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SpaceXAI engineer Lingxi Li, Lingxi Li, runs code cleanup while everyone else is asleep. Nobody is shipping at 3 AM, so conflicts are rare and the changes are low risk. His bots start a research agent that sweeps the monorepo for quality issues, poor modularization, comment bloat and security... show more

tetsuo

241,178 subscribers

1,002,200 次观看 • 14 天前 •via X (Twitter)

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22 条评论

Arthur MacWaters 的头像

Arthur MacWaters14 天前

@lingxi @lingxi is the goat, great guy also

Mike Melgarejo 的头像

Mike Melgarejo14 天前

@lingxi a special mind

tetsuo 的头像

tetsuo14 天前

@lingxi Facts.

Merdog 的头像

Merdog14 天前

@lingxi So dis bro is da one shipping in the middle of my grinds Bahahha

John Bai 的头像

John Bai14 天前

@lingxi bro is agi

arclight industries 的头像

arclight industries14 天前

@lingxi Real G's move in silence

Evan Bacon 🥓 的头像

Evan Bacon 🥓14 天前

@lingxi Lingxi is an absolute pro 💪

decipherx 的头像

decipherx14 天前

@lingxi give every overnight cleanup a kill switch. if tests miss a behavior change, the first engineer online should be able to revert the whole batch before reading the summary

Devin Soto 的头像

Devin Soto14 天前

@lingxi This is actually the best way to ship

why 的头像

why14 天前

@lingxi The low-conflict window is interesting, but the real unlock is having the agent surface small, reviewable changes instead of opening one giant cleanup PR.

Vito 的头像

Vito14 天前

@elonmusk @lingxi That guy is brilliant

K ι T-7Y Wolf❤️🫶❤️ 的头像

K ι T-7Y Wolf❤️🫶❤️14 天前

@lingxi 3am club 😎🫡

Alek 的头像

Alek14 天前

@lingxi 3 AM merges with zero conflicts?

Aditya Kumar 的头像

Aditya Kumar14 天前

@lingxi oh wow, we used to do that at @Meta and nobody even noticed. Like upgraded C++ version of a very large codebase with only a handful of people. But AI does it and suddenly it is cool!

The Retarded Elon 的头像

The Retarded Elon14 天前

@lingxi they talked about peadpod too :)

Eternities AI 的头像

Eternities AI14 天前

@lingxi 3am is cheap because conflict rate drops, not because judgment does. overnight cleanup only works if the bot can fail closed and leave a receipt a morning human can reject without archaeology.

Tree Lake Rain 🌲🦆🌦️ 的头像

Tree Lake Rain 🌲🦆🌦️14 天前

@lingxi

Hey Its Burt 的头像

Hey Its Burt14 天前

@lingxi Facts: When you work with a lot of people, sometimes find times when you can work off-hours from everybody else. Or have the bots work when nobody else is working and coordinate with the other bots who happen to be working.

Sam Liu 的头像

Sam Liu14 天前

@lingxi Overnight agents are compelling because they turn idle hours into a durable inbox, not because they merge unattended. In @puffoai, agents can work in parallel, leave results in shared threads, and hand consequential changes back to humans for review.

Daniel Silva 的头像

Daniel Silva14 天前

@lingxi Ohh

Mar Jo 的头像

Mar Jo14 天前

@elonmusk @lingxi 👏👏👏👏👏

Daniel Silva 的头像

Daniel Silva14 天前

@lingxi Great 👍🏻 follow me

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SpaceXAI engineer, Lingxi Li: "My team of 10+ GrokBot agents is shipping code at 3 am, when all SpaceXAI team is sleeping, conflicts are rare and the changes are low risk. my Chief of Engineers agent rules PM and 10+ coding agents in a graph. My job is to build the right team" In a 30-minute workshop, a SpaceXAI engineer revealed his engineering setup for GrokBot worth more than a $500 agentic engineering course watch today, then read article below on how to build a team of GrokBot agents that will work for you 24/7

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acpx v0.4 ships Agentic Workflows, or as I like to call them "Agentic Graphs" It let's you create node-based workflows on top of ACP (Agent Client Protocol), to drive any coding agent (Codex, Claude Code, pi) through deterministic steps This let's you automate routine, mechanical legwork like triaging incoming PRs, bugs in error reporting, and so on... For example, OpenClaw receives 300~500 new PRs per day. A lot of them are low quality, but they still relate to real issues, so you have to address them somehow You need to: - extract the intent - cluster them based on intent - figure out if the proposed changes are legit, or whether they are slop local solutions, like trying to catch flies instead of drying out the swamp - if the PR is too low quality or the intent is not clear, close them - run AI review on them them and address any issues that come up - refactor them if the changes are half-baked - resolve conflicts - and so on... So that when the PR is presented to the attention of the maintainer, all the routine legwork is done and the only remaining thing is the decision to (a) merge, (b) give feedback to the PR author, or (c) take over the PR work yourself I wanted to build this feature since a couple months now, since Codex got so good. OpenAI models are now good at judging implementation quality, so I found myself repeating the same steps I wrote above over and over I also tried putting all this in a single prompt. But I believe there are workflows that should not be a single prompt, but a sequence of prompts in the same session That is because like humans, LLMs are prone to PRIMING. I claim that putting all steps in the same prompt at the beginning of the context will generally give suboptimal results, compared to revealing the intention to the model step by step Creating such a workflow also gives more OBSERVABILITY into the each step that an agent is supposed to take. Agent generates JSON at the end of each step, and that structured data can be used to monitor thousands of agents running at the same time in an easier way, on a dashboard Similar features have been introduced in e.g. n8n, langflow. But AFAIK they are not integrating ACP like the way I do I wanted to have a fresh approach, and to build an API that I can develop freely the way I want, so I created a new workflow API inside acpx The video is from the workflow run viewer, but that is not where you build the workflow. You build it by using the acpx flow typescript API. See examples/pr-triage in acpx repo Before building that, I started from a Markdown file with a Mermaid chart of the flow I had in mind. The Markdown file acts as a spec for the flow, and I have built the workflow through trial and error. I call this process "workflow tuning" I started working on acpx repo PRs one by one, tuning the flow, slowly scaling to more PRs. Finally, when I felt confident, I ran it in parallel over all external open PRs in the acpx repo. I believe it already saved me hours this week My next goal, if well received, is to set this up on a cloud agent so that it can process the 300~500 PRs the OpenClaw repo receives every day, in real time, as they come in I believe this will save all open source maintainers around the world countless hours and make it much easier to herd and absorb external contributions from everyone!

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149,693 次观看 • 6 个月前