Prologue: Learning Space Policy
A series about trying to think clearly when the ground keeps moving
Space policy is having a moment. That is not automatically a good thing.
When a domain becomes strategically salient, the surrounding commentary tends to polarize into two familiar genres. One is advocacy dressed up as analysis. The other is technical enthusiasm that treats policy as a footnote to physics. Both can be sincere. Both can still be wrong in ways that matter.
This series is my attempt to do something else: practice disciplined policy analysis under uncertainty and constraint.
It is also, candidly, a learning project. I do not pretend to have the answers. If I did, I would not be writing a series. I would be writing a memo with a lot more footnotes and a lot fewer adjectives.
Why I am publishing this series
The practical reason is that space policy decisions are getting bigger, faster, and more consequential across civil exploration, commercial regulation, national security, and sustainability. Think Artemis timelines that keep shifting, debris mitigation rules that still lack enforcement teeth, commercial launch licensing that cannot keep pace with the manifest, proposals for space-based data centers and cislunar reactors that don’t yet have a regulatory home, and a growing gap between space security strategy and the institutions that have to execute it. And yet a lot of the debate remains analytically slippery. People talk past each other, hide value judgments inside confident language, and treat institutional realities as background noise.
The personal reason is that I have been teaching space policy for the last two years at the RAND School of Public Policy, and teaching has a way of humbling you on a weekly schedule.
The first time I taught the class, in the very first session, a student asked me a simple question: why are you teaching this class? I remember answering with something I heard years ago from Peter Senge, an MIT professor I took a class with: the best way to learn is to teach.
That line stuck with me because it is true in the most inconvenient way. Teaching forces you to show your work. You cannot hide behind jargon. You cannot outrun the hard questions with vibes. If you say “it depends,” a good student will politely ask, “on what, exactly?” and then wait.
So I am doing the same thing here. I am writing in public because it is the only way I know to keep learning honestly. I will get things wrong. If you see a flaw, tell me. If you have a better frame, teach me. If you think I am missing a crucial constraint, I would genuinely like to know.
Where this series comes from
The material draws from lecture notes, slides, and arguments I have had to refine repeatedly in the classroom at the RAND School of Public Policy - two years in a row! I am grateful to RAND for the opportunity to teach. It gave me the space, colleagues, and students who pushed my thinking harder than any conference panel ever could. Also, unlike conference panels, my students are not afraid to tell me when something does not make sense.
Teaching makes one thing obvious: many space policy problems are not hard because the physics is hard. They are hard because the decision environment is hard. Incentives are misaligned. Authority is fragmented. Uncertainty is real. Timelines are politically imposed. Costs are visible while benefits are diffuse. And every serious decision touches multiple equities at once.
My good friend Brian Weeden often describes space policy problems as “wicked.” He is right. “Wicked” problems are a concept from planning theory: problems with competing objectives, no clean endpoint, and solutions that generate second-order effects you do not get to ignore. The next post will unpack what that means.
What this series is and is not
This series is not advocacy. I am not trying to rally you to a program, an institution, or a slogan.
It is not forecasting. I am not predicting what China will do, what Congress will pass, or what the next market will look like. When uncertainty dominates, pretending to forecast is often a way to avoid stating assumptions and making trade-offs. It is not a set of teaching notes. The posts draw from teaching, but they are written for practitioners, analysts, and anyone early in their career who wants to understand how the decisions that shape space actually get made.
What it is: an effort to model how a policy analyst thinks when the ground is moving and the incentives are not cooperating.
How I will approach each post
Each post will take a real policy question and treat it as a decision problem. That usually means five moves:
Define the decision. Many debates fail because people are not arguing about the same choice.
Make options legible. If you cannot name the alternatives cleanly, you cannot compare them.
Surface trade-offs explicitly. Space policy is full of talk that assumes we can maximize everything at once. We cannot.
Treat uncertainty honestly. What is known. What is not known. What would change the conclusion.
Make institutions visible. Authority, incentives, budgets, and regulatory structure shape outcomes as much as technology does. This is probably the most underappreciated move on the list, and one I will return to repeatedly.
If you are allergic to frameworks, fair. But in policy, frameworks are often what keep you from accidentally optimizing the wrong thing.
The five-equities lens
Across the series, I will use a consistent lens to avoid smuggling values into analysis without naming them. Think of it as a checklist for what any serious space decision is trading off.
The five equities are:
Innovation – the rate at which new capabilities, actors, and business models can emerge
Cost – what programs and regulations actually demand in dollars and political capital
Safety – protecting human life, crew and public, on the ground and in orbit
National security – maintaining strategic advantage and deterrence
Sustainability – preserving the long-term usability of the space environment
Notice that these can pull in opposite directions. Stricter safety requirements can raise costs and slow innovation. Prioritizing national security can conflict with sustainability norms. That tension is the whole point of the lens: it forces you to say which equity you are privileging and what you are giving up.
You can disagree with this set. The point is not perfection. The point is explicitness.
The framework underneath the series
One post in the series will lay out the analytic framework explicitly. The short version is sequential. Step one is decision modeling: define objectives, define options, compare performance, and surface trade-offs. Step two is stakeholder power analysis: identify who has authority, who can block, what incentives dominate, and what implementation paths are plausible.
The sequence matters. Start with politics and you often rationalize the status quo. Start with technocracy and stop there and you recommend the “best” option that cannot happen.
How to read this series
Read these posts the way you would read an analytic memo, not a manifesto.
Ask:
Did it define the decision and the options clearly?
Did it make trade-offs explicit rather than hidden?
Did it state uncertainties plainly, including what would change the conclusion?
Did it treat institutions as causal rather than decorative?
If you find yourself agreeing with a post because it flatters your priors, slow down. The goal here is not to win an argument. It is to think cleanly.
What comes next
The next post argues for a basic reset: space policy is harder than it looks, not because rockets are complicated, but because the problems are wicked in the precise sense Brian means it! Competing equities, uncertain facts, contested objectives, fragmented authority, and real constraints.
If there is a single promise of this series, it is this: no slogans, no pretending away trade-offs, and no performance of certainty. Just careful thinking, in public, about the decisions that actually shape outcomes.