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Everything We Got Wrong About Research-Plan-Implement - Dexter Horthy

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  • Recommended by 2 people: 2 in engineering communities.
  • Presented by Dexter Horthy, founder of HumanLayer
  • An opinion. It argues one side of a question engineers disagree on.

Intermediate. Assumes working knowledge.

148K views7 months ago2 recommendations

AI and machine learningTools and practiceAI agents and tool useAI for codingTransformers and LLMs

Dexter Horthy explains why the Research-Plan-Implement pattern for AI agents failed and advocates for more structured human ownership of code.

Dexter Horthy (HumanLayer) Keynote at the Coding Agents Conference at the Computer History Museum, March 3rd, 2026. Abstract // RPI was supposed to fix AI coding, but Dexter Horthy says it kind of broke it, especially when teams started outsourcing thinking to agents, so now he’s pushing qrspi: fewer magic prompts, more structure, more human ownership, because the real problem isn’t the AI, it’s engineers trying not to think. Bio // Dex is currently focused on building AI coding agents that can tackle complex problems in large codebases at HumanLayer. Prior to this, he worked on APIs for agent orchestration and human-in-the-loop systems, and authored the April 2025 essay “12 Factor Agents,” where he first coined the term “Context Engineering.” He has been coding since high school, when he built tools for NASA researchers to navigate the Moon’s south pole, and is an enthusiast of tacos and burpees—though not necessarily in that order.

Why it's here

2 people recommend this

What people say. Recommended for its insights on maintaining code quality and human oversight when using AI coding agents.

u/kammcein r/embedded • Recommends

On “What parts of embedded development would you actually trust AI to automate?”

All of those. LLM are a force multiplier in the hands of an expert. Meaning, when you ask it to give you info or insights about any of those bullets, then you ensure that the info is correct. I recently seen a talk about AI agents where the founder of the AI agent startup used to say, "read the plan not the code". Now he says "Please, please, I beg you, read the code. You must" link to this video I'm not an AI super user and I find that agents produce more code then I have time to review.
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u/Azaexin r/ExperiencedDevs • Recommends

On “How are experienced teams preventing architectural drift as AI-assisted development scales?”

…ns. this is not good and where things can destabilize. my view at this point is, this is pretty much where traditional planning really cuts back in but at higher points of leverage. if code is mostly dealt with by the agent, the next "too much to juggle" becomes tasks and whole verticals not the code itself. ref his current state of discourse: [video what he eventually gets at without maybe quite realizing it at the time is like, the summary of plans he's describing is basically at the level of what i think a TPM juggles, ironically enough, except the leverage now sits around the engineer. also we don't use their agent skills directly, just taking inspiration from the subtle context e…
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