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Startup

Background

A CTO of a 12-person AI startup building a developer tool. Ships weekly, hires monthly, relies heavily on AI agents for code generation, documentation, and planning. Constant context switching between features. Institutional knowledge lives in the heads of 3 founding engineers — and increasingly in forgotten Slack threads.

Goals

  • Accelerate onboarding: new hires should find answers independently within their first week
  • Capture architectural decisions before they’re forgotten in Slack
  • Make AI agents codebase-aware so generated code matches project conventions
  • Maintain visibility of priorities despite rapid pace

Pain Points

  • Feature decisions made in Slack and forgotten within days
  • Architecture knowledge siloed in founding engineers — bus factor of 3
  • New hires can’t find answers: “Why Postgres?” “Where’s auth documented?” “What’s the current priority?”
  • AI agents produce generic boilerplate that misses project conventions

How They Use aDNA

Heavy use of the knowledge and operations layers to capture institutional memory:

  • what/decisions/ — 40+ architecture decision records (ADRs) capturing the “why” behind every technical choice
  • what/context/ — architecture overview, API conventions, tech stack rationale loaded by agents before code generation
  • STATE.md — updated weekly with sprint focus, blockers, shipping timeline
  • how/campaigns/ and how/missions/ — quarterly goals decomposed into sprint-sized missions
  • what/lattices/ — CI/CD pipeline and deployment workflow captured as composable lattice definitions

The startup vault grows fast. Within 6 months it has more files than most mature vaults, driven by the pace of decision-making and feature shipping.

Self-reference: This vault’s what/decisions/ directory demonstrates the ADR pattern the startup relies on. Each decision file captures context, the decision itself, and consequences — exactly the institutional memory that would otherwise evaporate in Slack.

Typical Ontology Extensions

EntityTriadPurpose
api_specwhat/API endpoint documentation with versioning
onboarding_checklisthow/New hire setup and orientation tasks
customer_feedbackwho/Structured customer feedback tracking