.txt

Agent Frameworks Considered Harmful — Rémi Louf, .txt

Aug 22, 2026 · 20:29

Rémi Louf, CEO of .txt, argues agent frameworks are harmful because they keep agents trapped in code; he built a runtime where agents are markdown files triggered by events. Taking two weeks away from his 15-person company, he wanted a morning briefing that processes voice notes, market news, and CRM updates. Each failure in the first week led to infrastructure: an append-only log, a real queue, and content-addressed prompts stored as hashes, enabling diffing and replaying runs. He insists typed tool calls and typed events are non-negotiable boundaries, since 20% of his events were malformed and rejected. After deploying it, 20 agents now run, and he replaced third-party APIs with open-source models. His advice: build before you buy.

No more bad outputs with structured generation: Remi Louf

Oct 14, 2024 · 15:32

Rémi Louf, CEO of .txt and co-maintainer of Outlines, argues that structured generation—guiding LLMs to produce valid regex, JSON, or context-free grammar outputs—eliminates parsing errors and hallucinations while adding negligible overhead. Outlines masks tokens that violate the target structure, enabling Mistral 7B to achieve 99.9% valid JSON (vs. 17% without). It also accelerates inference: a chatty 50-token ChatGPT answer shrinks to 8 tokens, and structured generation boosts open models beyond GPT-4—Phi-3 Medium hits 96.5% on Berkeley function calling (GPT-4 gets 93.5%). With one shot matching eight shots in accuracy, Louf contends that most text is structured and that structured generation should be the default for non-chatbot workflows.