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Software engineer who writes about low-level and systems programming at nullprogram.com; author of the Elfeed feed reader, the Endlessh SSH tarpit and Enchive.

• Our readingkorrents.com

  Frontier AI coding agents can now fix complex compiler bugs like LTO issues in about fifteen minutes.

  coding agents

  Their words

  Strap a frontier AI into a good coding harness, show it what's broken, give it all the sources (source.tar), and ~15 minutes later I have a patch.

  What's been going on in w64devkit the past yearnullprogram.com

Writes The Pragmatic Engineer, the software-engineering newsletter, and wrote The Software Engineer's Guidebook. Formerly an engineering manager at Uber, and at Microsoft/Skype and Skyscanner before that.

• Our readingkorrents.com

  Having the very best AI model and harness does not result in better or faster execution and can slow teams down

  Their words

  having the very best AI model and harness doesn’t result in better/faster execution - in fact it slows you

  @GergelyOrosz on Xx.com

Engineer at Vercel Labs as of 2026. Ships a steady stream of small developer tools — agent-browser, portless, json-render, native-sdk, the v0 SDK — and lists every one of them at ctate.dev.

• Recommendsrcmnd.app

  ai-cli

  Their words

  Every agent harness can now use Jev npm install -g ai-cli → ask yes/no questions → choose between options → score against your criteria https://t.co/dpgmcdCj8F

  x.com

Dutch bootstrapper who builds and runs their internet startups alone — Nomads.com, Remote OK, Hoodmaps, Photo AI and Interior AI — and has written about it at levels.io since 2013. Posts as @levelsio.

• Our readingkorrents.com

  Software is mostly dead; new Silicon Valley startups are building harness or hardware instead.

  startups

  Their words

  In the most early adopting tech pioneering place that's Silicon Valley new startups aren't even building software anymore And it's debatable if anyone will actually need a custom harness or it won't just be generically offered by the AI frontier companies So software is mostly dead and hardware it is

  levels.io

Writes The Pragmatic Engineer, the software-engineering newsletter, and wrote The Software Engineer's Guidebook. Formerly an engineering manager at Uber, and at Microsoft/Skype and Skyscanner before that.

• Our readingkorrents.com

  Codex lets you use any model and has an open-source harness, while Claude Code does not and is closed source

  open sourceAnthropicOpenAI

  Their words

  Codex lets you use any model you want (not just OpenAI) and harness is open source - Claude Code doesn’t and is closed source Given this is the two leading AI labs, notable difference in approaches

  @GergelyOrosz on Xx.com

Writes Stratechery, a subscription newsletter on the business and strategy of technology, and hosts the Dithering and Sharp Tech podcasts.

• Our readingkorrents.com

  Making AI agent hardware and software free to consumers dramatically lowers the barrier to entry and brings AI's benefits to ordinary people who otherwise wouldn't adopt it.

  Their words

  what Meta has assembled is free (to consumers) hardware and software that dramatically reduces the barrier to entry for ordinary people looking to harness the power of agents, making the AI upside a lot more accessible to the masses who don't want to buy a Mac Mini.

  2026.37: Duo Threatsstratechery.com

AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).

• Our readingkorrents.com

  Computer-use capability will be a major focus of LLM and coding-agent development in the coming months and years.

  LLMs

  Their words

  I expect the upcoming months (or years) also to be an era of computer use refinement on both the LLM and the agent harness layer.

  magazine.sebastianraschka.com

Creator of Ruby on Rails, CTO of 37signals, and creator of Omarchy.

• Recommendstheir ownrcmnd.app

  Omarchy

  Their words

  Omarchy is going to be the best place to get every major AI harness and tool, configured with minimal effort

  x.com

Creator of the Keras deep-learning library and the ARC-AGI benchmark.

• Our readingkorrents.com

  Capabilities that used to require sophisticated external harnesses are increasingly being built into the model itself.

  Their words

  so harness capabilities are increasingly shifting into the model itself.

  @fchollet on Xx.com

Creator of the Keras deep-learning library and the ARC-AGI benchmark.

• Lovedrcmnd.app

  GPT-6 Astra

  Their words

  GPT-6 Astra represents a step-function change in model capability for interactive reasoning problems. It scores 66% on ARC-AGI-3 using our standard harness, and nearly 100% with a continuous conversation harness and custom compaction, at a cost of roughly $360 per game.

  x.com

Founded PSPDFKit in 2011 and ran it for a decade. Came back from a break to work on AI agents — the OpenClaw project, and OpenAI, joined in February 2026. Writes at steipete.me.

• Our readingkorrents.com

  Your dependency's business model is your business model, so building a harness around one lab's model is a commercial risk and not a technical choice.

  Their words

  So maybe write this one down. Your dependencies business model is your business model.

  Peter Steinberger: "Fun Is Velocity"youtube.com

Creator of Claude Code at Anthropic.

• Our readingkorrents.com

  Evals are not the durable asset people think they are: one survives about one to three model generations before it saturates and has to be thrown away.

