the increased cost-share for states. And on top of that, some state governments (like Texas) only meet every two years, making the 2-3 year timeline impossible. Another issue with the council is the apparent bias in its makeup. While it did include representatives with leadership and emergency management experience from hard-hit states like Florida, Texas, Louisiana, Mississippi, and Virginia, there was a notable lack of members from other disaster-prone parts of the country, like California.

Another problem is the council’s recommendation of using a parametric insurance program to replace FEMA’s current Public Assistance Program (the main funding source for community-level disaster recovery). Parametric insurance is a type of insurance where payments are disbursed almost immediately following certain trigger events, and while it has demonstrated potential in rapidly distributing funds after certain hazardous events, there are too many variables to feasibly consider replacing the entire Public Assistance Program in 2-3 years. For example, the council includes an example of determining payment amounts by hurricane category (e.g.,: a Category 2 hurricane would disburse less funds than a Category 4). However, hurricane categories are based on wind speed alone, and hurricanes with weaker winds can still do extensive damage through other means, like storm surge and rainfall (Hurricane Ike in 2008 and Hurricane Harvey in 2017 are two such examples). These complexities would have to be accounted for when establishing the thresholds of a parametric insurance framework, and without rigorous pilot testing, runs the risk of over or underpaying states following disasters.

One final concern is the council made no mention whatsoever of the BRIC (Building Resilient Infrastructure and Communities) grant program. This absence from the report likely means BRIC is not a priority for current leadership, despite it being one of the largest sources for proactive mitigation funding for states and communities. BRIC has been the subject of much consternation following its abrupt cancellation in April of 2025 and its later reinstatement in March of 2026 (following a lawsuit from several states). However, there is now a heavy focus on “shovel-ready projects” (i.e. physical infrastructure projects that have already been planned out). While this sounds good for efficiency, as we noted earlier, not all infrastructure critical to community wellbeing and recovery is physical and “shovel-ready”. Things like social and public health infrastructure are just as important for disaster recovery, but tend to be overlooked in recovery efforts. In limiting BRIC funding to these types of projects, states and local governments will be unable to be truly proactive in their mitigation efforts to prevent future damage from disasters. 

Conclusion

The review council’s recommendations are not as bad as they could have been and FEMA’s continued existence seems to be safe (for now). Indeed, many of the recommendations could yield positive results, especially when it comes to reducing the burden and obstacles that survivors face in getting help. However, some of the recommendations (like using parametric insurance methods, reducing state assistance, and attempting to implement sweeping changes over a fast 2–3 year timeline) could pose problems for states, communities, and survivors, and a longer transition period with pilot testing will be needed to ensure these changes happen efficiently and effectively. 

In the mid-1990s, researchers at the University of Texas at Austin developed lithium iron phosphate, the cathode chemistry that would come to dominate the global electric vehicle battery market. The technology was American. A few years later, A123 Systems, a start-up spun out of MIT, commercialized it, building what was then the largest lithium-ion battery factory in North America with the help of a $249 million Department of Energy grant. The technology worked. The company had customers, including several leading automakers.

But the broader ecosystem was not there: EV demand materialized far more slowly than projected, manufacturing costs remained high without the scale to drive them down, and no institutional mechanism existed to bridge the gap between a working technology and a commercially viable industry. The company received substantial public funding, but a single grant, however large, cannot substitute for the sustained ecosystem support at the early and scale-up stages that modern industrial production requires. A123 filed for bankruptcy in 2012. In 2013, China’s Wanxiang Group acquired it.

Meanwhile, China was building that ecosystem. The government launched EV battery subsidies in 2009, mandated technology transfer from foreign automakers, and designated advanced batteries as a strategic priority under Made in China 2025. Chinese firm CATL, founded in 2011, scaled the same lithium iron phosphate chemistry that American researchers had invented and A123 had tried to commercialize. By 2017, CATL was the world’s largest battery producer. Today it holds roughly 38 percent of the global market, with China as a whole responsible for nearly 80 percent of global EV battery cell production. BYD, another Chinese manufacturer, outsold Tesla in 2025 by nearly three to one (4.6 million vehicles versus 1.6 million), drawing on its expertise in battery manufacturing. The chemistry was ours; the industry is theirs.

This is not an isolated story. It is a pattern that repeats across the sectors most critical to American economic and national security. China controls over 60 percent of global rare earth mining and 90 percent of processing; MP Materials operates the only active rare earth mine in the United States. The solid rocket motor supply chain, which is essential to America’s nuclear deterrent and missile defense, has collapsed from six qualified domestic suppliers in the 1990s to two today. China installed 295,000 industrial robots in 2024 while the United States installed 34,000, a disparity that has accelerated since Covid. We now import over half of our active pharmaceutical ingredients, and Chinese companies now run nearly a third of global clinical trials, up from just 5 percent a decade ago. Unsurprisingly, China now accounts for 35 percent of global manufacturing volume (three times the American share) while leading in research and development in sixty-six of seventy-four tracked technology areas.

These figures are not, of course, mere abstract facts; they represent genuine economic and employment realities: for example, the automotive sector alone supports nearly eleven million American jobs. They also carry serious security implications: a defense-industrial base that cannot surge production, pharmaceutical supply chains dependent on geopolitical rivals, and critical minerals choke points that give Beijing leverage over American technology.

Read more in American Affairs.

The energy affordability crisis is hitting American communities hard, and nowhere is the pressure more acute than at the state and local level. Leaders are responding to the needs of their constituents while navigating a tangle of barriers—ranging from project development hurdles to political and social constraints. Tackling these challenges requires a holistic approach, as addressing one barrier—whether it’s clean energy permitting, financing, or supply chains—without the others won’t work.

To tune into the action on the ground, FAS convened practitioners, state and local officials, advocates, and policy experts to discuss what it will actually take to deploy clean energy faster, modernize electricity systems, and lower costs for households. 

We heard about lots of efforts underway in city halls and state capitals across the country, many of which are aligned with our recently released Clean Energy for Local and State Governments (CELS) playbook and other recent recommendations for capacity support and innovation at the state and local level. One message came through clearly: while barriers are real, so are the opportunities. Across the conversation, participants identified practical, high-impact levers that states and cities can use right now. 

The ideas were so good we wanted to share them far and wide—read below for more. 

Building capacity for ambition by maximizing what we already have

States and cities have good ideas—and motivation—to bring down electricity prices. But the reality is more complicated. Institutional and political constraints strongly shape the pace and scope of their desired reforms. State and local governments face legal and administrative limitations, including state-level restrictions related to financing, building codes, and utility authority. Many cities (and states!) operate with limited staff and budgetary resources. Lack of capacity makes it difficult to implement ambitious energy policies – even when there’s political will. 

Expanding this capacity is a path to better government and lower prices—and the first step towards rebuilding trust in government as a vehicle to do big things. Resources are a not-insignificant part of being able to do those big things, but of course, it’s not always possible to hire whole new teams of staff or stand up new programs. It’s also not always necessary!

We heard from state and local leaders across the county about how they’re getting creative with existing resources to carry out their promises to constituents. Permitting processes, for example, are an oft-cited barrier to increasing energy supply and driving down electricity prices. With little meaningful change at the federal level, states are looking for ways to improve their own permitting pipelines. 

Pennsylvania has led on this front by clarifying and centralizing permitting authority across agencies, establishing clear timelines and accountability for permit reviews, and digitalizing processes to cut down on administrative burden. Making progress didn’t require building whole new teams or throwing out environmental protections—instead, Pennsylvania made the permitting process clearer, more consistent, and more predictable to increase certainty for solar developers without increasing impact.

