Open-weights models struggle with rigid developer instructions

This is a classic "vibe coding" vs "engineering" clash — open-weights and mid-tier models often collapse under the weight of strict negative constraints and formatting rules.

• –The highly specific comment style rules (imperative mood, specific punctuation per line type) are notoriously difficult for smaller models, which tend to revert to their pre-training distributions
• –Pi Coding Agent relies entirely on standard Markdown files like `AGENTS.md` to steer behavior, meaning success depends completely on the underlying model's system prompt compliance
• –While models like Kimi and GLM are improving at coding logic, they still trail behind GPT-4o and Claude 3.5 Sonnet in rigid adherence to multi-part instructions
• –The thread underscores that high "reasoning" settings do not automatically translate to high instruction fidelity