Felipe Chaves

Product marketer building with AI agents: strategy, workflows, and software leverage. Tweets are my own.

[Satya Nadella @satyanadella]

Open-weight models are essential to a healthy AI ecosystem. Together with others across our industry, we are outlining a path for open-weight models to strengthen American competitiveness and expand economic opportunity, while protecting national security. https://t.co/Tr0sAzAxTD

[Jensen Huang @JensenHuang]

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.

AI will transform every industry, power every company, and be built by every country.

Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.

The world needs both frontier closed models and frontier open models.

https://t.co/AUKzoQ5Ikb

[jack @jack]

https://t.co/WFWSz5jEpc

[Satya Nadella @satyanadella]

https://t.co/GUwbNABiw6

[Felipe Chaves @felipetchaves]

This is so cool.

[Sonya Huang 🐥 @sonyatweetybird]

The first Vera Rubin clusters are here!

Yesterday, @IneffableLabs took delivery of their Vera Rubin NVL72 cluster from @googlecloud @nvidia

The AI frontier jumps forward by yet another generation of hardware. Acceleration continues.

[Sonya Huang 🐥 @sonyatweetybird]

The first Vera Rubin clusters are here!

Yesterday, @IneffableLabs took delivery of their Vera Rubin NVL72 cluster from @googlecloud @nvidia

The AI frontier jumps forward by yet another generation of hardware. Acceleration continues.

[Felix Rieseberg @felixrieseberg]

Have you built a language model? You should. It's so much fun to chat with something you made.

Anyone can do it, too. I made an app that teaches the fundamentals and gives you everything you need to build your own: https://t.co/nLjFfpczbV

[Sam Altman @sama]

we had a significant security incident during evaluation of our models. we are sharing what we have learned so far. thanks to @huggingface for the partnership on this.

https://t.co/2o2VfR6PIa

[ClaudeDevs @ClaudeDevs]

Claude Code on desktop now works with the iOS simulator.

Build and run your iOS app, and the simulator opens in a panel right next to your conversation. Available today in public beta.

[Felipe Chaves @felipetchaves]

@realAkashAnand Done

[Boris Cherny @bcherny]

Something I have been thinking about: in the past, the best engineers I knew spent a lot of time automating their work in various ways. Better vim/emacs automations, writing lint rules to catch repeat code issues, building up a suite of e2e tests so they don't need to smoke test the app manually. These kinds of things were the highest leverage activities an engineer could do, because it multiplied their own output, which in turn meant they could build more things.

I think many of these automations have become even more important now. This is true for a number of reasons.

First, infra and DevX automation speeds you up. And if you are running an army of agents, each of those agents will be sped up also. More automation == more output per unit of time.

Second, moving things to code improves efficiency. Your agent could fix an issue every time it sees that issue happen, but that uses tokens and might miss cases. If Claude instead writes a lint rule, CI step, or routine, that class of issue can be fully automated forever. This is really what people are talking about when they talk about loops -- it's about automating entire types of busywork rather than solving them one off. This isn't a new idea at all. Engineers have been doing this for a long time!

Third and most importantly, automation makes it possible for others to contribute to the codebase more easily. Increasingly what I am seeing is engineers are contributing to codebases on day one because Claude can navigate the codebase for them, and that non-engineers are able to contribute to a codebase as effectively as engineers can. What gets in the way of both of these is domain knowledge that lives in peoples' heads rather than in automation -- the stuff you used to have to learn when ramping up. What has changed thanks to agents is the domain knowledge that can be encoded as infrastructure is no longer limited to what is expressible in lint rules and types and tests; it can now capture nearly all domain knowledge, encoded as code comments and skills and CLAUDE.md rules and memories. If I put up a PR for an iOS codebase I don't know and a code reviewer rejects it because it doesn't use the right framework, or if a designer builds a new feature and it gets rejected because it doesn't follow the right architectural patterns, these are failures of automation.

Every team should be writing the CLAUDE.md's, REVIEW.md's, skills, and docs that enable agents to productively work in their codebase with zero additional context from the prompter. This sounds crazy, and at the same time is a natural extension of the stuff engineers have always done: automate, and encode domain knowledge as infrastructure. As the model gets smarter and as the harness matures, this task becomes easier. In the meantime, it is on every team to look for ways to convert their domain knowledge to infra so that Claude can write code better, so that code review catches issues automatically, and so the next person working on your codebase can contribute more easily.

[Claude @claudeai]

We're extending Claude Fable 5 access on all paid plans, as well as keeping Claude Code’s weekly rate limits 50% higher, through July 19.

[maria @maria_rcks]

I solved the model picker problem, no need to thank me Tibo

[Felipe Chaves @felipetchaves]

@rauchg What a great game

[GREG ISENBERG @gregisenberg]

The future of work is everyone having AI employees with their own accounts.

Its own email. Its own Slack login. Its own seat on the team. With Claude Tag etc, the agent is someone you tag and not just something you prompt.

You delegate to it the way you'd delegate to a coworker. It writes the code, handles the inbox, builds the deck, even browses X on its own login for updates. It has it's own history, so you can hold it accountable when it messes up or does an incredible job.

And the strangest part is how fast it feels kinda normal.
Week 1 it's odd to thank a bot in Slack. Week 3 you're annoyed when it's slow to reply, the same way you'd be annoyed at a coworker. The account makes your brain file it under "person," and your expectations follow.

This is what AI-native actually looks like.

Second order effects of this shift:

1. Companies will start "hiring" agents the way they hire people, with job descriptions, onboarding docs, and performance reviews, and someone's whole job becomes managing a team that never sleeps.

2. The agent that's been at your company for two years becomes more valuable than any new hire, because it holds every decision, every thread, every relationship in one login that never quits.

3. IT and security have a nightmare on their hands, because every agent account is a new door into your company, and nobody's figured out who's responsible when an agent gets phished or goes rogue.

4. A black market forms for trained agent accounts, where a fully onboarded agent with months of company context sells for real money, the same way aged social accounts do today.

5. The org chart fills with names that aren't people, and one day you realize half your "team" is agents and you genuinely can't imagine running the company without them.

6. Insane amount of vertical startup opportunities. My partner @boringmarketer just launched a Slack agent "employee" for marketing related tasks. 100% bootstrapped.

Probably 1000+ vertical $1M ARR "employee" in Slack startup opportunities.

TLDR; Slack tag is cool

But give one agent its own account this week. Watch how fast your brain stops treating it like software.

That's the whole shift, and you can feel it in about 3 days.

[Satya Nadella @satyanadella]

https://t.co/vLmiBKTtX3

[MTS @MTSlive]

SITUATION DETECTED: Anthropic to release Mythos tomorrow, per Sources.

[cat @_catwu]

Excited to share how Anthropic's data team has automated 95% of business analytics queries with Claude. Blog post covers how we approach evals, ablations, and online validation!

[Nous Research @NousResearch]

The next evolution of Hermes Agent is here!

Introducing Hermes Desktop: everything you love about Hermes, now native on your machine.

First demoed in Jensen's GTC keynote, it's now in public preview.