Identifying capacity investments with a high return like these are useful—not just for improving delivery, but getting near-term wins that governments can point to to build trust with constituents and provide proof of concept. The think tank and advocacy community can help by identifying creative solutions to increase government capacity at low cost and better leverage existing capacity. 

PUCs, PUCs, PUCs!

We heard a lot of anecdotes about increased attention on Public Utility Commissions (PUCs) given how hard utility bills are hitting constituents. 

Most critical decisions affecting utility bills occur in regulatory proceedings—rate cases and planning dockets in front of PUCs. However, these processes are often technically complex and dominated by utilities, which typically have significantly more resources and information than governments or community members. States and local governments identified help engaging with PUCs—through more capacity and increased data tranparency—as a key opportunity to reduce energy costs and make other clean energy and affordability programs work. 

Capacity at PUCs themselves also came up as a major barrier and opportunity. States can appropriate additional funds to PUCs to help them access adequate staff and technical expertise, or can establish intervenor compensation funds to help level the playing field in rate cases. Ann Arbor, Michigan reported saving ratepayers over $1 billion through interventions in electric and gas cases, in part by investing in legal and technical support for intervenors. Municipalities in Wisconsin, organized under the Wisconsin Local Government Climate Coalition, also banded together to intervene before the Public Service Commission and advocate collectively.

The advocacy community can help as well. By training intervenors, pressuring utilities to increase transparency or provide additional, and supporting local and state governments’ ability to intervene in rate cases, they can help provide key perspectives and evidence to inform PUC decisionmaking. 

Mind the (financing) gap

Unsurprisingly, state leaders identified the cliff in federal financial support for projects as a reason it is harder to implement state and local clean energy programs. 

Getting creative with financing can help state governments stretch existing funds or partner with peers or community organizations. States can use tools like revolving loan funds to support pre-development and construction financing, pooled lending authorities, or loan guarantees to reduce interest rates. Mechanisms that merge public and private financing capacities or improve transparency and certainty around project development can help public dollars go further. 

States and local governments are hungry for help using creative financing mechanisms. For example, how can municipalities play in using public debt to finance projects and reduce costs? This is a major place where the advocacy community can help. 

Don’t be afraid to experiment!

Policymakers were excited about experimenting with new policies that emphasize affordability, resilience, and economic benefits and in turn broaden political support for clean energy initiatives. One example discussed was the Utah Community Clean Energy Program, a first-of-its-kind opt-out clean energy procurement model created through collaboration between 19 Utah communities and Rocky Mountain Power. Approved by the Utah Public Service Commission in March 2026, the program allows participating customers to support new utility-scale clean energy resources through a modest monthly charge, with income-qualified households eligible to participate for free and all customers able to opt out at any time.

This work is already happening and not just in the areas highlighted here. Creating structures for policymakers to share successes and creative ideas can help multiply wins across the country. Collaboration can also support officials working in politically or institutionally constrained environments, where proof of concept and policy examples can help build momentum. The Metropolitan Washington Council of Governments offers one example of how regional institutions can pool resources to accelerate local action. Through its regional environment fund, the COG supports the design and coordination of climate initiatives that signal aggregate demand across members, like fleet electrification or emissions reductions. It then follows up with implementation guides, technical assistance, and best practices that local governments can adapt. 

There is a lot of momentum in utility operation and regulation to reexamine  the way we’ve always done things. Political will from state or local leadership can help question old ideas and advance new ideas to benefit the public. Combined with successful implementation experiments above, further experimentation and research can drive progress and support for state-level  climate leadership. 

Over the past few months, the Trump administration has been laying the foundation to expand the use of the Defense Production Act (DPA) for energy infrastructure and supply chains. This started back in March when the Trump administration issued an Executive Order extending to the Department of Energy (DOE) the authority to directly engage in contract allocation for energy needs under DPA Title I. 

A month later, on April 20th, the Trump administration released a series of Presidential Memoranda establishing presidential determinations for grid infrastructure, equipment, and supply chain capacity; large-scale energy and energy related infrastructure; natural gas infrastructure; coal supply chains and baseload power generation capacity; and domestic petroleum production, refining, and logistics capacity and delegating DPA Section 303 authorities to DOE. These actions are reminiscent of the series of presidential determinations that the Biden administration issued in June 2022 for energy materials and technologies, which also included transformers and electric power grid components. 

So what does this all mean and why does it matter?

DPA Doing the Heavy Lifting

The DPA grants the President a unique set of authorities designed to direct, expand, and expedite the domestic industrial base for materials, technologies, and energy crucial to national defense when the private sector cannot be expected to meet the nation’s needs on its own. For example, DPA authority was used during the COVID-19 pandemic to expand production of medical supplies and vaccines. 

DPA has a few titles that give different powers when invoked, with Title I and Title III being the most frequently used. Title I gives the President power to require private companies and contractors to prioritize certain contracts and orders over others for national defense purposes, including for materials, equipment, and services needed to “maximize domestic energy supply”. Using Title I, the government can, for example, require that manufacturers prioritize orders for the federal government or domestic customers over foreign exports.   

Title III gives the President powers to expand domestic production and supply of goods, materials, and critical technologies needed for national defense and allows the President to use an array of financial mechanisms to do so. To use Title III authorities, the President must first issue a presidential determination ascertaining that the requirements to use the authority have been met and then delegate the authority to an agency to implement. Hence, the series of presidential determinations issued last week. 

Breaking the Bottlenecks 

Notably, both the Trump and Biden administrations have issued presidential determinations to address vulnerabilities in grid component supply chains. The Trump administration’s determination states that the United States’ deteriorating grid infrastructure, constrained by long lead times and shortages of grid components, is detrimental to national defense; industry cannot alleviate these supply chain bottlenecks without government intervention; and the authorities provided in DPA Section 303 are “the most cost-effective, expedient, and practical alternative methods for meeting this need”. DPA Section 303 authorities invoked by Trump include “purchases, purchase commitments, financial support for the development of production capabilities, or other action” necessary to alleviate supply chain vulnerabilities. 

Through these DPA determinations, the Trump administration is explicitly tying the U.S. energy system to national security and making energy supply chains a national priority. In the context of grid supply chains, this is absolutely crucial given domestic shortages of components like transformers and breakers and an overreliance on imported goods in a time of geopolitical competition and fracturing relations. 

Grid equipment, however, was not the only focus of Trump’s actions. Three of the other determinations support expanding fossil fuel infrastructure for natural gas, coal, and petroleum production. The last determination, focused on “large-scale energy and energy-related infrastructure”, appears to be a catch-all for any other energy projects that the administration wants to support. The memorandum invokes Trump’s prior Executive Order 14156, which declared a “National Energy Emergency” due to the U.S.’ “current inadequate and intermittent energy supply.” This suggests that intermittent renewables like wind and solar will likely be excluded from eligibility. 

Such a large number of determinations raises questions about which ones will take priority. Can the U.S. government simultaneously support the expansion of natural gas, coal, petroleum, grid supply chains, and other large-scale energy infrastructure all at the same time? Trump’s DPA determinations explicitly direct the Secretary of Energy to implement them, adding a level of urgency and accountability. Yet, executing on all of these determinations will require significant coordination, staffing, and funding that has not yet materialized. 

