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title: Good Engineering Doesn’t Trust Engineers | daily.dev
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# Good Engineering Doesn’t Trust Engineers

**[Leonid Bugaev](https://daily.dev/sources/uqfpqbodd9zyqvagaimem)** · [@leonidbugaev](https://daily.dev/leonidbugaev) · 75 upvotes · 9 comments

## Summary

AI's ability to generate massive amounts of code exposes a long-standing weakness in mainstream software development: it lacks the rigorous engineering discipline found in fields like aerospace and nuclear safety. Drawing on NASA's systems-engineering practices—hazard analysis, independent verification and validation, requirements traceability, and separation of verification from validation—the piece argues that code should never be the sole source of truth. Instead, requirements and evidence should persist independently of implementation, whether written by humans or AI agents. The author's product, ReqProof, is presented as an approach to keep requirements, hazards, and evidence explicit and traceable through an AI-driven development lifecycle, arguing that proportional rigor based on risk is the antidote to both sloppy vibe coding and over-engineering.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.reqproof.com/p/good-engineering-doesnt-trust-engineers>

## Community discussion

Top comments from developers on daily.dev.

**@geekluffy** · 9 upvotes

> That line hits right at the core: _'If removing the keyboard removes our identity, we were never engineers. we just had a temporary monopoly on construction.'_
>
> Typing syntax was never the engineering; understanding environmental constraints, hazard modeling and building systems that assume humans can be wrong is the actual job. Easily the most grounded, necessary wakeup call the software industry has had all year

**@agustinbarrientos** · 3 upvotes

> A two-line authentication change should require more evidence than a thousand-line UI refactor

**@ahmetozel** · 2 upvotes

> Requirements traceability is the piece that translates most cleanly to AI-generated code, and for a reason the aerospace comparison makes obvious: when implementation is cheap and disposable, the requirement is the only durable artifact. Regenerate a module and the code is new, but the hazard it was supposed to mitigate has not changed. The hard part is keeping the evidence honest as the implementation churns - a test that was written by the same agent that wrote the code is verification in name only, which is presumably why independent V and V exists as a separate discipline rather than a...

**@webkmsyed** · 2 upvotes

> This is a strong point.
>
> Relying only on “trust the engineer” (or the AI) has always been risky. When code becomes the only source of truth, small mistakes compound fast especially with AI generating large amounts of it.
>
> Requirements, traceability, and independent verification feel more important than ever. Curious how teams are applying these ideas in practice without slowing everything down.

**@nark3d** · 1 upvotes

> We kept this from slowing anything down by making the requirements runnable. We write the acceptance criteria as checks the agent can run against its own work, and the traceability then lives in the test suite rather than a document that drifts. The second source of truth has to be something a machine can re-verify cheaply, or it turns into a wiki nobody trusts. https://prickles.org/tenet/verifiable-specs/AI4

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---

Tags: [#ai-coding](https://daily.dev/tags/ai-coding)

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