Claude Agent SDK
2 Artikel
Harness Debt: Ihr KI-Agenten-Gerüst arbeitet still gegen das Modell (2026)
Ihr KI-Agent ist wahrscheinlich schlechter als das Modell darin — und die Lücke ist Ihr eigenes Gerüst. Ein experimentelles Harness erzielte mit demselben Modell mehr als das Doppelte von Anthropics Standard-Harness. Die Lösung ist kein größeres Framework, sondern das Löschen von Annahmen, die am Tag des Claude-Opus-4.6-Release veraltet waren.
Harness Design for Long-Running AI Applications: Inside Anthropic's Generator-Evaluator Pattern (Claude Agent SDK, 2026)
On 24 March 2026 Anthropic Labs engineer Prithvi Rajasekaran published the most rigorous public account to date of how Anthropic designs harnesses for long-running AI applications — a GAN-inspired generator-evaluator pattern applied across two unusually different domains: frontend design (subjective, no binary verification) and full-stack coding (objective, machine-verifiable). The piece evolves the November 2025 Initializer + Coding Agent baseline into a three-agent planner + generator + evaluator architecture, with concrete cost-and-duration data ($200 / 6h on a retro game maker test, then $124 / 4h on a more ambitious DAW after the Opus 4.6 simplification pass). Inside the pattern, the two failure modes it fixes (context anxiety + self-evaluation bias), how it compares to LangGraph / AutoGen / OpenAI Assistants v2 / Devin, when it doesn't fit, and the canonical principle every team operating a harness should adopt: stress-test every component against the current model.