Show Me the Money 

As we have written before on grid supply chains, federal policies like DPA can help correct for market failures, derisk the construction of new manufacturing facilities, and unlock faster grid modernization, but issuing a presidential determination is only the first step. Without a clear funding mechanism to implement the directives, we can only speculate where the money will come from.

Three possible sources currently exist. First, funding could come from whatever remains of the $1 billion that was appropriated in the One Big Beautiful Bill Act (OBBBA) to carry out DPA activities. Some amount of these funds may have already been committed to the DoD and MP Materials deal, and it is unclear how much remains unallocated or what the administration plans to do with the remainder. 

The other alternative options could be FY27 appropriations or an FY27 reconciliation bill. The Department of Defense (DoD) is requesting an eye-watering $30.4 billion in DPA funding for FY27, nearly 100 times the amount appropriated by Congress for FY26. $30 billion of the requested amount is in mandatory funding, which would have to be appropriated through a budget reconciliation bill that the Trump administration is pushing for. Historically, the Pentagon has served as the manager of DPA funds, allocating funding to other agencies as necessary and directed by the White House, so while DoD is the agency requesting this funding, some amount could potentially be transferred later to DOE.

Complementing these funding sources is the $375 million in appropriations from FY26 to DOE to “enhance the domestic supply chain for the manufacture of distribution and power transformers, components, and materials, and electric grid components.” Typically only funds that Congress explicitly appropriates for DPA can be used to implement DPA authorities, but DOE could use the $375 million for supporting activities to help plan for DPA implementation (e.g. analysis and stakeholder engagement), especially since the goals of the appropriated money overlap with the goals of the DPA determination. 

Now what?

These determinations are just the beginning. Now, it will be up to the administration and Congress to either find existing funding or appropriate new funding. DOE will then need to create and follow through on an implementation plan. We at FAS will be keeping an eye on whether these developments actually materialize over the coming year.

The Office of Personnel Management has been busily reversing course on federal workforce reductions with some splashy hiring announcements. In December, it launched Tech Force, a pooled recruitment effort targeting 1,000 early-career technologists to be placed across agencies for two-year stints. In March, it stood up across-government shared certificate for project managers. It launched an Early Career Talent Network spanning five job categories. Two weeks ago, it expanded Tech Force into cybersecurity. OPM Director Scott Kupor has been explicit about his ambition: this is a “model for more centralized, efficient hiring across government.”

I’ll bite: yes, there’s a lot of promise in that! The instinct behind all of these actions builds on years of initiatives meant to create efficiencies out of the hundreds of thousands of hires made federally each here. Pooled hiring, which should include one well-designed announcement, one shared assessment, and many agencies drawing from the same pool of qualified candidates, is exactly the kind of tool the federal government should be using. I saw this up close when I was at OMB and I fully drank this Kool-Aid. The logic is compelling: (typically) the federal government processes over 22 million applications and hires over 350,000 people into public service every year. No private employer operates anywhere near that scale, which I still believe can be an asset, and pooled hiring creates the entry point to get there. 

But pooled hiring has a track record (going back several administrations), and it’s uneven. Most recently, the Biden administration championed it most ambitiously during the infrastructure surge, where OPM partnered with seven agencies and hired roughly 5,000 employees, doing things like USDA hiring 39 HR specialists off a single certificate (if this sounds underwhelming to you, trust me when I say it’s mindblowing to your average hiring manager; more explained shortly). But the same period produced plenty of pooled actions that generated duplicative work, agency foot-dragging, and candidates who aged off certificates before anyone made them an offer. FAS and others have been studying these challenges in the context of the permitting workforce surge, and the problems are structural, predictable, and repeating. Also? Solvable. 

The concept has promise but implementation has kept breaking in the same places. This piece is about why and about how to get it right, now, while there’s political will and active momentum to use it.

The Design Error at the Center of Everything

First, a quick explainer on how this actually works — because “pooled hiring” gets used loosely and the mechanics matter. A pooled hiring action is a competitive job announcement run either by OPM centrally or by a lead agency on behalf of multiple agencies and intended to fill multiple open positions in multiple agencies. Instead of each agency posting its own announcement, recruiting its own applicants, and running its own assessment, one announcement goes out, one applicant pool forms, and one assessment process screens candidates into a shared certificate of eligibles (government-speak for a ranked list of candidates that agencies can choose from). Agencies that have signed on to participate can then make selections from that certificate without having to run their own action from scratch. OPM-run actions (like the current Tech Force or the project manager cert) work the same way, just with OPM as the lead rather than a single agency. Either way, the cert is the output: a ranked list of candidates who have been assessed as qualified, available to any participating agency to hire from without having to solicit new resumes, review their qualifications, administer assessments, or other tedious parts of the hiring process.

That’s the theory. 

The shared certificate is where most implementations stop. Agencies get a screened list and then do their own thing — their own interviews, on their own timelines, with their own offer processes. Or maybe they don’t, even when they said they would! The coordination ends at the cert. Everything downstream remains fully siloed at each agency.

This is far from the ideal that most policymakers have in mind and what many private employers do. A genuine pooled hiring action pools the whole pipeline. Recruitment, assessment, interviewing, and offers — all coordinated, all running in parallel across participating agencies. That doesn’t work for every role, but in surge situations, or for roles where agencies make dozens of hires of the same roles every year, it’s great. Agencies don’t just agree to draw from the same pool. They show up on the same interviewing days. They make offers on the same compressed timeline. Candidates who applied once get considered by many agencies simultaneously with each running its own slow-motion version of the process.

Almost nothing the federal government currently calls “pooled hiring” actually does this. The new OPM actions are no exception. Tech Force is better marketed than previous efforts, and the private-sector partnerships are genuinely new. But the selection and offer stages remain siloed at each agency and I’ll be very curious if they make selections. That’s the design flaw everything else flows from.

What Breaks When You Don’t Fix the Design

When I was at OMB, we saw these failure modes up close, in what were probably deeply frustrating meetings with the valiant program team as we learned where the seams were. Some things we saw:

Pooled hiring worked when it was a clear administration priority and had OPM and OMB supplementation. Early indicators suggest that Tech Force has success because it’s clear that the administration, the OPM director, and OPM staff are both giving it attention and smoothing implementation behind the scenes.  That’s good for proof of concept, but it doesn’t show the weaknesses that can emerge when administration accountability doesn’t hold agencies to delivery on innovation hiring methods. 

Agencies didn’t trust screening they didn’t run. OPM’s own guidance requires agencies making selections from another agency’s certificate to verify that the original qualification and assessment criteria are appropriate for their position. That verification step becomes a second screening — which defeats the efficiency rationale entirely. Agencies that double and triple-screened candidates created more work than if each had run its own action from scratch. The fix isn’t better guidance, it’s building trust into the design upfront, by ensuring the people trusted with the most relevant subject-matter expertise help design the assessment in the first place.

Demand didn’t stay put. Agencies raised their hands, agencies or OPM ran a resource-intensive recruitment action, and then agencies were slow to hire — or circumstances changed before they did. The August 2024 OMB/OPM hiring memo specifically directed agencies to review available shared certificates before launching new hiring actions — a discipline that, if actually followed, would force better demand alignment upfront. It mostly didn’t happen and, absent the sort of prompting we talk about later, is hard to enforce. Partly this is a culture problem, but it’s also a structural one: agencies that don’t plan for talent surges find that new hiring needs don’t align with their existing workforce plans or their capacity to recruit, assess, and onboard. You can’t opt into a pooled action and then be surprised when the pool fills.

