Backend · Programmer · AI Programming

The Real Vibe Coding Superpower Is a Brutally Detailed Spec

By SamDeepThinking · Jul 14, 2026

Read original on juejin.cn ↗ Google Translate ↗ Alt translation

Engineers who spend their time wrestling AI-generated code in chat threads are optimizing the wrong loop. A polished spec acts as a lossless handoff that raises the probability of a correct one-shot generation, turning AI from a conversational debugger into a reliable code executor.

Summary

A production bug fix required a 700-line, 2,000-word specification built through dozens of back-and-forth rounds with AI. The process mirrors what mature engineers already do — analyze requirements, design solutions, and think through boundary conditions — but externalizes it into a living document that doubles as a machine-readable instruction set.

The chat is not the work product. Consensus from each discussion round gets precipitated back into the spec: correct content stays, missed scenarios are added, wrong parts are revised. The result is a structured input containing business context, design rationale, constraints, edge cases, and acceptance criteria, not a sprawling chat log.

When the spec was complete, the AI generated the full fix in one pass. The human's job shifted to code review and deployment verification. No iterative code tweaking was needed because the upfront investment in specification quality eliminated downstream rework.

Takeaways

— Specs written with AI for a production bug fix reached 700 lines and 2,000 words after dozens of refinement rounds.

— AI does not know which data is critical, which legacy logic must be preserved, or which code paths are off-limits — the spec must encode all of this.

— Constraints like “do not break original code,” “minimize change scope,” and “prove the bug is fixed” are stated explicitly in the spec.

— The human decides the overall design approach; AI is used to surface missed scenarios, better implementations, risks, and unhandled boundary conditions.

— Chat history is treated as raw material — correct content is kept, gaps are filled, and errors are corrected — producing a clean spec rather than a long, messy thread.

— A complete spec functions as a well-formatted AI instruction that includes business background, design thinking, constraints, edge cases, and acceptance criteria.

— With a sufficiently polished spec, AI generated the full fix in one pass; the human only reviewed, tested the main flow, and deployed.

— Time spent polishing the spec replaces time that would otherwise be spent repeatedly modifying AI-generated code.

Conclusions

The core shift is treating the spec as the durable artifact and chat as ephemeral scaffolding — most AI-coding workflows invert this, leaving knowledge trapped in threads.

A spec refined over dozens of rounds becomes a lossless encoding of business context that no prompt snippet can match, which explains why one-shot generation success rates climb with spec maturity.

The workflow described is essentially design-level pair programming with AI, where the human retains architectural authority and delegates completeness checking to the model.

Calling this “the greatest trick of Vibe Coding” is a deliberate provocation: it reframes the term away from casual prompting and toward rigorous, specification-first engineering.

Concepts & terms

Spec Driven Development

A workflow where a detailed specification document — containing requirements, business context, design decisions, constraints, edge cases, and acceptance criteria — is iteratively refined with AI before any code is written. The finished spec serves as the primary instruction for code generation.

Vibe Coding

A colloquial term for AI-assisted programming where developers describe what they want in natural language and let AI generate the code, often through conversational back-and-forth. The term is sometimes associated with casual, underspecified prompting.

Source: juejin.cn ↗ Google Translate ↗ Backup ↗