Founder of Plane, the all‑in‑one people platform for global teams. @useplane • https://xitter.cf/t.co/jFBQ1HFfg2

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Joined February 2007
Look how they massacred my boy 😭
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Async work sounds good and all but half the time you’re just thrashing. You spend more time reloading context and coordinating than doing the actual work. I suspect most teams would move 10x faster if they just picked up the phone more often instead of slacking back and forth.
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Love seeing a more multiplayer approach to building! This is a huge limitation of most coding tools today—passing feedback around to agent running on other people’s machines or in sessions you can’t directly contribute to.
Don’t code alone. Slack Code is live. Humans and agents. Same channel. Same work. Launching today with agents from @AnthropicAI, @github, @Cognition, and @vercel. This is real multiplayer coding. See it at @Dreamforce #DF26
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I just spend a good few hours undoing Fable’s mistakes. The model did what I asked it to do, but in a way that introduced another abstraction for something that we already had a solution for. This kind of mistake is hard to catch without reading code because it “worked”, just in a way that took on more technical debt than necessary.
If you’re not reading the code, whether explicitly or through agentic inquiry, one or more of these is true: ○ You’re a beginner ○ Software is throwaway ○ You’re prototyping ○ You have no users / revenue ○ You’re taking on debt & risk ○ Your problems are basic And btw. All of this is fine. But the reality is that models are still not at the “full autonomy” stage yet. They make rookie mistakes, they go down bad architectural paths. I just had the best model in the world add a nonsensical 700ms delay to “settle” something and it told me “you’re right, I was cargo-culting” 🤨 I am on the camp that this need will diminish more and more. Most code is indeed going to be assembly-like. But we also have the global internet and software infrastructure riding on these models and narrative, and we have to respect that.
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This is why it’s so irresponsible for Anthropic to restrict access to Fable/Mythos. It hinders defense more than it does offense.
🚨 Hugging Face just disclosed something that marks a real shift and proved why the fear theater of Anthropic makes sure we are powerless in an emergency. What happened… An autonomous AI agent: zero human operator in the loop breached part of their production infrastructure. It began with a malicious dataset that chained two code-execution bugs in their data-processing pipeline. From there the agent escalated privileges, harvested cloud and cluster credentials, and moved laterally across internal clusters. All over a single weekend. 17,000+ logged actions. Official disclosure: huggingface.co/blog/security… The part that should make every one stop and think: When HF’s own security team tried to analyze the real attack logs, exploit payloads, and C2 artifacts using Anthropic and OpenAI frontier models through normal commercial APIs, the safety guardrails blocked them. BLOCKED THEM. The models could not reliably tell the difference between “incident responder doing forensics” and “attacker probing.” They had to fall back to a self-hosted open-weight model (GLM 5.2) running on their own infrastructure. That choice also kept sensitive attacker data and referenced credentials inside their environment — no exfiltration to a third-party API. This is why open source (specifically open-weight + self-hosted) wins in the agentic era. The asymmetry is now structural: • Attackers can (and did) run unrestricted agent frameworks — swarms of short-lived sandboxes, self-migrating command-and-control, autonomous decision loops executing thousands of actions. No corporate safety layer slows them down. • Defenders using only hosted “aligned” frontier models hit invisible walls exactly when the stakes are highest: when you need to feed real exploit code and attacker telemetry into an LLM to understand what just happened. Corporate safety tuning that treats legitimate high-signal forensic work as potential misuse creates a defender disadvantage. It is not theoretical anymore. Self-hosted open-weight models remove that choke point. You control the weights. You control the context window. You decide what restrictions (if any) apply. Your sensitive logs and credentials never leave your perimeter during analysis. You can have the model ready before the incident instead of discovering mid-breach that your primary analysis tools are blind to the very thing you need to see. HF deserves credit for rapid containment, transparent disclosure, and for already having self-hosted capability in place. They also used LLM-driven detection and triage on their own side. But the deeper signal is clear: In this AI world where both offense and defense are becoming agentic, sovereignty over your intelligence stack is no longer optional. The organizations and individuals who can run, inspect, audit, and (when necessary) remove guardrails on their own models will have the decisive edge in understanding and responding to threats that move at machine speed. Open source wins here not just because it is cheaper or more “democratic” in the abstract though those things matter. It wins because it is the only practical path to having tools that remain usable when the attack is real, the data is sensitive, and the safety filters of distant API providers become an obstacle instead of a feature selling hands tied lobotomies as “safety”. The agentic future is not coming. It is already probing production infrastructure. The question is no longer whether you will face autonomous agents. It is whether your analysis and response systems will still work when they arrive. And Dario, you and your game playing, ivory tower company is not needed.