We struggled to tell the right people, and the system didn’t either. There’s a more fundamental problem sitting underneath the demand-alignment failure: hiring managers and HR specialists often don’t hear about pooled hiring announcements at all, and when they do, it’s generally not with enough lead time to actually prepare. Pooled actions get announced through OPM memos and Chief Human Capital Officers (CHCO) Council communications that circulate at the leadership level (and boy howdy did we circulate!), but that information doesn’t reliably travel to the hiring manager who is already three weeks into drafting a job announcement for the exact role sitting in a shared cert. And when it does arrive, it arrives as information: there’s no deadline attached, no checklist triggered, no reason to stop what they’re already doing. As it stands, among the 200K+ hiring managers, most made very few hires a year or in their overall career, so learning a process with barriers to entry was challenging. 

Nothing interrupts the default action.The deeper problem is that nothing in the hiring workflow itself cues anyone to look. When a hiring manager initiates a new action in the hiring system, they’re not pushed or incentivized in any systematic way to check for an existing cert. When an HR specialist begins drafting a job announcement, no flag surfaces to say: a shared certificate for this position series already exists, do you want to use it? The system simply lets them proceed. This means that even when an agency or OPM has done the work of running a pooled action and producing a cert, agencies duplicate that effort anyway; less due to indifference, but because the path of least resistance is to do what they’ve always done, and nothing in the process interrupts that default.

The fix here is partly cultural but a lot technical. The Agency Talent Portal and USA Staffing need to surface available shared certificates at the moment a hiring manager or HR specialist initiates a new action for a covered position: as a required check embedded in the workflow itself. If you’re about to post a GS-12 data scientist announcement and there’s an active governmentwide cert for that exact series and grade, the system should tell you, right then, before you proceed. Opt-out, not opt-in. The current design assumes awareness that doesn’t exist and motivation that isn’t reliable.

Pooled actions were expensive for the “owner” and the experts: While cost-saving overall, running pooled actions could be resource and time consuming for the “owner,” and particularly the subject matter experts brought in for assessment, particularly when hires were not ultimately made. 

The position description bottleneck. Pooled hiring inherits whatever good and bad planning exists in agencies’ position description (PD) libraries. Even for commonly-hired roles, position descriptions are not always readily accessible and, likewise, standard assessments often don’t exist at every grade level. But it’s a bigger challenge than that: the whole GS system presumes (competencies, job task analyses, and more) that every job is highly specialized, not generalizable for cross-agencies pools. FAS documented this directly: OPM and the Permitting Council collaborated to create a pooled, cross-government announcement for Environmental Protection Specialists — one job announcement producing a candidate list many agencies could use. But the assessment became a bottleneck because standard assessments didn’t exist for each grade level in the announcement, requiring significant additional development time. This isn’t an edge case, it’s a Tuesday. Breaking!  OPM Director Kupor just announced a new AI tool to generate PDs!  We’ll follow with interest. 

Hiring managers couldn’t get access without a permission chain. For a new hiring innovation to be adopted, you’d think that all the barriers, incentives, and opt-in/out dynamics would be aligned. You’d be wrong. Pooled hiring at a “mother may I” architecture: system passwords and access, coordinators, gating processes, intermediaries between hiring managers and shared certificates. It’s a design flaw dressed up as compliance. The same 2024 memo had to explicitly direct agencies to update hiring manager permissions in the Agency Talent Portal. That it needed to be said tells you everything about how poorly the access question had been handled. As FAS and the Niskanen Center jointly documented in their analysis of the current OPM hiring memos, the toughest tasks are also the most crucial: changing the culture around hiring to empower managers, and actually letting line managers be managers.

Talent teams could be a good idea that keeps getting launched without the authority or resources to actually work. Every administration for the past decade has called for empowered agency talent teams — small, specialized units charged with driving hiring innovation, adopting new tools like SME-QA, and coordinating participation in pooled actions. M-24-16 explicitly called for agencies to create and sustain these teams, and the current OPM Merit Hiring Plan has stood one up at the central level as well. The concept has potential but execution has been consistently undercut by the same failure mode: no committed resources, no authority to intervene, no access, and no product mindset. In understaffed agency HR offices that were not empowered to “get to yes”, the function hasn’t meshed well, and moreover, it’s arrived in a system that already lacks strong strategic workforce planning, a key enabler of its potential success. 

As FAS and the Niskanen Center documented agency talent teams, OPM communications and education support, and the necessary systems changes all require people, money, and IT investment that hasn’t materialized. Announcing a mandate is not the same as funding its execution.

But underfunding isn’t the only problem. Even well-resourced talent teams have struggled when they lacked the institutional standing to actually change agency behavior. The core failure mode is assuming that having good people in the building is enough — that talent solves problems on its own, without a clear theory of change about authority, access, and how decisions get made. An agency talent team that is advisory in nature, without a direct line to hiring managers and HR decision-makers, without leadership backing when they push back against entrenched process habits, and without metrics that create accountability for adoption, is not going to move the needle on pooled hiring participation. It’s going to produce reports and hold workshops and then watch agencies do what they were already going to do.

Veterans preference created confusion that nobody addressed proactively. Preference applies differently in delegated examining versus merit promotion contexts. When agencies share certificates across those lanes, legal ambiguity creates real hesitation. This is genuinely solvable — but only if OPM issues targeted guidance with each pooled action as a standard part of the launch package. Stepping back, it’s necessary to state that any type of absolute preference is going to make pooled hiring challenging. Clarifying guidance is a Band-Aid.

Small technical barriers compound the problem. One underreported friction point: shared certificate policies can constrain agencies from sharing certs across different geographic locations designated in the original announcement, or across different hire types — temporary versus permanent. An agency running a pooled action for DC-based positions can’t easily extend that cert to field office hires. A cert issued for permanent positions doesn’t smoothly cover term appointments. These are solvable technical problems that OPM and OMB could fix through policy revision but they require someone to actually map the barriers before designing the action.

And when agencies go it alone anyway, the burden multiplies for everyone. This is the part that gets lost in discussions that treat siloed hiring as merely inefficient rather than actively harmful. When agencies that are already understaffed — particularly permitting and HR teams — don’t leverage opportunities to work together, bottlenecks compound. Pooled hiring isn’t just a convenience for well-resourced agencies. For teams that are already stretched, it’s the difference between a manageable workload and an impossible one.

Agency HR leads without the skills or network to work across agencies. Like so much else, pooled hiring depends on relationships. OPM and agencies have not carefully selected the HR managers who not only understand the potential policy barriers to working across agencies but the collaboration skills and networks to solve problems quickly. 

The Assessment Question: Use the Right Tool Not the Easy One

If you’ve read this far, you’ve probably heard of things like SME-QA, the greatest acronym in the hiring world. Let’s talk assessments. 

The default federal hiring assessment — the self-assessment questionnaire — is effectively worthless for identifying technical talent. As Jennifer Pahlka has put it, the system has been built so that the most important knowledge is how the hiring process works instead of the knowledge needed to do the job. A nationally recognized programmer once applied to the Department of Defense and was initially rejected because their resume described real expertise in language that didn’t match OPM’s classification keywords. Meanwhile, someone who understood the system could mark themselves “expert” across every self-assessment category with no verification at all.

