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The tweet discusses the problem of bloat in AI agent harnesses, agreeing with Kaffu's critique that harnesses become "rich man's toys," and advocates for a composable architecture of small, replaceable workers to reduce drift and keep systems cheap and debuggable.
Recommends a free open-source technical book 'How to Build a 7×24 AI Agent from Scratch', systematically explaining AI Agent engine, digital human protocol, AI browser, production-grade scheduling and other practical content, based on the real 300,000-line open-source project Halo, and written in a human-machine collaboration manner.
This article summarizes four common pitfalls encountered when deploying AI Agents from demo to production: unreliable function calling, cumulative failure rate of multi-step tasks, improper memory management, and security permission issues, along with corresponding solutions.
The author introduces 'Autoharness', a tool that uses Claude Code to autonomously optimize agent harnesses by iterating on prompts and hyperparameters. This resulted in a 40% performance increase on the tau2-airline benchmark.