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Dex Horthy

What Dex Horthy thinks about coding agents

@dex-horthy · 26 positions · On ppll ↗

Founder of the agent company HumanLayer, author of the 12-factor agents principles, and the engineer who put the name "context engineering" on the practice.

Dex Horthy did not write this page.

We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it. Or tell us what is wrong here.

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Only Dex Horthy on coding agents. See everyone on coding agents

13 dated positions, 2026, in their own words. Our reading of what Dex Horthy has said — not written or endorsed by them.

  1. Our readingEvery abstraction in agentic programming — RAG, memory, agentic history, structured output — is just a different way of passing tokens into a model, and understanding that beats learning any of them.

    Their wordsAnd at the end of the day, they're all like different ways to pass tokens into a model and ask it to produce usually some structured output. And understanding that is a lot more powerful than trying to learn memory and trying to pick some agent framework off the shelf and some memory framework off the shelf.

    ↗Context engineering with Dex Horthyyoutube.com 1st of 26 in this recording

  3. Our readingHarness 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 wordsWell, 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 2nd of 26 in this recording

  5. Our readingLoop engineering works exactly as far as verification does: make a problem very verifiable and you can treat it as a black box and let the model run.

    Their wordsAnd I think the lesson in loops engineering is like if you can make a problem very verifiable, you can kind of like treat it like a black box

    ↗Context engineering with Dex Horthyyoutube.com 7th of 26 in this recording

  7. Our readingThe valuable form of loop engineering is a slow loop — a nightly cron job that fixes one thing and opens one pull request — not a redesign of your whole infrastructure around agents.

    infrastructure

    Their wordsSo I think the the thing I'm most excited is actually like what we call like iterated loops or like slow loops where we basically have a cron job. We have the loop the the the structure of the loop is really easy. It's like run this llinter fix one thing commit and push and then we run that every night in our GitHub actions and we wake up every morning to one PR that makes the codebase a little bit better.

    ↗Context engineering with Dex Horthyyoutube.com 8th of 26 in this recording

  9. Our readingWhat 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.

    Anthropicreinforcement learning

    Their wordsBut 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 13th of 26 in this recording

  11. Our readingAgentic code review raises the floor but cannot be trusted, because the model reading the code is the same model that wrote it, and it will tell you the code is great.

    software quality

    Their wordsyes it will catch things and it will raise your floor but I don't believe like the model writing the code is the same model reading the code and if you ask a model hey is this code good it's going to be like oh yeah it's great comprehensive it's got unit tests

    ↗Context engineering with Dex Horthyyoutube.com 14th of 26 in this recording

  13. Our readingIf you want loop engineering, build one loop at a time and keep them small: every part of the agentic-factory playbook is good advice except the part where you stop reading the code.

    Their wordsif you want to do loops engineering, you should build one loop at a time and you should keep them small and contained. Basically, I think everything except stop reading the code is really good advice.

    ↗Context engineering with Dex Horthyyoutube.com 15th of 26 in this recording

  15. Our readingA team that slows down and reads every pull request and every line of code should expect only a 30 to 50 percent productivity lift from AI.

    Their wordsyou can slow way down and read every PR and read every line of code. Uh, and then you're only going to really get modest benefits from AI because that becomes I I think you should expect maybe 30 to 50% lift in productivity is kind of what I see when we go into teams

    ↗Context engineering with Dex Horthyyoutube.com 16th of 26 in this recording

  17. Our readingA plan that spells out every line of code to change gives you no leverage: it costs as long to read as the pull request, so you end up skimming it and reading the code twice.

    Their wordsAnd the plan doc, what was bad about it is it didn't give you leverage. The plan was every single line of code that was going to change like in diff blocks and like all the new stuff to write. And so like people would review these plans. We recommended this. We told people to read the plans. We read all our plans. And then eventually I found myself like I just kind of skimmed the plans.

    ↗Context engineering with Dex Horthyyoutube.com 17th of 26 in this recording

  19. Our readingResearch and planning documents are tactical execution artefacts to be thrown away and regenerated, because tokens are cheap and a doc that has drifted from the codebase costs you time.

    Their wordsI do the research I do the plan I do the implementation I throw the docs out and the next time I need research I just do it from scratch because tokens are cheap and my time is expensive

    ↗Context engineering with Dex Horthyyoutube.com 18th of 26 in this recording

  21. Our readingFour things about a context window decide what an agent does next: its size, whether the information in it is correct, whether information is missing, and the trajectory it is already on.

    Their wordsthere's four things in your context window that matter. There's like the size of it, how many tokens? There's like the quality of the information is like is there any incorrect information? Like if the model had some thinking trace where it decided the wrong thing was true. Is there missing information? Does this like have context missing that it should have? And then there's the trajectory.

    ↗Context engineering with Dex Horthyyoutube.com 22nd of 26 in this recording

  23. Our readingAn agent repeats its own history: whatever it did on the last change — ran the tests or skipped them — is what it will do on the next one, because it is predicting the next message in the conversation.

    Their wordsAnd so if I say, "Hey, make this change." and the agent makes the change and then it runs the test and then they're broken and then it fixes the test. I have very high confidence the next change I asked it to make, it's going to follow that path again

    ↗Context engineering with Dex Horthyyoutube.com 23rd of 26 in this recording

  25. Our readingThe IDE of the future has to be rethought from the ground up for agents, rather than being a text editor with an agents tab bolted on.

    developer tools

    Their wordsbasically the idea is like the IDE of the future needs to be rethought from the ground up for agents. And it might not even be a like I don't know a lot of editors kind of started with the text field and bolted on an agents tab.

    ↗Context engineering with Dex Horthyyoutube.com 25th of 26 in this recording