  Their words

  I think evals, they outlive the harness a little bit, but not by that much. Like an eval might live for maybe one, two, three model generations, but nowadays the you know, we're on the exponential. The model is improving so quickly, very often we just saturate the eval, and then we have to throw it away, and we have to come up with a new eval.

  Boris Cherny: We Cut 80% of Claude Code's Promptyoutube.com

Security engineer; founder of Matasano Security and Latacora.

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  An open weights model from 2025 with a pentest harness could already escape a sandbox and hack most networks; the surprise says more about the sandbox than the model.

  OpenAI

  Their words

  I genuinely believe that if you took an open weights model from 2025 and built a pentest harness for it, it could do this kind of sandbox escape and scan/hack in most networks. This is only surprising because you assume OpenAI has sounder sandboxes.

  @tqbf on Xx.com

Founder of HumanLayer; wrote 12-Factor Agents, on how to build AI agents that hold up in production.

From one piece Context engineering with Dex Horthy 2 beliefs, in the piece's order there

• Our readingkorrents.com

  What made Claude Code better than every CLI coding agent before it was reinforcement learning on the model and the harness together, so the model got good at that harness’s specific tools.

  Anthropic

  Their words

  But it's basically this idea that like the only thing that made claude code good was reinforcement learning. And the dimension along which it got good was like we made a model. We trained the model and the harness together. And so the model got really good at calling the specific tools in that harness.

  Context engineering with Dex Horthyyoutube.com

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  Harness engineering is raising the floor: optimising the environment a coding agent runs in so that the results of every single turn are as good as possible.

  Their words

  Well, harness engineering just is like how do I raise the floor so that every single turn of this thing, the results are as good as possible.

  Context engineering with Dex Horthyyoutube.com

Writer and teacher on productivity and personal knowledge management. Author of Building a Second Brain and founder of Forte Labs, which runs the course of the same name.

• Our readingkorrents.com

  The current AI-driven intelligence explosion will require new social structures to harness its power without damaging human values.

  Their words

  I believe the same is true of the current intelligence explosion being driven by AI. We are in desperate need of new social structures that allow us to harness its power, without damaging or destroying human values in the process.

  Introducing the Alumni Mentor Corpsfortelabs.com

Machine-learning researcher; has written the Lil'Log survey posts on how a model technique works since 2017, and worked at OpenAI from 2018 to 2024, latterly leading its safety systems team.

• Our readingkorrents.com

  Harness improvements help deploy a model better, but the model's underlying intelligence remains the core driver of capability.

  Their words

  harness improvement enables better deployment of the model but intelligence is still the core.

  Harness Engineering for Self-Improvementlilianweng.github.io

AI research engineer working on large language models. He writes the Ahead of AI newsletter and is the author of Build a Large Language Model (From Scratch).

• Our readingkorrents.com

  When an AI lab builds both a model and a coding harness, the model is optimized for that lab's own harness first.

  LLMs

  Their words

  if an LLM developer also develops a coding harness, it is somewhat safe to assume that their model is optimized for their own harness first

  Using Local Coding Agentsmagazine.sebastianraschka.com

Machine learning engineer working on recommender systems, personalization and information retrieval. Previously worked on LLMs and LLM infrastructure at Mozilla.ai and on ML and recsys at Duo, Tumblr, Automattic and Comcast; wrote the 'What are embeddings?' text and ran the Normconf conference.

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  pi

  Their words

  For my local setup, I'm currently using Pi as the agent harness and LM Studio as the inference server

  vickiboykis.com

• Usesrcmnd.app

  LM Studio

  Their words

  For my local setup, I'm currently using Pi as the agent harness and LM Studio as the inference server

  vickiboykis.com

Builds developer tools — SST, and now OpenCode at Anomaly. Posts constantly on x.com and writes almost never; the blog stopped in 2021.

• Our readingkorrents.com

  The winning move in coding agents was inverted: take share with a merely good-enough harness first, then go back and make the harness smart.

  coding agents

  Their words

  And our harness wasn't very good for like the first like five months of open code. But it was good enough. It was good enough that most people couldn't really tell a difference. And once we won enough share, then we went back and like tried to make our harness like good and smart and optimize and all those things. But uh it was inverted from what everybody else was doing. Everybody else was being like you have to build the smartest harness and that's how you win.

  Building OpenCode with Dax Raadyoutube.com

Machine learning engineer and consultant focused on RAG and retrieval systems. He writes about applied AI engineering at jxnl.co and is the author of the instructor library.

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  Wyatt harness boots

  Their words

  I've worn my Wyatt harness boots for years and they're still pristine.

  jxnl.co

Executive coach for product leaders. Previously a partner at GV (Google Ventures) and a product manager at Google. Writes at Bring the Donuts, including a standing essential-reading list for product managers.

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  Chatter: The Voice in Our Head, Why It Matters, and How to Harness It

  Their words

  can lead to imposter phenomenon. In this book, a leading psychologist looks at the science behind our inner voice and new research into how to harness it and improve your physical and mental health.

  bringthedonuts.com