Bret Taylor: evaluation

Transcript context

…The thing that seems to me is funny is if you look at the landscape, still in 2026, if you open a new Gemini chat or if you open a new ChatGPT chat, it's basically a blank slate. There's no memory. Then, I mean, Claw, people talk about the WhatsApp and Telegram integrations and things like that. But it feels to me a big part of the value is not only can it do stuff proactively, but it has memory. But the way it has memory is this super janky... It's like the movie Memento. It writes things to a markdown file, and it's just writing the things to remember, and the compaction is kind of buggy. It didn't always write down the exact right things to remember and stuff like that. But isn't it funny that you can get super polished mainstream consumer apps that have no memory at all, or this wildly insecure three-name-changes project that almost remembers things by scribbling notes in the margin, and that is the state of consumer AI. I have a, probably not very thoughtful, but technical theory on this. Coding agents to have gone through transformation over the past four months. The difference between if we were here in October versus now, our conversation about the future of software engineering would be materially different. How often can you say that about a technology? People always, in my circles anyway, you look at a coding agent and you extrapolate to other domains. You're like, "Could all digital tasks be like this? " The answer is obviously yes, over some period of time. But it's really interesting because sometimes, I think the hard part of engineering is in the details, and code repos have very specific qualities. One is all the context is in one place, in files that are largely textual, not binary. For most broad information tasks, that's not true. When you're writing your annual letter, my guess is the sources of information were in so many different systems, data warehouses. It's not impossible for an agent to use those things, but the idea that you can straight-line from coding agents to writing the Stripe annual letter, I don't totally buy. Then similarly, when the agent's actually performing work on a code base, there's feedback, there's compile errors, there's often unit tests, there's integration tests. There's the history of every change that we made in a really formal format, along with code reviews. It's almost designed for a robot, and you can self-reflect. Maybe we as engineers have always modeled ourselves after robots, and now we can actually fully realize that vision. What's interesting about it is the idea that it wrote a markdown file for memory, I think is maybe more significant than a hack. I actually think to some degree— Turning your life into code?…

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