Hot take: I think it's still important to understand the code that our agents write! In this mega thread (based on my AIE talk today), I will explain why that's the case, and show some ideas for how to efficiently understand code. Alright, let's dive in. 1/

Blogged about it here: simonwillison.net/2026/Jul/2…

before @geoffreylitt 's talk I was 90% given up on sloppy work around me, now i am more hopeful. the future will be very polarized: those who understand will keep having the next big idea. those who delegate understanding will be replaced by the agent.

50 years ago @NotAlanKay envisioned that computers could be a new medium, better than the book, for teaching people — especially kids — how to think about the world. In this picture, it might look like these kids are watching YouTube on an iPad, but they're not. They're playing an interactive game and editing the code as they play it to get a better understanding of physics. This was 50 years ago!! 34/

Alright, let's wrap up. Today we've covered some techniques that were about understanding code... but actually I think this is a much bigger issue. It's still important for humans to understand how things work in general! Not just to verify, but to participate. And surprise surprise, this is not a new idea. It harkens back to the very origins of our field of computing... 33/

Recently in Notion we've been shipping tons of new features for humans and agents to work together, so your whole team develops a shared understanding instead of each working in a silo. One tiny example: as of last week you can run Claude and Cursor agents in Notion. I do a lot of my coding that way now. And when those agents makes a technical plan in Notion, it's in a collaborative page by default, so I can comment on it with my team and discuss immediately. Thinking together, not alone! 32/

When you and someone else hold the same mental model, you can communicate efficiently. You have a shared vocabulary that evokes the same images. so you can jam and riff and have creative conversations. Without those shared structures, those conversations are much harder. I'm really excited about creating shared environments where teams build that understanding together. It's kinda what Notion is all about too. 31/

Alright, last technique: Shared spaces. So far this has all been about understanding solo... but when you're working on a team, you need to understand TOGETHER. 30/

The point here is that agents can write bits of code that help us humans understand other code. This is a big deal! 29/

Another example. I was migrating my personal website from one framework to another, and Claude wrote a script that did it — something like this. But it was very hard to review: I wasn't familiar with the new framework, and all I could say was "I guess that looks about right." So I asked Claude to make me a video game — a command center where I do the port myself, step by step, watching the visible effects and the file tree evolve. It produced a UI where I click buttons to run the port step by step, with my old site and new site running side by side. In this command center I watched the new site come to life incrementally. That left me with a similar understanding to doing it by hand — but much faster, because the whole experience was laid out for me. 28/

Last year I was coding a Prolog interpreter and struggling to intuit what was happening inside. I worked with an agent to build this debugger, which let me step through the execution of my logic language — scrub through time, see what's on the stack and which rules are evaluated at each step. I could even leave comments for myself ("nice, we correctly applied that rule"). There's a big difference between making a tool for me to debug and letting the agent debug — doing it myself is how I develop understanding along the way. 27/

(Apparently twitter has a 25-tweet limit for the thread composer. I'm just gonna keep replying here with more slides until I have to board my flight!! 26 and onward!)

Papert had this beautiful idea he called living in Mathland: if you want to learn math, live in Mathland — just like if you want to learn French, you go live in France. Could we build an environment where children learn math naturally, as a consequence of their curiosity? So how do we apply that to code? Can we make worlds you inhabit and naturally intuit how the system works and how it's changing? 25/