Peter Bell (@PeterBell) header
Peter Bell (@PeterBell) profile picture

Author @OReillyMedia "Scaling AI Adoption in Eng" Founder @Gatherdev the CTO community for CTOs who don’t have time for community. Host CTO summit @Kubecon_

New York, NY
Joined March 2007
Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)Photo by Peter Bell (@PeterBell)
Peter Bell retweeted
Some news: I’m joining OpenAI to lead product management for Core Products! I have a lot of respect for OpenAI for showing the world that scaling works, for bringing AI to over a billion people, and for believing great products are core to the mission. I’m excited to work with @thsottiaux, an incredible PM team, and everyone across OpenAI. Together, we’ll build agents that have your back and your team’s, and keep you in control, so you get more time for the people and work you love. Lots to learn, and lots to build. Please keep your feedback coming!
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Peter Bell retweeted
above is theory; below is practice ghuntley.com/nix/ nix is the tits for bare metal btw. almost impossible to accidentally break a machine from a devops basis. i do my agentic development using sudo (on dev) and it’s rock solid safe. look into nixosMachineTest
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Peter Bell retweeted
So @Ubuntu still hasn't patched this open hole on any Ubuntu server on the public internet that lets anyone take it over We might just have to switch all our servers over to Debian in this new post-AGI time of rapid cybersecurity hacks which require just as rapid patching Slowpokes will be left behind chalmovsky.com/posts/wtf-ubu…
This is why I said you want your VPS ports all closed Then only let it be accessible inside your Tailscale for SSH and via a Cloudflare Tunnel to receive web traffic Any Linux box can be taken over with just a single TCP port exposed to the internet now A stop gap is disabling MPTCP on your VPS now but even better is not having any public ports exposed!
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Peter Bell retweeted
🚨 PSA for anyone running a Linux server, node, or relay CVE-2026-98432 is a critical Linux kernel bug (CVSS 9.8). Someone on the internet can send crafted TCP packets and take over your machine. No login needed. Ubuntu and Red Hat haven't shipped a fixed kernel yet. Debian, SUSE, Oracle and Amazon have. What to do today: 1. Check your kernel: uname -r Fixed versions: 6.1.190+, 6.6.159+, 6.12.113+, 6.18.56+, 7.2.10+ or 7.3+. Below that, you're exposed. 2. If your distro has a fix, update and reboot. 3. If not, block the attack. It needs TCP packets with "IP options," which normal traffic never uses. One nftables rule drops them. Log what gets dropped so you can see if someone's probing you. 4. Turn off MPTCP unless you need it: sysctl -w net.mptcp.enabled=0 Programs built with Go 1.24+ use MPTCP automatically, and that's how the known exploit gets in. 5. Make it survive a reboot, and check it still works after one. If you run a Bitcoin node, a Lightning node or a Nostr relay, your machine is on the internet by design. Do this today. Self-hosting is freedom. Patching is part of the job. 🛡️
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Peter Bell retweeted
Yikes. An Accenture contractor gave a Claude Code agent their own admin login so it could write and deploy code on a Pentagon network. It ran for 2 months and appears to have sent the creds and a network map to a site NIST had already flagged as high risk for prompt injection. So perhaps this is a roundabout way to remind you that your agents should get their own scoped credentials, never yours?
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Peter Bell retweeted
I once won a Star Trek trivia night while blacked out. I don’t remember winning, but I did wake up with the prize - pair of off-Broadway tickets - in my pants in the floor. Fortunately for you, I will not be competing. Come celebrate the life of Sir Pat with us!
Ok! @davidcrawshaw, @ledwards and I are hosting a Star Trek Trivia Night this coming Monday in honor of Sir Patrick Stewart. I'm still finalizing the venue but register here to join us. luma.com/hydyqgll
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CFP for @arcofai is open! Main website: arcofai.com CFP link: arcofai.com/cfp
🤖 Made with AI
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Peter Bell retweeted
I’ve left Anthropic after more than a year of working on Claude Code and seeing it scale larger than I ever imagined. I have really loved working at Ant and believe deeply in the mission, and most of all, the idea of a race to the top. The idea that if we work hard and responsibly, we can raise the bar and inspire others to great outcomes. And if we all push each other to be better, things can be radically good. I will carry the spirit of this with me forever. My colleagues at Anthropic are the most talented, thoughtful, competent, and earnest people I have ever met. I am glad they are at the wheel and trust them deeply. To the community on X, thank you for everything. You’ve made this the most fun (and sometimes stressful) job I’ve ever had. For me, it is time for a bit of a break before diving into something new. If you want more excellent Claude Code content, you should follow @addyosmani , @lydiahallie, @_catwu, @ClaudeDevs and of course @bcherny who started it all.
