Spec-First Development: Why LLMs Thrive on Structure, Not Vibes

The shine is starting to wear off vibe coding. I know, because I’ve been there. One moment I’m in Cursor, impressed by what a large language model can produce. The next, I’m staring at the clock, realising I’ve lost hours because it couldn’t navigate the complexity of the codebase I’m working on - and I find myself back in PyCharm, questioning the value of the detour.

One answer that’s emerging is "Spec-First Development". You don’t toss vague instructions at an AI and hope for magic. Instead, you craft the clearest, most rigorous specification you can - and let the agent build from that. Better still, treat specifications as code artefacts: versioned, under source control, and continually refined with compacted, curated context.

For me, this isn’t a radical shift. I’ve long worked with test-driven development, where the unit test is the specification. And LLMs thrive on this. Unit tests aren’t just notes in prose; they’re executable specifications - formal, computable, and unforgiving in all the right ways.

That’s the deeper lesson: when you hand a spec to an LLM, the more formalisation, the better. Natural language is fine, but structure wins. Code loves tests. Maths loves notation. Business, however, has no equivalent - no unit test for strategy documents, compliance rules, or process design.

Enter ontologies and knowledge graphs. They give us a way to formalise business semantics, capturing domains in rigorous, computable detail. Paired with an LLM, they don’t just guide the generation - they also validate it.

The future of agentic coding - and of LLMs in business more broadly - won’t be built on “vibes.” It will be driven by how well we can formalise intent: transforming ambiguity into something structured, testable, and executable.

⭕ Spec-kit: https://lnkd.in/dPZCgUeq
⭕ What is an Ontology: https://lnkd.in/ePS7ha8z
⭕ What is a Knowledge Graph: https://lnkd.in/e5ed_f8g