Early Access • Instruction Layer for AI Development

From goal to merged PR, automatically.

Synapses turns product goals into agent-ready Build Packs. Your AI coding agent gets the context, constraints, and success checks it needs—no more prompt drift.

Join the waitlist See how it works

CI-Ready

Agent-Safe

Predictable

Traceable

What's a Build Pack?

A Build Pack is a portable spec that packages your intent, scope, guardrails, and tests into a single artifact your AI agent can execute.

Example: Add i18n (EN/PT-BR) with toggle

build-pack.yaml

version: 1
kind: build-pack
id: bp_demo_i18n_toggle

context:
  goal: "Increase non-English engagement by 10% in 30 days"
  problem: "English-only site; Brazilian users bounce"
  feature: "Client-side i18n with language toggle"

work:
  tasks:
    - id: t_impl
      name: "Add i18n scaffolding and toggle"
      runner: claude-code
      spec:
        prompt: |
          Add simple client-side i18n to apps/web:
          - Create translation files (en.json, pt-BR.json)
          - Implement minimal i18n util
          - Add <LangSwitch> component
          - Update homepage to use translations
        files_scope: ["apps/web/**"]
        constraints:
          no_touch: ["infra/**", "packages/**"]

validation:
  acceptance_criteria:
    - id: ac_en_hero
      description: "English copy appears on default render"
      check:
        type: regex-on-file
        file: "evidence/home_en.html"
        regex: "Build Packs for AI Code Agents"
    - id: ac_pt_hero
      description: "Portuguese copy with lang=pt-BR"
      check:
        type: regex-on-file
        file: "evidence/home_pt.html"
        regex: "Build Packs para Agentes"

Context

Goal, problem, and feature definition

Work & Constraints

Tasks, scope, and guardrails

Validation & Evidence

Tests run locally, evidence attached to PR

Tests run locally, evidence attached to PR. Reviewers see proof, not promises.

Four pillars of autonomous development

Context Map

Capture goals, problems, and features so AI code agents have real context, not vibes. Reviewers see intent, not guesswork.

Plain-language goals
Links intent to implementation
Measurable outcomes
Reviewer-friendly context

Build Packs

Agent-ready specs that package scope, guardrails, and success checks. Every PR includes evidence-based validation.

Clear scope
Success checks with evidence
Lightweight test plan
Easy to review

Agent Dispatch

Run Build Packs locally on your laptop. No new infra. No security reviews. No cloud dependencies.

MCP-compatible
Local-first. Runs on your laptop
No infra required

Validation Loop

Tests run locally, evidence attaches to PRs. Reviewers see evidence, not vibes.

Evidence-based validation
Tests run locally
Proof in every PR
Reviewers trust the output

How it works

Define intent

Goal → Problem → Feature → Tasks.

Generate Build Pack

Create a compact, agent-ready spec.

Dispatch to AI code agent

Run locally with your agent or share.

Validate & learn

Track what shipped and why it matters.

Already trying agents? Annoyed by flaky outputs?

Why not just write prompts?

Prompts drift. Specs bloat. Build Packs stay crisp, portable, and tied to outcomes.

❌ Just a prompt

"Add i18n to the landing page"

No context. No constraints. No validation.

✓ Build Pack

Context: goal, problem, feature
Constraints: files_scope, no_touch
Validation: acceptance criteria, evidence

Build Packs include 3 things prompts don't: constraints, success checks, and evidence requirements.

Quick comparison

Random prompts

Avoid

Long PRDs

Avoid

Synapses Build Packs

Recommended

Built for every stage

Solo Founders

Move from idea to action without extra meetings. Keep momentum and measure progress.

Write once, act fast
No overengineering
Clear reviews

Product Teams

Give engineers and agents the same source of truth.

Fewer misreads
Aligned execution
Faster PRs

Growing Orgs

Stay consistent as you scale. Add lightweight guardrails as you scale your AI agent usage.

Light governance
Clear ownership
Measurable outcomes