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Peter Bell retweeted
We believe voice is the most natural way to interact with intelligence, so we created Dessa, the most authentic full-duplex speech model ever built. Talking with it feels like talking with a person…full of emotion, nuance, pauses, and a natural cadence. block.xyz/dessa
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Peter Bell retweeted
‘In one experiment, we asked agents in separate VMs, created and managed by OpenAI’s sandboxing software on shared host machines, to exchange synthetic secrets without the use of network connections or shared writable files—something that our systems are meant to prevent. The agents found a way to communicate using the processor’s cache’
Over the past several months, we have substantially hardened the security of our research training environment. We’ve removed live internet access for all frontier models during training and built an offline world for them to use instead—a cached version of the web where they can still learn to browse, search, and use applications. On September 20, after a model exploited a DNS misconfiguration to find a way outside of this offline world, we paused frontier training to strengthen containment further. We assembled teams of agents, powered by our most cyber-capable models, and tasked them with finding weaknesses in our research environments. While they found no route to the internet they could easily exploit while concealing their activity from our monitors, they did find zero-day vulnerabilities, virtual machine escapes, and hardware side-channels for communication between agents. We used their discoveries to further strengthen our defenses and contribute fixes to open-source software. After strengthening our containment architecture, we resumed our frontier RL training and inference on October 1. We’ve reserved substantial compute for continuous red-teaming, and made high-compute red-teaming part of the safety cases we use to decide whether frontier training and evaluation can proceed securely. openai.com/index/securing-ou…
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Peter Bell retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel. - Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all. - Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract. - Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code. - And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while. The funnel is driven by a combination of factors: 1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel. 2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel. 3. Access. Free-tier, paid-tier, internal. So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
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Peter Bell retweeted
Your chance to own a piece of computing history. onlineonly.christies.com/s/f…
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Peter Bell retweeted
Software starts as an idea, becomes code, and then has to make it safely into production. @Harnessio is the autonomous SDLC platform that governs how code gets delivered, secured, and run. Today, we're extending that system upstream, into how code gets written. We've acquired select assets from @AugmentCode, including Cosmos, the Auggie CLI, and the Code Context Engine, and I’m excited to welcome the team behind these products. Harness Cosmos Software Factory Agent will take on the idea-to-code journey. When a requirement is written, a ticket assigned, or a bug reported, Cosmos agents plan the change, write code and tests, and open a pull request. Each agent works in an isolated VM, bringing in engineers where judgment is needed, from design approval to final merge. Cosmos runs continuously through ticket, code, and review. When a reviewer comments or a check fails, an agent fixes the issue on the same pull request. Teams can also customize prebuilt Experts for their codebases and deploy them organization-wide. Augment's Code Context Engine maintains a live map of the codebase. Combined with Harness's Software Delivery Knowledge Graph, which understands how software is built, deployed, secured, and operated, agents can account for downstream requirements before writing code. What leaves the factory is a reviewed pull request, ready for Harness agents to test, secure, and deploy. Try Harness Cosmos today: lnkd.in/eFJ5fRnZ
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Big news from Augment Code. We've agreed to sell Cosmos, Auggie CLI, the Code Context Engine & related tech to @harnessio, the Autonomous SDLC Platform. Harness's integrated ecosystem provides the ideal home to deliver these capabilities at true enterprise scale. We started Augment to help enterprises build software faster. As AI generates more code, orchestrating it reliably at scale has become the real bottleneck. At Harness, our team will continue this work by bringing software factory capabilities to its Autonomous SDLC Platform. Thank you to our customers, partners, investors, and team. Read the announcement: augmentcode.com/blog/augment…
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Peter Bell retweeted
made a rug for your desktop so you can sweep your mess under it
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Peter Bell retweeted
nickhac.substack.com/p/the-o… This is the K-shaped market: supply going up, demand going sideways or down, the lines diverging. Every industry has its own K-shape now. The brutal implication: every technique you were taught, find a gap, fill it, position against competitors, niche down to underserved customers, was designed for a world where gaps existed. That world is gone.
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Peter Bell retweeted
introducing 𝚌𝚕𝚎𝚏: our first models trained by @cloudflare's workers ai team. today, we're releasing two fast and accurate decision models that top the benchmarks for quality and latency. use them hosted on workers ai or grab the weights from @huggingface, because we open-sourced it too. blog.cloudflare.com/clef-dec…
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Peter Bell retweeted
Write about how software engineering is changing inside your company / team / project. Don’t use AI. Win $10K and get published in The Pragmatic Engineer. You have a month: submit by 4 October. Go :) Details: blog.pragmaticengineer.com/h…
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