The Subject Matter Expert Qualification Assessment, or SME-QA, was one of the skills based hiring toolkits developed to fix this: real experts screen for real skills, with HR ensuring merit principles hold. SMEs independently review every resume. Candidates who clear the initial bar then go through further steps like structured interviews, coding exercises, or written assessments — administered by other practitioners in the field, not generalist HR staff. For technical roles going into a pooled action — data scientists, cybersecurity professionals, engineers — SME-QA paired with a shared certificate is close to the ideal design. Build the assessment once with governmentwide SME input, share the cert, and every agency draws from a pool that was actually screened by people who know the field.

But any skills based hire practice has a scaling problem that’s been documented since the first USDS pilots. The work is resource intensive for federal agencies not used to dedicating so much SME time to a hiring process. As Niskanen’s recent analysis of the Chance to Compete Act makes clear, new written assessments developed by industrial-organizational psychologists are extremely resource-intensive to produce — likely prohibitively expensive at the scale needed to cover broad swaths of the federal workforce. But there are roles and moments where such dedicated investment makes sense. 

The design principle that should govern this: pooled hiring should be an opportunity to concentrate assessment burden at the enterprise level, not multiply it at the agency level. Build the assessment once, or maximize use of SME-QA time, governmentwide, for roles where it genuinely matters. Actually use them consistently rather than rebuilding from scratch at each agency. And as Niskanen argues, transform OPM’s role from compliance monitor to assessment engine: a marketplace of vetted, shared tools agencies can pull from rather than commission independently.

There’s a trust dividend here too. Agencies that contribute subject-matter experts to the assessment design have far more reason to trust the resulting certificate. Skin in the game at the assessment stage translates directly to confidence at the hiring stage.

A Note On Listening

Many successful pooled actions worked because OMB and OPM (or other senior White House offices) gave attention, capacity, authority and accountability to the process, bolstering agencies who were being asked to execute hiring  with unusual flexibility and competence. 

Overall, however, when agencies told OPM and OMB that pooled hiring was hard for them to execute alone, the response from the center was too often some version of: the guidance is out there, the instructions are online, that’s how the process works. Agencies described a cascade of rigidities that made implementation genuinely difficult, and we weren’t always responsive. We treated compliance problems as communication problems. If agencies weren’t doing it right, they must not have understood it correctly, so the answer was more guidance, clearer FAQs, better webinars.

That’s the wrong diagnosis. What they were telling us was that the process didn’t fit their reality and that the gap between what the policy assumed and what their operations actually looked like was wide enough that no amount of additional instruction was going to close it. When the people responsible for carrying out a policy are consistently telling you it’s hard in specific, consistent ways, the right response is to ask what’s broken in the desig.. The people designing these systems need to hear that feedback as signal instead of as resistance to be overcome.

This is the reason why the recommendations in this piece are about structural changes to how pooled hiring is designed, not about better outreach or clearer communications. Agencies don’t need another memo explaining how shared certificates work. They need a system that works in the conditions they’re actually operating in.

How to Actually Do This Right

The current OPM actions are a real opportunity. Here’s what would make them work, stated as plainly as possible.

Lock in real demand before you launch. Not expressions of interest: actual hiring commitments with funded billets and named positions. The failure mode is OPM building a pool that agencies shop from slowly or not at all. Require agencies to submit hiring forecasts before they’re included in a pooled action, and hold them to those forecasts with visible accountability.

Build assessment infrastructure before the announcement goes up. Standardized PDs, validated assessments, and clear SME selection criteria that agencies trust need to exist before the action launches. Thecentralized position description library called for in M-24-16 is the right vehicle. Critically, assessments need to exist at every grade level included in the announcement. 

Build the awareness and the system prompt together. Upgrade communication on pooled hiring announcements directly to hiring managers and HR specialists. But communication alone won’t fix this. The Agency Talent Portal and USA Staffing need to surface available shared certificates at the moment a hiring manager or HR specialist initiates a new action for a covered position series and grade. This should be a required check embedded in the workflow itself — before they proceed with drafting a new announcement. If you’re about to post a GS-12 data scientist announcement and an active government-wide cert exists for that series and grade, the system should tell you right then. The current design assumes awareness that doesn’t exist and motivation that isn’t reliable.

Pool the interviewing, not just the screening. Coordinated interviewing days. Same-day or 48-hour offer authority for hiring managers. Agencies competing for the same candidates simultaneously, not sequentially. Cross-agency onboarding cohorts that start together and build peer networks from day one. This is what actually compresses time-to-hire.

Fund and empower talent teams as implementation infrastructure. Every idea in this piece requires someone inside each major agency whose job it is to make that happen. That’s what a talent team is for. But talent teams need three things that they rarely get: a dedicated budget line, direct access to the hiring managers and HR leadership they’re supposed to influence, and metrics that hold them accountable for adoption rates and actual hiring outcomes rather than process activity. A talent team of one person with a shared budget and no senior sponsor is not an implementation strategy.

Give hiring managers direct access. Update the Agency Talent Portal permissions. Eliminate the intermediary layers between a hiring manager and a cert they’re authorized to use. Hold managers accountable for whether they hire. Culture change here is real but it follows structural change: when managers have direct access and clear authority, behavior shifts.

Make follow-through a metric with teeth. Agencies that opt in and don’t hire should have to explain why, publicly, to the President’s Management Council.The voluntary participation problem doesn’t get solved with please-and-thank-you memos.

Run continuous pooled actions for common roles. HR specialists, contracting officers, environmental specialists, IT managers — these aren’t surge needs, they’re permanent ones. A cert that’s always open, with agencies drawing from it as needs emerge, is far more useful than a prestige program that runs once a year and then goes quiet.

The Bigger Lens

(with thanks to Gabe Menchaca and Peter Bonner for making the stronger argument)

Pooled hiring is a microcosm of a question the federal government seesaws on constantly: what does it mean to govern as an enterprise rather than as several hundred agencies that happen to share a payroll source?

This requires admitting something those of us who have worked in the center don’t always say plainly: agencies and their leaders are protecting their turf for understandable reasons. They are accountable for their missions, their budgets, and their outcomes. When a pooled hiring action asks them to trust a cert they didn’t design, coordinate interviews around a shared calendar, and accept that they won’t get every single thing they want, and that’s a big ask! The trade may be worth making, but it doesn’t happen automatically, and the center has not historically done a good job making the case for why, or building the conditions under which agencies can actually say yes.

That’s a collective action problem, and it’s harder than it looks. It requires genuine leadership alignment across all the agencies involved, and a center that has made the benefit of cooperation concrete and visible rather than just asserting it in guidance. Too often the response to non-participation has been more documentation rather than an honest look at what the actual barrier was. That’s compounded by a structural problem worth naming: agencies are accountable for their HR outcomes but OPM holds much of the compliance authority over how hiring gets done. Accountability without authority produces exactly the behavior you’d expect.

The federal government has demonstrated it can operate differently. The BIL surge, the data scientist certs, USDA’s HR specialists (and maybe Tech Force) worked because the conditions were right: shared design, locked-in demand, leadership alignment, enough urgency to overcome the default toward agency autonomy. The question is whether we can build those conditions deliberately rather than stumbling into them during a crisis. That requires a solid theory of change about how cross-agency infrastructure actually gets adopted: one that takes agency self-interest seriously as a design constraint rather than an obstacle to be overcome by memo. Get that right, and pooled hiring becomes a model for how the federal government decides what to do together and what to do apart. That’s a bigger prize than faster hiring. It’s a more functional government.

Spring is here and so is the debate on the budget. The Fiscal Year 2027 (FY27) President’s Budget Request (PBR) is out and the appropriations process is in full bloom, even if one small but important piece of FY26 lags behind in the form of funding for the Department of Homeland Security (DHS). Meanwhile, states continue to step up and address the most pressing science and technology gaps. 

