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On “Harness Engineering for Self-Improvement”
955K subscribers • 1 video on Hallway
Intermediate. Assumes working knowledge.
580K views6 months ago4 recommendations
AI and machine learningTools and practiceTransformers and LLMsAI agents and tool useAI for coding
Mario Zechner explains why he built a minimal coding agent harness and discusses how AI agents are impacting open-source software.
All I wanted was a shitty coding agent that is truly mine. And I’d have loved to just tell you why and how I built pi. But then Peter decided to make it the agentic core of OpenClaw. And now pi is collateral. So yes, this is a talk about pi. But it is also a talk about how agents are destroying OSS, how I deal with that, and a plea to slow the fuck down. x.com/badlogicgames github.com/badlogic linkedin.com/in/mariozechner/ Timestamps – Intro and motivation for building pi – Act 1: Building pi and the frustration with existing agent harnesses – Why current context management in tools like Cloud Code and Open Code fails – The importance of minimal harnesses and the "Terminal" benchmark – Introducing pi: A self-modifying, extensible agent core – The "YOLO" security philosophy and extensibility through TypeScript – Examples of pi extensions (chat rooms, NES, Doom) – Act 2: OSS in the age of "clankers" and how to fight them – Act 3: A plea to slow down and stop the "slop" in software development – How agents create "enterprise-grade complexity" and why humans are still the bottleneck – Practical advice: How to effectively integrate agents into your workflow --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: ai.engineer/talks/RjfbvDXpFls-pi-coding-agent Join our upcoming AI Engineer conferences (see ai.engineer landing page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS 2026 in Sydney ---What people say. Recommended for its critique of bloated AI agent harnesses and its insights on building minimal, self-modifying agent cores.
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