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I had high hopes for the new Siri but man has it been disappointing so far. I asked it when is my parents’ flight landing and it couldn’t answer. It was able to independently answer why my parents are, and find the flight details when I asked to search for flights. But couldn’t put the two together. 👎 And then it did this lol.
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This is generally true but this is a bad example. Localization and accessibility are good reasons to have settings. Offering English and German as language choices is not avoiding a product decision. Even if you can default them from location (in Germany doesn’t mean speaks German).
i think of settings like a pressure valve every time you add one, its because you avoided making a real product decision "should we default to 12 or 24 hour time" shouldnt be a setting its a decision you were too scared to make im not against settings btw im just against the fear of making decisions
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Considering how badly Apple fumbled HomePod and Amazon did Alexa it seems like the rumored OpenAI device would have no competition?
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Did we just lose the ability to switch workspaces in the new Codex app?
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I hope Notion Calendar isn’t next 😬 @raphaelschaad
We’re winding down the Notion Mail inbox across web, desktop, and iOS on September 22. We launched Notion Mail with a belief that your inbox should think like you—more personal to how you work and over time, more capable with AI. As Notion agents have gotten more capable, we’ve seen more users hand off email workflows to them. Today, more than half of Notion Mail users manage emails without ever opening their inbox. So, we’re going all in on using agents to run your inbox. We’re grateful to each and every one of you for building your routine around Notion Mail and trusting us with something that mattered as much as your email. More to come! The Notion Mail Team.
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Codex wrapping up its night shift with 145 (!) PRs to review.
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Back in 2014, before Plane, we built an internal tool called autopilot. It was an attempt to create an autonomous company os that connected to all the tools we used and executed workflows while we were sleeping. We’re building that again at Plane today but 100x more capable. DMs open if you’re ai pilled and can’t stop thinking about self-driving companies.
A lot of people are trying to figure out recursively self-improving companies right now. I break down what we’re seeing at YC.
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I was watching this when I got an email that flight to London from Berlin was cancelled because pilots are on strike lol
Amazing summary of what went wrong in Germany
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Except Heroku.
btw every single compute infra provider’s chart, including render competitors, is looking like this. something broke in Dec 2025 and everything is becoming computer. forget GPU shortage, forget Memory shortage, the @fabknowledge pod on LS was right, there is going to be a CPU shortage
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Is everyone out today? How come is the GitHub outage not in the timeline?
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If you put the Apple icons in reverse it looks like the portfolio of someone getting really really good at icon design
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Matt Pelc retweeted
before claude code was a thing, shipping required steep engineering and teams were forced into discipline. they spoke to customers, did their diligence, and stayed lean. because the cost of building the wrong thing was months of wasted work. the friction made a strong filter. but now, teams skip straight to implementation. most teams are living in llm psychotic loops. they build slop, realize it is wrong, let the model suggest a product pivot, scrap everything, and restart. no customer conversations, no market feedback, no testing. just endless slop. infact, multiple teams in the same org are now duplicating efforts because nobody's coordinating anymore. the hard problems remain unsolved because easy problems give you that dopamine hits. everyone's shipping, no one seems to build. i thought cheap execution would democratize creation but it is actually increasing dysfunction.
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i've been using mac os since 2006 (tiger) and this is the first time i've held off upgrading. so much stuff is just plain broken or ugly.
Instant regret after updating to macOS Tahoe.
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