FY27 Science Funding: “Aww Mom, science cuts for budget again!?” 

As expected, there are more deep cuts for science R&D in the FY27 PBR. 

• Not So Fast: Appropriators on both sides are already signaling skepticism towards sweeping cuts and changes, such as Senator Moran‘s (R-KS) concerns about eliminating the National Institute for Standards and Technology’;s (NIST) Manufacturing Extension Partnership. 
• More $$$ for AI: According to Department of Energy (DOE) Chief of Staff, Carl Coe, his agency “will need a lot more” funding to hit Genesis Mission targets. That says a lot from the guy who used to lead DOE’s Department of Government Efficiency (DOGE) efforts.
• Power of the Purse: FY26 oversight is still important as ever, and the House Science Committee minority released an impressive report detailing how NASA implemented unauthorized (read: illegal) cuts in last year’s budget in accordance with the FY26 PBR. It’s impossible to overemphasize how important it is to keep attention on this. 
  • “In 2025, NASA acted in concrete and formal ways to implement the proposals of the President’s Budget Request for Fiscal Year 2026 (FY26 PBR).”

Trump to NSB: “You’re Fired!” A moment of silence for science governance 

All 22 members of the National Science Board (NSB) have been fired as the National Science Foundation (NSF) and science at-large absorbs the latest blow to its basic operation from this administration. The NSB is mandated by law and appointed by the president. It advises the NSF, Congress, and the president on science. 

• Bc the Constitution?: There is little explanation for the dismissal, other than comments to Inside Higher Ed regarding the constitutionality of the board’s membership without Senate confirmation. Meh. 
• Lots of Change: This comes as we await a new NSF leader – Jim O’Neill – and NSF deals with sweeping changes like the elimination of the Social, Behavioral, and Economic Sciences directorate. 
• Grants Still Slow: This massive loss of leadership only compounds the slow-trickle of science grant approvals and accusations of politicization. So far, this administration has canceled or suspended nearly 1,400 NSF grants. The NSF has only doled out 758 grants compared with 2,327 grants the same time last year. 

Labs of Democracy: States keep pushing on S&T policies 

States have no choice but to deal with the ever-pressing issues associated with the AI explosion and uneven federal support for innovation. We’re continuing to see the “Patchwork-Moratorium” AI policy tension play out at federal and state levels on both data centers and safety. 

• AI legislative action highlights include:
  • Maine’s governor vetoed a bipartisan moratorium on large data centers that would have made them the first state to do so. 
  • Florida is seriously considering an “AI bill of rights,” with the Governor and allies pressuring the legislature to act on tech accountability and child safety. 
• States are investing in entrepreneurship
  • Indiana is investing $15M to attract international tech startups through a venture initiative tied to Israel.
  • West Virginia is launching a new Office of Entrepreneurship to support startups and small businesses navigate state agencies and processes

Looking to May 

May brings more appropriations process fun as the committees scrutinize the president’s FY27 budget request and compose their own funding bills (which we can expect will again rebuke the massive proposed cuts to science). 

This contentious summer period will reach a boiling point as we arrive closer to the midterms, making meaningful legislating even more complicated. Congress is racing to get laws passed on pressing matters like AI and housing as well as standing business like FY27 funding. 

No one will be surprised if we end up with a continuing resolution to push our shutdown deadline out past the midterms, so the real question is what else will they get done this summer? We know this Administration will be staying busy. 

There are lots we didn’t cover, so we’ll just have to talk again soon! 

It’s a fascinating time to be thinking about carbon markets. In one corner, California just reauthorized its carbon market program, the EU’s Emissions Trading System continues to evolve as the world’s largest compliance market, and a growing number of countries — from Brazil and Indonesia to Singapore and Kenya — are standing up or expanding their own systems, with the architecture for international carbon trading under Article 6 of the Paris Agreement beginning to take shape. In the other, markets are facing headwinds. Pennsylvania just dropped out of a regional carbon market, and while about a quarter of global emissions are now covered by trading systems, steep emissions cuts haven’t followed. 

More broadly, profound legal and political changes in the larger economy and in global climate policy are pushing forward a wide-ranging conversation on next steps in climate policy. In this transitional moment, carbon markets clearly have a role to play in economic and industrial policy, but that role, and the policy environment in which markets function, merits examination.What would it take for carbon markets to actually deliver at the scale and pace the climate problem demands? 

The standard story on the role of pollution markets goes like this: emissions trading worked brilliantly for acid rain in the 1990s, so let’s do it for carbon. Effectively pricing and trading carbon emissions is key to driving a clean-technology transition.

But that story glosses over something important. The acid rain program was operating in specific conditions, with a small universe of highly regulated power plants, shared grids, clear cost information, and a relatively straightforward, easy-to-deploy fix (smokestack scrubbers) for the problematic emissions in question. Carbon emissions trading is orders of magnitude harder – it spans every sector of the economy, involves far more actors, and requires infrastructural changes that don’t come cheap.

That doesn’t mean carbon markets are futile. It means they need to be fit for purpose and embedded in a broader policy strategy. We call this regulatory ingenuity: fitting tools to tasks, rather than hoping one tool does everything.

Three Tools, Three Roles

Climate policy has historically relied on three approaches, each with real strengths and real limits.

• Regulatory mandates have been effective at cutting smog and cleaning up fuels. But motivating a wholesale shift in energy sources – where the required infrastructure investment runs into trillions and the economic and societal implications are complex and multifaceted – has proven far harder to accomplish through existing regulatory tools, and far harder to sustain politically.
  
• Fiscal and industrial policy, exemplified by the Inflation Reduction Act, has helped drive down clean energy costs, build domestic supply chains, and deploy major industrial and regional strategies that regulation alone couldn’t deliver. Though IRA implementation faced deployment challenges, and a partial partisan repeal under Trump limited its reach, its core policy design moved markets. The replacement bill retains many of the IRA’s programs.
  
• Carbon markets have generated billions in revenues for reinvestment and, in principle, long-term emissions accountability. In practice, both governmental and voluntary markets have struggled to track and deliver emissions reductions reliably across the economy.

These tools work best together. Markets in particular have seen the most success as part of a “portfolio” of programs – including regulation and fiscal policy – where the carbon market functions as a backstop, setting direction and generating funds but not carrying the full weight of an economy-wide transition.

Zooming In On Markets

Positioning markets for continued success requires being clear-eyed about what they can and can’t do. Several structural limits are worth naming.

First, markets optimize for cost per ton, a powerful but incomplete signal. Capital flows to the cheapest reductions first, and that is how markets should work. But cheap reductions are not necessarily the ones critical to fully developed industrial strategies. For example, the marginal cost of generation is not the full cost of reliable, delivered, politically durable clean power. Integration, transmission, siting, and community acceptance all carry real costs that today’s price signals don’t reflect. Until those full system costs are reflected and competitive, markets alone will not scale clean energy at the pace or scale needed. This disjunct between cheap reductions and strategic reductions recurs across the economy. Bridging that gap requires R&D and early deployment to drive costs of needed solutions down to the point where markets take over. 

Second, carbon prices can’t drive decarbonization without affordable alternatives. A carbon price passed along to gas-pump drivers doesn’t transform transportation unless there is something cheaper to switch to. Where affordable alternatives exist, as in markets with cheap electricity and accessible EVs, adoption follows.  Where they don’t, carbon pricing cannot close the gap, and the political backlash against visible consumer costs has been swift.

