# Specification Files for Agents > Source: > Published: 2026-09-22 07:00:00+00:00 Something about **AI-based** code generation seems **lazy** or sloppy. After all, "vibe-coding" is often used to convey poor quality. And giving an AI agent short, poorly-reasoned prompts tends to give at best **inconsistent results**. Recently I started experimenting with writing detailed **specification files** (in Markdown) and having an LLM **generate** the required code. I have found using a single function, like `parse_settings` or `parse_prompt`, along with a known `struct` type that is returned is a good strategy. Some notes: • I can get reliable output from Qwen 3.8 27B (actually Bonsai Ternary 2). • Code generation takes about half an hour even for short 150-line outputs. • I can switch models (for example, using a frontier model in the cloud) and the specifications can be reused. • I can just maintain the specifications instead of the actual code, which could be simpler. • It is possible to use an LLM to "debug" a specification and resolve any inconsistencies, which is an important step in this approach.