I have just completed the AGI Strategy course by BlueDot Impact, and I wanted to share a few reflections, especially from the standpoint of someone working on science and innovation in Nigeria. The course is essentially an entry point into one of the most important questions of our time: how do we shape the trajectory of advanced AI systems so that things actually go well? In about ~25 hours, it moves quite deliberately from understanding the landscape to thinking about what one can do, not just what one can say (BlueDot Impact).
1. Strategy, not abstraction: What I appreciated most is that the course treats AGI not just as a technical issue, but as a strategic one. Incentives, coordination failures, institutional capacity, these are the real drivers. It forces you to think less about models in isolation and more about decision-making systems around them.
2. From risk to intervention: There is a strong push toward actually building something. You’re not allowed to just sit with the ideas; you have to translate them into a project, whether research, policy, or an organization (LinkedIn). That shift from thinking to doing is important.
3. The narrowing window: There’s an underlying sense, never overstated, but quite clear, that the window to shape outcomes may not remain open for long. That naturally pushes you toward more focused, high-leverage work.
4. A structural blind spot: the Global South
Many AGI strategy discussions assume strong institutions, reliable infrastructure, and coordinated governance systems. That assumption simply doesn’t hold in many parts of the world.
From where I sit, this raises some practical questions:
As part of the course deliverable, I worked on a project trying to engage directly with this gap:
https://docs.google.com/document/d/1N1eI0STfS-Yfm66h64LqM-EmJMCCMuaGDIc6CsKaK3c/edit?tab=t.0#heading=h.hsyis9sy4428
The core idea is to build sentinel detection systems in surveillance-blind regions, drawing on:
The motivation is quite straightforward. In many places, there is no wastewater infrastructure, no centralized monitoring—so entire regions become invisible to early warning systems. That’s already a problem in biosecurity. It may become a bigger problem in other domains. I wonder if anyone might be interested in collaborating on this, or will likely fund a pilot.
I find myself increasingly drawn to work at the intersection of the following:
More broadly, I think distributed sentinel systems could become a useful general model for risk detection, not just in biology, but potentially beyond.
If AGI is ultimately a global coordination problem, then leaving large parts of the world out of the picture may not just be an equity issue; it may be a strategic one. I’d be interested to hear from others thinking along these lines, particularly those working outside the usual US/EU policy and lab ecosystems. If helpful, I’m also open to feedback on the project itself or conversations around collaboration.
Thank you for writing this. It's the only first-person account of the AGI Strategy course I've found.
Your point about the structural blind spot resonated with me. I work as an AI data annotator specializing in Korean, mostly on safety and red-teaming tasks, and I see a similar pattern in evaluations: they assume the criteria work across languages and cultures, but that breaks even in a high-resource language like Korean.
To your open question, I think it becomes strategic whether anyone intends it or not. Frontier labs are concentrated in a few countries, AI is increasingly treated as a national strategic technology, and access can be shaped through export and access controls. Evaluation is where I see this concretely. Most countries will deploy models built elsewhere, tested against criteria written elsewhere, without the means to check whether those criteria hold in their own context. So yes, I'd agree it's strategic.
A couple of small side questions, if you are willing to share: I'm working through the course's public curriculum first. When you applied, did you already have something like the sentinel detection project in mind, or did it take shape during the course? What would someone miss by working through the curriculum alone rather than in a cohort?
Thank you for engaging with this post. It is interesting to see from your experience too that AI strategies seem to leave a blind spot in several countries and cultures. We don’t know how bad actors might exploit this in future.
As to your question, when I started the course, I had a vague idea that Metagenomics was a way to go in pandemic preparedness( this may be influenced by my background, I am a microbiologist). However, the course helped me to narrow down to the idea of sampling in rural communities like Nigeria and sequencing in a mobile lab. I believe this is feasible. With nanopore technology and a solar system. One can move from region to region and perform random sampling- I must confess that none within the field of biosecurity have found this idea interesting. So it is basically in my head.
With regard to engaging with the course alone. One thing the course does is to bring you into a community- Although am still exploring how useful the community is. The exchange of ideas and experiences can help broaden your scope beyond what you already know.
Unless you are like me that feels the community is biased towards some kind of people and location. I think you will enjoy the course joining a cohort
Thank you for the detailed reply! I'm outside biosecurity, so unfortunately I'm unable to give you feedback on the mobile sampling idea on its merits, but I know what it's like to have an idea that is still only in your own head. I think the hard part isn't the idea, it's finding the right people to discuss it with, develop it together, and tell you whether the direction makes sense. I hope you find them.
Your point about the community is a useful data point. I'll keep it in mind when I decide between the public curriculum and a cohort. I hope to see your updates on how the pilot develops!