My maybe controversial opinion: If TTFT is important to you, you're doing something wrong. Don't wait for the agents, make them wait for you. Don't stare at a single transcript. Do something else. (Yes, there's a tiny number of exceptions to this.)

Increasingly convinced: people who do best with agents are those that are good at shipping things in small pieces. Someone who could ship a feature in 4 commits going to main now does better with agents than the guy who always ended up with a 6k PR on Friday afternoon.

Another thought I had yesterday in that conversation: These models are so much more now than text-to-code converters. Think bigger! Aim higher! Now that the models can contribute across your whole stack, vertically, it's to let them loose horizontally: Let them monitor deployments, let them debug prod, let them do ops, let them help end to end. If you think "they'll screw this up" that's on you and your codebase. Either you need to spend more tokens and build up instincts or you need to make your codebase and company processes friendlier to agents.

Unexpectedly found myself in a conversation about agents yesterday evening with someone who now has to use Qwen at work, because company wants to save money. Really struggled with expressing how much of a category change using latest frontier models is vs. using Qwen.

Same prompt, four modes/models: - GPT-6 Sol - Opus 5.5 - High (GPT-6 Astra) - Ultra (Fable 5.1) Here's the prompt: "Look at the last two news posts we published on runner functionality: one runner is now enough, and one runner many worktrees. I now want you to write a news post that's similar but for the functionality behind the `shared-runners` feature flag. It should probably also contain a screenshot of the picker that shows two normal runners and two shared runners, like `gpu-runner` or `macos-builder` or something and some nic elooking avatars and good data. And it should succinctly explain how it works and how people can use it." Costs: - Opus 5.5: $9.54 - GPT-6 Sol: $3.10 (estimated list price, using sub) - High: $7.58 (estimated list price, using sub) - Ultra: $15 Notes: - Ultra took by far the longest, Ultra is the only one that didn't create docs (I didn't say they should create docs but I think the other models looked at previous commits and figured out they should do that?) - Ultra was the only model that didn't prominently display the "give me the grant to upload assets at the end" - I think Opus 5.5 is the best result. It really feels like more creative (headline) and it nailed the screenshots. - High is my second favorite.

I'll say this: I've gotten more out of using orbs and asking agents "test this e2e & give me irrefutable proof it works" than out of 80% of tests I've written and ran over the last 15 years. It's truly remarkable that we can now ask machines: "Did you manually test it?"

I know people who spent $12k in tokens and built nothing. @Westpac spent $12k in tokens on @AmpCode and built a new intranet for their 35,000 employees (vs. ~$3–5M pre-AI cost). "Amp is unlocking a huge amount of value in engineering" from

Quite a few people clowning on me for saying that UI will be generated on the fly. Two things: 1. You don't have to generate it all from scratch, but dynamically assemble widgets. 2. Tried chat jimmy? In a few years, we could have today's frontier intelligence at this speed