A playbook for field strategy
This is how you can produce a good strategy for solving important global problems, fast.
At BlueDot, we’ve used this playbook to design draft strategies for specific biosecurity interventions, including UV air disinfection, DNA synthesis screening, and pandemic early warning systems. These strategies inform where we direct top talent and which new projects we help launch.
The need for field-level strategies
A field is a community of individuals and organisations working to address a shared problem. In our case, the fields we operate in are trying to mitigate risks from AI and synthetic biology.
These fields are under-resourced and confused. Without a strategy for what we’re trying to achieve and how we’re going to achieve it, we risk producing elegant answers to pointless questions, focusing our scarce resources on unimportant problems, and failing to protect humanity from harm.
It’s nobody’s job to produce field-level strategy — most actors in the community focus on their own organization or their own role.
Many “strategies” that people do produce are shallow, one-off wishlists that don’t get distributed to relevant stakeholders. They set goals before deeply understanding the problem and analysing what matters most for whether or not we’ll succeed. Strategy isn’t a goal, it’s a form of problem-solving, and you can’t solve a problem you don’t understand and haven’t defined.
Field strategy is still challenging to do well. Defining the “problem-to-be-solved” is contentious and a moving target. Information is privately held or not written down. Experts disagree because they have different values and world-models. You might just aggregate people’s opinions and produce a vague mush. Few people have done this well before. You’ve not been appointed to do this, so you need to earn legitimacy and trust by doing the hard work well.
Here’s how you can overcome these challenges.
How to produce a field strategy
These steps should be done in parallel.
Read and take notes
You’re not the first person to think about this problem. Start by reading the field’s seminal literature, and important pieces from adjacent fields. You can use AI to search for the best papers and blog posts, and they’re also great thought partners to ask you questions, give you feedback, and prod your mental models for how things work.
Take lots of scrappy notes. Don’t write prose; stick to one-sentence bullet points. Synthesise what you’re learning into the most critical insights, and group your notes into sensible-seeming categories to help you build a stronger mental model of the field. Keep track of your confusions and uncertainties, as these can steer further research and interview questions.
Ask and listen
You’re unlikely to find the most important insights on the public web. They live inside people’s heads or in private google docs. To acquire this information, you need to talk to lots of the right people. Connect with them via cold emails or via warm introductions. As a heuristic, try to have 50 calls in your first 50 days of working full-time on this.
The usefulness of conversations tends to follow a power-law: most conversations will be fine, a few will be extraordinary, some you won’t realize were useful until weeks later. So you need to constantly search for the most insightful people.
To gather the most juicy insights during your calls, you need to build a connection quickly. At the start of every conversation, share your backstory, ask them for theirs, and find common ground. Demonstrate you’re competent, be vulnerable, and mirror their energy.
Avoid biasing them with your ideas early on. Ask open questions that give them a lot of space to explore and share things you don’t expect. For example, “If we’ve solved X problem in 10 years, what’s the most important thing that needs to happen next year?”. Read The Mom Test for question-asking advice.
After you’ve asked a broad open question, listen intently and ask a follow-up question that zooms in on a specific thing they said that seems important. You know it’s a good question if their eyes light up or if they have to think super hard and then say something really valuable.
You should also come prepared with sharp, open questions that enable them to build on what you already know. For example, “In X paper, I noticed Y, but this conflicts with my intuition Z. What’s your intuition about Z, and what drives that?”.
If you’re confused, express that confusion and give them the opportunity to help you. If you hear them say something that doesn’t make sense to you or doesn’t align with your model for how things work, chase it. Ask follow-up questions. This is how you discover unknown unknowns.
Move fast through the network
Every call is an opportunity to bounce into the next conversation. In the final 5 minutes, prioritize generating names for potential introductions. If you’ve asked great questions, demonstrated that you’re determined to solve this problem, and they’ve had fun, they’ll feel excited to introduce you to people they admire.
To help them generate names, prompt them with:
Who’s done the best writing on this problem?
Whose work are you most impressed with?
Who do you turn to for help when you’re stuck?
Who would I learn the most from?
Explicitly ask for introductions before the call ends. Then you need to make it as easy as possible for them to make those introductions. Immediately after the call ends, send them a complete draft email they can use to make the introductions. This should include a subject, a bio of yourself and a description of this project. Aim for <100 words.
Once you’ve been introduced, you need to move fast. If you send them a scheduling link, it might take them 1-2 weeks to click on it, and they might schedule a meeting for 1-2 weeks after that. But you need to move as deep into the “intros chain” as quickly as possible.
Immediately after you’ve been introduced to someone, send them a calendar invite for the next day at a reasonable time for their timezone. Use this format for the calendar event title: “[TBC] YourName<>TheirName”. Reply to the introduction asking if that time works, and if not, when works best for them. This tactic runs a higher risk of annoying people and shouldn’t be used with everyone, but I think it’s worth the speed benefits most of the time. Use it thoughtfully.
Write and rewrite
After your first few calls, start writing your v1 scrappy strategy doc. In separate sections, answer these questions:
What is the precise problem/threat you’re trying to solve?
If this field succeeds in 5-10 years, what’s different about the world?
Where are things at today? Who’s working on this, what’s been tried, what’s the funding and policy landscape?
What’s the biggest obstacle between here and success?
What approach could overcome this obstacle, and why would it work?
What needs to happen in the next 6-12 months?
Here are some work-in-progress examples: UV air disinfection, DNA synthesis screening, pandemic early warning systems.
This structure is adapted from Richard Rumelt’s “Good Strategy, Bad Strategy,” which is well worth the read. The most common failure mode when doing strategy is jumping from “what success looks like” to “what should we do”, without diagnosing why we’re not already succeeding.
Remember that your first call with an expert is only the beginning of your relationship with them. Give them commenting access on your google doc, thank them for their input, and ask for their feedback. You know this is working when people spend a lot of time in your doc, when experts debate each other in the comments and generate new insights, and when people ask you if they can share the doc with their peers.
This isn’t a one-off, linear process. It’s messy, and you’ll jump around a lot. You’ll discover big new questions and conflicting evidence that undermine your confidence and makes you feel confused. You’ll get lost down rabbit holes. And you should be prepared to rewrite everything from scratch a few times.
But after a few weeks or months, you’ll have a clear sense for where this field needs to be, a sharp diagnosis for the biggest obstacle blocking progress, a plan of action for overcoming that obstacle, and widespread buy-in from the most powerful and influential stakeholders in the field.
Taking action
This process doesn’t just produce a document. It gives you strong relationships with influential players throughout the field. It gives you situational awareness about what everyone’s doing and why, and what’s blocking them. It makes you a person people turn to when they want to know what’s happening, what matters most, and what to do next.
Then the next phase begins: obsessively communicating the strategy, overseeing implementation, removing obstacles to progress, and updating and refining the strategy as the field evolves and we learn from reality. More details on this in a future blog post.
If you’re working on an important global problem and you don’t know what to do (and seemingly neither does anyone else), this is how you can make yourself useful to a field that needs direction.
Further reading
These blog posts will help you understand what we mean by strategy. I believe it’s worth spending 5+ hours engaging with these.
Thanks! I started a more technical journey on AI after working in developing countries for many years. Just exploring AI deeper after I took BlueDot’s AGI course. Will use the advice to figure out the project , as well as my background.