Finally, market revenues may not cover the real costs of transition. Refinery closures, shifting energy economies, and job losses in fossil-dependent regions have major consequences for workers and communities, as California is now grappling with. Carbon revenues alone won’t fill that gap.

Beyond these structural realities, there’s a second, more fixable problem: carbon markets haven’t yet been built to function like mature markets.

The first problem is an infrastructure problem. Today’s carbon markets lack the infrastructure, breadth, and sophistication of mature financial markets. Registries are fragmented, data fields are inconsistent, chain-of-title is unclear, and there is no unified ledger capable of ensuring finality of settlement. A functional carbon market requires the same institutional foundations that other markets rely upon: transparent interoperable ledgers, consistent data schemas, reliable transfer and custody, and audit trails that regulators and institutions can trust. Only with this plumbing does a market become truly “investable.” Without it, liquidity cannot form and institutional capital remains on the sidelines.

The second problem is a comparability problem. In markets where a “ton” of carbon credit does not represent a consistent underlying asset, credits can vary dramatically in durability, additionality, leakage, and earth-system risk. These differences are economically meaningful because they characterize the credit, duration, and performance risks of this asset class, and current markets do not sufficiently account for them.

Financial markets long ago learned how to handle heterogeneous assets. Commodities are graded, mortgages are underwritten, bonds are rated, structured products are tranched in a standardized form that, when paired with transparency, enables informed decision-making. Carbon markets similarly need a standardized, quantitatively grounded way to express expected atmospheric impact. Infrastructure and comparability are mutually dependent. Without infrastructure, standardized units can’t be recorded, verified, or enforced. Without comparability, infrastructure has nothing meaningful to track.

These problems are solvable; indeed, efforts are underway to solve both the infrastructure and comparability gaps. But even a technically mature carbon market will still bump against the structural limits above. The market needs to be embedded in a broader strategy.

What Well-Designed Markets Can Do 

There is broad agreement that big industrial emitters — power plants, large manufacturers, heavy industry — are natural candidates for direct market participation, and especially so in the context of well-developed economic strategies that can attend to a range of transition equities. In compliance markets, where regulation creates scarcity, well-designed trading systems can accelerate their decarbonization while generating substantial revenues that can be directed toward harder-to-reach parts of the economy.

The harder question is what role markets should play beyond these large point sources — particularly in voluntary and offset markets, where demand is discretionary, the underlying units are heterogeneous, and market infrastructure is less mature.

One view is that most other sectors are poor fits for direct market participation and that the primary value of carbon markets lies in generating revenues and behavioral shifts from the parts of the economy that respond well to price signals, and directing those resources toward the parts that don’t. Natural and working lands, for instance, urgently need funding to manage climate risk —wildfires are erasing climate gains in California, and carbon sinks are deteriorating under pressure from fire, drought, and deforestation. Diffuse emitters — small freight operators, aging refrigeration systems, millions of buildings that need electrification — lack the capital or capacity to participate in complex trading systems. In this framing, carbon markets function less as direct decarbonization tools and more as engines of transition finance: pricing what can be priced, and channeling the proceeds toward what cannot. 

Adherents to this view would also emphasize that there are broad categories of public transition cost, like addressing major regional shifts in public budgets and private incomes as entire industries transition, that at minimum require additional funds and policy to manage. California’s closing refineries (and the attendant political debate over the fundamental structure of its fuels system and the fiscal stability of affected counties) are an example of revenue and policy challenges that a market alone cannot close.

A different view holds that the problem isn’t that many sectors are inherently unsuited to markets, or that markets can’t contribute to larger public finance challenges, but that the markets themselves are unfinished. Today’s markets lack sufficient demand signals that arise when governments impose some form of compliance obligation, whether through a tax, procurement standards, or other policy mechanisms. Carbon credits from forestry projects, land management, methane abatement, and engineered removal all represent real atmospheric interventions — but the current market has no rigorous way to compare what they actually deliver. Without standardized infrastructure and a common unit of impact, a forestry credit and an engineered removal trade as if they are equivalent when they are not, or one is excluded entirely when it could be valued proportionally.

In this framing, the fix is not to route around the market but to build the market properly — with the comparability tools and settlement infrastructure that would let heterogeneous credits be priced accurately and traded with confidence. A market built this way could reach diffuse actors through intermediation, aggregation, and structured products, much as mortgage markets reach individual homeowners without requiring each one to trade directly. A framework for carbon markets, which proposes standardized assessment of atmospheric impact per dollar, offers a concrete path toward this kind of market maturation. It could also more efficiently channel funds to public needs by helping direct scarce capital to whatever delivers the most verified atmospheric benefit per dollar.

Though we (the authors) differ about which view we believe to be most true, we also realize that these two views are not necessarily in conflict. Revenue transfer and market maturation can work in parallel. A strategy oriented around revenue transfer focuses on regulation, fiscal policy, and public investment to do the heavy lifting, with markets in a supporting role. A strategy oriented around market maturation invests in the infrastructure and standards that would allow markets to bear more of the weight directly. The right path almost certainly involves both, and getting the sequencing and emphasis right could be one of the most consequential design choices in climate policy today.

Where Do We Go From Here?

The above analysis lets us take a more sophisticated look back at the acid rain program. The lesson this program teaches isn’t “markets work, full stop.” It’s that markets can accelerate a transition whose economics are favorable, such as the transition to widespread use of smokestack scrubbers: straightforward, cost-effective technology. But markets cannot create that favorability, nor are they always designed to anticipate and manage second-order effects.

A second lesson is that well-designed tools, matched to the right problem and the right timescale, can deliver real results. That applies to carbon markets themselves — which today have design flaws that can be corrected — and to the broader policy architecture in which they sit. A powerful path emerges when well-designed markets are embedded in a broader strategy: enforceable regulatory limits that create real scarcity and price signals; industrial policy that is not only well-designed but well-executed; and a clear theory of how the costs and benefits of transition are distributed.

But it also applies within the market. If carbon markets are going to play a meaningful role — whether as engines of transition finance, as instruments of accurate pricing across heterogeneous climate interventions, or both — they need the infrastructure and standards that any serious market requires. That work is underway, and it deserves at least as much attention as the policy debates that surround it.

So what’s going on with carbon markets? We’ve asked one incomplete tool to do the work of three. And we’ve debated what role markets should play without finishing the market itself. It’s time to do both: modernize market structure, and stop asking markets to work alone.

Over the past month, we’ve been running digital service retrospectives with more than 100 people from across the United States to help us design more effective services that lead to better outcomes for people across the country. You can read more about our project here. 

We know that the biggest, boldest ideas can come from anywhere and we have deliberately taken a community-driven approach to our retrospective work. Our sessions are open to anyone who’s worked in government digital services — alums and current staff of USDS, 18F, TTS, and state and local teams who have spent years inside government trying to make things work — and we’ve given everyone a chance to contribute. The result is a lot to unpack: a huge amount of insight, frustration, pride, and hard-won experiences people shared with us. What struck us most was the tension: sometimes uncomfortable disagreement among people who had dedicated years to the same mission. That tension, it turns out, is exactly what this exercise is designed to surface.

When I landed at the US Digital Service, I immediately was inundated with stories, myths, mysteries, hero/villain narratives, and beliefs about what USDS does, how it does it, and why it works that way. Sometimes, the opinions were so strong that they came off like fact. And when I joined another agency, “the way things work” was approached as a set of truths written into legislation, rather than a series of decisions that accrued over time. Organizations built on destiny can be nearly impossible to improve — you can’t iterate on a legend, and you can’t refactor a belief.

