I’ve been watching the “AI coding agent” space explode: faster scaffolds, faster refactors, faster everything. The downside is also obvious: when you move fast, you can end up with a pile of code that kind of works but doesn’t match what you actually meant.

That’s why GitHub’s Spec Kit caught my eye.

Quick note: I haven’t personally tried Spec Kit yet — these are my notes based on what I’m hearing (and what I watched a coworker do with it).

Spec Kit is an open source toolkit that pushes you toward spec-driven development: write down what you want, why you want it, and the constraints you care about — and then let an agent implement from that spec instead of guessing from a vague prompt.

Repo: https://github.com/github/spec-kit
Docs: https://github.github.io/spec-kit/

The moment it clicked for meLink to heading

A coworker of mine used Spec Kit on a POC project and the “shape” of the work looked different right away:

• Less back-and-forth about what we meant
• Fewer surprise abstractions
• More predictable output across multiple agent runs

The punchline: when the intent is captured in a spec, the agent doesn’t have to invent it.

The Spec Kit workflow (high level)Link to heading

Spec Kit’s “happy path” looks like:

1. Establish your project principles (“constitution”)
2. Describe what you want to build (the spec)
3. Convert it into a technical plan (stack + architecture)
4. Break the plan into tasks
5. Implement the tasks

If you’ve used agents before, you’ll recognize the steps — the difference is Spec Kit makes them explicit and repeatable.

A concrete example (mocked)Link to heading

Here’s the kind of prompt sequence that makes Spec Kit feel powerful. You don’t start with “write me code”. You start with constraints and outcomes.

1) Create a constitutionLink to heading

This is the part most teams skip, and it’s the part that saves you later.

Example:

/speckit.constitution
Create principles focused on: readable code, tests for critical paths, predictable UX, and performance budgets.

What I’d put in here (for my own projects):

• Prefer boring solutions over clever ones
• Tests for core flows before shipping
• Small PRs, no huge rewrites
• Explicit error handling and observability

2) Specify the feature (the “what” and “why”)Link to heading

Example:

/speckit.specify
Build a feature that lets users share a read-only link to a board. The link expires after 7 days. Viewers cannot see private boards. Include analytics for link creation and link visits.

This is where you define outcomes, boundaries, and edge cases. If you do it here, you don’t have to fight the agent later.

3) Provide a technical plan (the “how”)Link to heading

Example:

/speckit.plan
Use Postgres for storage. Use server-rendered pages for the share view. Use signed URLs with an expiry claim. Track events via our existing analytics client.

4) Generate tasks, then implementLink to heading

Example:

/speckit.tasks
/speckit.implement

Now the agent is implementing against your constraints, not improvising them.

What I like about Spec KitLink to heading

• It turns “agent prompting” into an artifact. The spec and plan become part of the project’s memory.
• It reduces drift. If you rerun the agent later, you’re not starting from scratch.
• It makes reviews easier. You can review intent (spec) separately from execution (implementation).

Where it might not fitLink to heading

I don’t think Spec Kit is necessary for every change. If I’m renaming a variable or tweaking CSS, I don’t need a constitution and a task list.

But for:

• New features
• Cross-cutting refactors
• Anything that spans backend + frontend
• Anything where requirements are “obvious in someone’s head” but not written down

…this is exactly the kind of structure that keeps an agent from going off the rails.

If you want to try itLink to heading

From the Spec Kit README, you can install the specify CLI with uv:

uv tool install specify-cli --from git+https://github.com/github/spec-kit.git

Then initialize a project and pick an agent:

specify init . --ai codex

(That --ai codex bit is particularly nice: Spec Kit explicitly supports multiple agents, so you can keep your workflow consistent even if the tools change.)

Closing thoughtLink to heading

My coworker’s use of Spec Kit made something really clear: the bottleneck isn’t writing code anymore — it’s capturing intent.

Spec Kit is a good forcing function for that. And if you’re already building with agents, it’s one of the most practical ways I’ve seen to get “speed” without losing “clarity”.