2026 method

Spec-Driven AI Coding

Write the spec once. The agent runs it, hands you a diff, closes the ticket. One-shot prompts are last year.

AgentsRoom wires a Claude Code, Codex or Gemini agent to every ticket on your Kanban backlog. The spec becomes the unit of work.

What is spec-driven AI coding?

A spec is a well-written ticket: an objective, constraints, acceptance criteria. Spec-driven AI coding hands that ticket to an AI agent that codes, tests, and ships a PR. You stop writing prompts on the fly. You write a spec a human or an agent can run, then you give it to an agent.

The contrast with vibe-coding: vibe-coding is conversational, you steer the agent in real time. Spec-driven coding is disciplined async. You write, you launch, you come back when it's done. With one agent, it's clean discipline. With ten agents in parallel, it's the only way to keep your head above water.

โ€œA good spec saves ten prompts.โ€

Rule of thumb

The 4 pillars of a spec-driven loop

Without these four steps, you're doing prompt-driven coding in disguise. With them, you industrialize.

1

Readable spec

A short ticket with context, objective, constraints, acceptance criteria. Not a novel. Not a vague memo. The format a new human dev would read without asking back.

2

Isolated task

One spec, one branch, one agent. Not two specs on the same agent. Not one agent touching three areas of the code at once. Clean scoping comes from the backlog, not from the chat.

3

Autonomous agent

The agent reads the spec, plans, codes, runs the tests, opens the PR. You only step in when something blocks. No babysitting. Push notifications when it's done or when it needs you.

4

Human review

You read the diff scoped to the agent, not a tangled blob. You accept, you fix, you merge. The spec closes the ticket. The loop restarts.

Why AgentsRoom fits spec-driven coding

Backlog, ticket, and agent live in the same app. That's rare.

Native Kanban backlog

Drag and drop a ticket into a column, an agent picks it up. No need for Jira or Linear to start: the AgentsRoom backlog is enough, and it's versioned in your repo.

Optional public backlog

You can expose your backlog to clients via a URL. They file specs from the Chrome extension. You triage, you launch the agent. Client-driven development without a custom pipeline.

Multi-provider per ticket

One ticket on Claude Code, the next on Codex, another on Gemini CLI. You pick the model that fits the spec. They all coexist in the same dashboard.

Per-agent review

Each agent's diff is isolated. You read what one agent did, not a blend of five sessions. The spec only closes the ticket if the review passes.

Spec-driven AI coding FAQ

How is this different from prompt engineering?+
Prompt engineering optimizes a message sent to an LLM. A spec lives outside the chat: it's a ticket with an objective, constraints, and acceptance criteria. You can store it, version it, hand it to a human or an agent. Prompts are ephemeral. Specs are assets.
Do I need an external ticketing tool (Jira, Linear)?+
No. The AgentsRoom Kanban backlog is built in and stored in your repo. If you already use Jira or Linear, you can wire an MCP and let the agent read tickets from there. To get started, the native backlog is enough.
How many specs can one agent handle in parallel?+
One agent runs one spec at a time. You parallelize by launching multiple agents on multiple specs. With AgentsRoom, users routinely run 5 to 10 simultaneous agents, each on its ticket, each on its branch.
What does a good spec for an AI agent look like?+
Three sections: context (where it lives, why it matters), goal (what we want), acceptance criteria (how we know it's done). Bonus: a link to the file or function involved. Avoid vague specs: if a human would hesitate, the agent will go off the rails.
Does spec-driven coding work on legacy code?+
Yes, and that's where it shines. Legacy means a thousand small cleanup tickets. Write them once, fan out one agent per batch overnight, review the PRs in the morning. More productive than a human grinding the same refactor for two weeks.

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