Free playbook: A practical operating model for AI across the SDLC

The Product

From product intent to an agent-ready plan.

Enact, the spec governance platform for AI coding teams, creates a shared specification layer before code. It combines customer and team context with the realities of your codebase, gives product and engineering one place to approve the plan, and preserves those decisions as work moves into issue trackers and AI coding tools.

01

Capture context

Connect the evidence behind a feature: product intent from a customer call or ticket, decisions your team has already made, and the constraints that already exist in your codebase. Enact reads what's already true instead of asking someone to retype it.

  • Pulls context from Slack threads, support tickets, and customer calls
  • Maps which services and repos a change would actually touch

02

Approve the plan

Enact turns that context into a structured, section-by-section plan — scope, non-goals, acceptance criteria, and the technical approach — that product and engineering review together before anything is built. Nothing moves forward on a private assumption.

  • One shared document both sides sign off on, not two separate ones
  • Every open question gets resolved before implementation starts, not during code review

03

Handoff without drift

The approved plan becomes structured work in Jira or Linear, and the same context becomes the brief your coding agent works from — Cursor, Claude Code, Copilot, or Windsurf. As the plan changes, that change is traceable back to who approved it and why.

  • Keeps Jira/Linear tickets and the agent's brief in sync as scope changes
  • Preserves a decision history you can point to when something ships differently than expected

Not another PRD generator

A PRD describes a feature. Enact governs what happens after it's approved.

A PRD generator produces a document and stops there — what happens next is up to whoever reads it, if they read it at all. Enact is built for the part that comes after: the plan stays attached to the work as it moves into Jira or Linear, stays attached to the coding agent that implements it, and stays attached to the history of who approved what and why. If scope changes mid-build, that change is visible in the same place the original approval happened — not buried in a Slack thread or a doc nobody reopens.

It's also not a replacement for Jira, Linear, or the coding agent you already use. Enact sits one layer above them — it's the shared source of truth that makes what you hand to those tools accurate in the first place.

The difference shows up most clearly when scope changes mid-sprint. In a PRD-based workflow, that change lives wherever someone happened to write it down — a comment, a new doc, a message that only reaches half the team. In Enact, the same plan updates in place, the approval history shows exactly what changed and who signed off on it, and the coding agent picks up the revised brief instead of building against a version that's already stale.

Who it's for

Product managers

Write the intent in plain language and see exactly what engineering committed to build — no waiting on a translated ticket to find out.

Engineering leads

Get a plan that already accounts for what the codebase actually looks like, so agents aren't guessing at architecture decisions mid-build.

Founders and small teams

Skip the overhead of a full PM function while still getting a real spec — plain language in, structured plan out.

Why we built it this way

“My last startup raised a seed round. We had the team, the runway, the ambition. What we didn't have was a clean line between what the PM decided and what engineering built. Every sprint felt like a game of telephone. By the time a decision reached the engineers, half the context was already lost. That gap doesn't just slow you down — it compounds until it breaks the team.”
Dushyant Kumar

Dushyant Kumar

Co-founder, Enact — read more on the team behind Enact

Every step in the product above exists to close that exact gap — not by adding process for its own sake, but by giving product and engineering one artifact they both trust before an agent starts writing code.

FAQ

Frequently asked questions