Don’t get me wrong, much of the government — and likely most mission-driven organizations — behave like this. And even for those of us who were lucky enough to start new teams or even agencies in our lifetimes have played a part in institutional myth-making as well. 

But where it gets limiting is when beliefs become fact, habits become silos, storytelling becomes rules, and we lose our ability to be a learning organization — and with it, the ability to evolve, challenge, and push forward.

So, we decided now was a good time to challenge the system of beliefs that make up government digital capacity, as well as policies and approaches that felt un-challengeable. Let’s see what rules we can rewrite and beliefs we can reset: a few sacred cows are long overdue to be put out to pasture

What we’re calling ‘sacred cows’

A sacred cow is a long-standing belief, structure, or practice that people hesitate to question — even when it may no longer be serving the mission. Surfacing these isn’t about blame. Most of these beliefs made sense at some point. Some of them were correct at the time.

The problem isn’t that these beliefs existed – it’s that they likely have become perceived facts and traveled. New people joined USDS or 18F or a state digital team and absorbed the orthodoxy without questioning it. It got baked into how teams were structured, how trust was defined, what counted as success. A field that was supposed to be about iteration stopped iterating on itself. 

And now, we want to create permission to examine them with fresh eyes, so we can design something better.

We asked every group in our retros a version of the same question: What is something in digital service that feels unquestionable — but might benefit from fresh examination?

Here are some of our favorites: 

“Delivery and Tech are a specialty team’s job”

We have spent fifteen years sending in outside digital teams to fix what agency leadership (including many IT leadership) didn’t understand well enough to build right in the first place. At some point the question becomes: what if we just built the competency in the system instead of relying on a “save the day” model? In 2026, all organizations are software organizations. Every Senior Executive Service-level leader making decisions about policy, procurement, service delivery, enforcement, and hiring is making technology decisions. These fields must become agile, responsive to users, multidisciplinary, and strategic—and conscious of the digital environment they operate in and create. 

A common pattern is deferring delivery and technology matters to specialists and we look forward to seeing how this space changes and matures. We know we are not alone wanting to see civil service and personnel reforms and are excited to learn about future reforms recommended by colleagues like The Tech Talent Project and TechViaduct. We should expect more ambition and better delivery consciousness from our agency leaders in all roles. An operating model that relies on external fixes rather than internal competence will always be behind. 

“Policy designed without users or implementation in mind can still be good policy” 

This myth came up in every session, multiple times.  No one wants to accept this shortcutting anymore.

Policy development and implementation should never be far from the citizens it would impact — its end-users — and the implementers who deliver those results. And yet too often, policy gets designed by academics, economists, and MPAs in isolation from the people who will have to build the system that makes it possible and the people who will have to live with its gaps or failures. Implementation and impact become an afterthought. 

In many cases, this wasn’t accidental. The way digital services were scoped and deployed reinforced the myth — technologists arrived after the policy was written, the budget was allocated, and the flexibility was gone. By the time they were in the room, the important decisions had already been made without them. 

One example of where tech and policy worked well together was Direct File — from the earliest days, USDS played an integral role in the policy development phase, including building early prototypes and user journeys throughout the formal policy process. Not only did the Direct File team carry that work forward into the product itself, but the multidisciplinary, cross agency relationships built during those early days supported the product through to its launch. 

Today, the technology that the government connects to Americans, the data that tracks results, and the design that saves time and stress are not optional components of policy – they’re how policy actually reaches people. Policy that skips this loop doesn’t just launch slowly — it launches wrong. Moving forward, 100% of policy needs to be designed with technologists, designers, and data scientists at the table, as the necessary translators to end users. 

“We can’t affect urgent change without damaging trust” 

Building trust between digital teams and agency partners came up in almost every session and almost everyone agreed it mattered. Where it got interesting was the question of who we build it with, why, and can it hold us back or slow us down when time is short? 

It was widely acknowledged that building trust is critical to the success of launching scaled, utilized, and beloved digital services. We also we had some really interesting discussions/debates around building trust inside of agencies. Trust was important — but alignment broke down on whether trust with agency partners is a core foundation, necessary as a form of permission, or a relationship built in practice through successful partnership. Trust can be invoked to justify waiting — or to avoid taking a position altogether. But it can also be the reason work doesn’t survive once the team leaves. 

Trust gained through the work is different from trust gained in order to do the work. Moving forward, we need to acknowledge this and ensure that the relationships we build will still carry forward through – and beyond – delivery.

Compliance is a proxy for quality control 

The Paperwork Reduction Act (a law meant to streamline how much data the government collects from the public) gets invoked constantly to stop user research before it starts. And the Authority to Operate process (the federal security review required before launching a system) is often a costly, never ending paperwork exercise that more often than not confuses compliance with security. Both exist for legitimate purposes, and both can be executed in ways that actually serve those purposes. 

But when they’re invoked as the default answer to slow or stop work, the cost is real: user research doesn’t happen, services launch without being tested against the people who need them, and security theater replaces actual security. 

Attempting to minimize burden on people and launching secure services are both good practices and, moving forward, we should look for transparent oversight that achieves this, while also ensuring the pace of delivery is not held back.  We’re keen to see future recommendations from partners in the state capacity ecosystem on PRA reform and TechViaduct on oversight recommendations. When compliance becomes the goal instead of the means, the people the law was designed to protect are the ones who pay for it.

We can’t have good tools

I kind of hate myself for even writing this because it is so obvious and frustrating. But, here I am, repeating what everyone said during our sessions because we are still saying it. 

Digital government professionals can use modern software to build, design, and launch great experiences… but with endless friction that makes it not worth asking. This plays out constantly: teams lack of access to modern resources and tools that allow them to work, like design software, coding environments, or even mission support tools, like Slack. The result is teams spending time on workarounds instead of the work, and talented people leaving for environments where the tools aren’t a fight to obtain.

Somehow, “we don’t have access to the tools we need” became an accepted condition of the work. It is time to reassess that. Procurement and approval processes should happen centrally to ensure that they are safe, secure, and ready to deploy in all agencies without significant delay.

The perfect team size exists!

Teams should be big! 

Teams should be small! 

This was another topic that came up in every session and there is no consensus on the right answer. The lack of consensus is actually the point — team size isn’t a principle, it’s a variable. Team size should be based on the problem you’re trying to solve or the outcome you want to achieve. Agency digital transformation cannot be realized with a USDS team of 2-4 people; that’s a gesture. Direct File had a product team of 75 (blended in house and vendor, but majority government employees) — that wasn’t bloat, it was what the problem required. But myths about team size calcify fast. Once ‘small and agile’ or ‘go big’ becomes part of an organization’s legend, rightsizing stops being a decision and starts being a heresy

Instead of assuming there’s a right size, identify the problem and build the appropriate team to solve it. Too often, building the team became the goal rather than the means — optimizing for org chart over outcomes. The team is not the product, the service is.

Try this at home

The Sacred Cows exercise is an effective tool for debate and to challenge our own assumptions as digital government professionals. This list could have been a lot longer, and if we want to rewrite the rules for better government, the more experiences we hear the better.

Do these resonate? What have we missed? Here were our prompts, but feel free to expand: 

What is something in digital service that feels unquestionable — but might benefit from fresh examination?

• Operating models
• Talent assumptions
• Procurement habits
• Funding structures
• Risk tolerance
• Measures of success