Daniel Chu

@thsottiaux I think the “definition” and hence the design and implementation of Ultra may not be correct. Even at Pro sub, one can probably only have 2-3 Ultra sessions. Ultra shouldn’t have been designed as “maximize token burn regardless of outcome”.

Hello beautiful people! We have reset usage limits across Codex and ChatGPT Work. And another one will come later in the day. Rejoice. Now that I have your attention, a quick update on ChatGPT Work, Codex and all the updates we shared yesterday. We’ve spent the last 24 hours reading feedback, looking at usage patterns, and talking with many of you. The short version is that there is a *lot* of excitement for GPT 5.6 Sol, ChatGPT Work on mobile & web, but also that we didn't get everything quite right. - We made it too easy to use the highest-compute settings without making the impact on usage limits sufficiently clear. - We reorganized the desktop app in one bold move, making familiar things like chats and projects harder to find. - Our launch framing was focused on ChatGPT Work and to some of our Codex fans it made it feel like Codex was going away over time. Absolutely not our intention, we love Codex and it is here to stay. - And we introduced regressions for some existing multi-agent workflows, alongside a collection of rough edges in plugins and other parts of the experience. We’re landing a first set of improvements today. We’re resetting usage twice so people can keep experimenting, changing defaults and the model picker so they don’t push people toward unnecessarily expensive settings, fixing several plugin submission issues, improving how we represent Codex in the product, and cleaning up some of the most immediate desktop problems. A larger set of improvements will land next week. We’re bringing chats and projects back into the sidebar in a more familiar and customizable way, making usage and reset timing much more visible, clarifying when to use ChatGPT Work and when to use Codex, and addressing the many other smaller pieces of great feedback we've had. The ambition behind this launch hasn’t changed. We think bringing ChatGPT and Codex together into a workspace where people and agents can collaborate is a very important step forward. But an ambitious direction doesn’t excuse avoidable confusion or regressions in the first version. Please keep the feedback coming. We’re moving quickly, and you should see the experience already get better with a few updates today; and substantially better again next week.

@thsottiaux thank you for making “Codex” work without removing into my computer. Feels great to be in the flow all the time now!

@trq212 You are a loop on your own

my process for writing right now is to do some engineering work, talk to a bunch of people about it, brainstorm and research with Claude, write a post, give 1 or 2 talks on it, rewrite the post, give another talk, rewrite the intro, wake up at 6am and rewrite it again, then post

@thsottiaux Just love this response! I always hate the feedback loop that goes: Me: “hey there might be a bug” Recipient: “repro it otherwise you are wrong and I am ignoring you”. I am keeping my sub just for this response!

Codex team is in a warroom on a Sunday combing through logs and checking whether there is anything that could lead to increased usage drains for some users. Taking it very seriously and won't rest until we get to the bottom of it.

When code becomes cheaper, product judgment becomes more valuable. Agentic Engg cannot replace customer understanding, onboarding, trust, or human adoption. Product development was never just about coding. Full essay: danielchu.dev/articles/produ…

@thsottiaux Please help enable reset on Mobile. I do 90% of my work on Mobile and once it hits limit, I can’t do anything about it

What should we improve in the Codex app. What's not delightful?

@thsottiaux I am using /fast a lot more on fixing system-breaking (or just annoying) bugs with excitement instead of anxiety!

Now that you can bank usage resets in Codex. Are you a hoarder or do you use them without breaking a sweat? How do you think about them?

Just learning about getting the quality loop right. Next: wanna experiment on the evolution loop

The hardest part of making agents self-improve wasn’t getting them to write code. It was getting failures to survive long enough to be learned from. The loop is the product: failure -> artifact -> issue -> eval -> fix -> replay -> new evidence. #AIAgents #AIEvals

Self-improving agents do not improve from autonomy alone. They improve when failures leave evidence: broken invariants, approval edges, terminal states, replayable evals. Otherwise it is still human memory with tools attached. Full piece: danielchu.dev/articles/self-…

@thsottiaux @Kappaemme1926 Codex mobile... it's too anchored to “my computer.” But my docs are in Drive. My repos are on GitHub. My work is already online. The phone should be enough to say: edit this doc, hunt this bug, monitor a thread, etc.

@Kappaemme1926 That's my line

If you use Codex daily, what’s your biggest complaint right now?

@thsottiaux I open ChatGPT mostly for Codex now. Codex mobile shouldn’t be a laptop remote. Ideas show up away from the desk, and repos/runners can live in the cloud. Let me turn a thought into a branch, prototype, sim run, or working diff. Hello world, Codex app? 🙂

@thsottiaux Your rest post was the nudge I needed to finally try /fast. I’d been avoiding it because of usage burn, but the reset made it easy to try on real eval/review-agent work. Fresh tokens give me way too much dopamine now 😂

The Codex usage limits have been reset for all paid ChatGPT subscriptions. You should be back to 100% weekly and 100% hourly limits. Let the tokens do incredible things today and have fun.

still very early though 😂 the hard part so far is making failures legible enough that the next loop has something real to learn from.

been thinking a lot about “compounding” in agent systems. the uncomfortable realization: my agents could fix issues once I named them, but they weren’t learning from their own behavior. so the next loop I’m building is observability → artifacts → issues → evals → fixes.

@claudeai lol I think I accidentally built a version of this into my harness because Claude Code + Opus kept getting too optimistic on complex work. Guess I can delete some code now 😂

Also new in Claude Code: dynamic workflows (research preview). For the hardest tasks, Claude makes a plan, runs hundreds of parallel subagents, and verifies its work before reporting back. Think a migration touching hundreds of files. Read more: claude.com/blog/introduci…

Introducing Claude Opus 4.8: it builds on Opus 4.7 with sharper judgment, more honesty about its own progress, and the ability to work independently for longer than its predecessors. Available today at the same price.

The dangerous AI eval result is not a red score. It is a green score nobody can explain. If the PM cannot say what behavior the eval measures, green becomes theater. The team is not learning. It is just watching a dashboard.

Before PMs write evals, they need a real feel for the user job. The pain. The expectation. The failure mode. Without that intuition, evals become a black box the team delegates to someone else. That is when measurement starts drifting away from product judgment.

If AI keeps making workflows, memory, and context easier to transfer, the old SaaS switching-cost playbook gets weaker: data lock-in, setup cost, personalization, etc. So what creates durable retention? Maybe it’s delegated trust built through repeated delegations.

A colleague made a casual comparison: AI subscriptions are starting to feel like streaming services. Gemini, ChatGPT/Codex, Claude as Netflix, Disney+, Apple TV+. The latest hot show wins the month. The others get cancelled until the next launch 😂