When I first started experimenting with “vibe coding,” building apps with AI agents felt like a superpower. The ability to spin up prototypes in hours was exhilarating. But as I soon discovered, the initial thrill came with an illusion. It was like managing a team of developers with an attrition rate measured in minutes—every new prompt felt like onboarding a fresh hire with no idea what the last one had been working on.
The productivity boost was real, but the progress was fragile. The core problem was context—a classic case of the law of leaky abstractions applied to AI. Models would forget why they made certain choices or break something they had just built. To cope, I invented makeshift practices: keeping detailed dev context files, enforcing strict version control with frequent commits, and even asking the model to generate “reset prompts” to re-establish continuity. Messy, ad hoc, but necessary.
That’s why GitHub’s announcement of SpecKit immediately caught my attention. SpecKit is an open-source toolkit for what they call “spec-driven development.” Instead of treating prompts and chat logs as disposable artifacts, it elevates specifications to first-class citizens of the development lifecycle.
In practice, this means:
- Specs as Durable Artifacts: Specifications live in Git alongside your code—permanent, version-controlled, and not just throwaway notes.
- Capturing Intent: They document the why—the constraints, purpose, and expected behavior—so both humans and AI stay aligned.
- Ensuring Continuity: They serve as the source of truth, keeping projects coherent across sessions and contributors.
For anyone who has tried scaling vibe coding beyond a demo, this feels like the missing bridge. It brings just enough structure to carry a proof-of-concept into maintainable software.
And it fits into a larger story. Software engineering has always evolved in waves—structured programming, agile, test-driven development. Each wave added discipline to creativity, redefining roles to reflect new economic realities—a pattern we’re seeing again with agentic coding. Spec-driven development could be the next step:
- Redefining the Developer’s Role: Less about writing boilerplate, more about designing robust specs that guide AI agents.
- Harnessing Improvisation: Keeping the creative energy of vibe coding, but channeling it within a coherent framework.
- Flexible Guardrails: Not rigid top-down rules, but guardrails that allow both creativity and scalability.
Looking back, my dev context files and commit hygiene were crude precursors to this very idea. GitHub’s SpecKit makes clear that those instincts weren’t just survival hacks—they pointed to where the field is heading.
The real question now isn’t whether AI can write code—we know it can. The question is: how do we design the frameworks that let humans and AI build together, reliably and at scale?
Because as powerful as vibe coding feels, it’s only when we bring structure to the improvisation that the music really starts.
👉 What do you think—will specs become the new lingua franca between humans and AI?
