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Core Concepts

Five concepts. That's all you need to understand GAAI.


1. Dual Track

GAAI separates two fundamentally different activities:

Discovery Track — figuring out what to build and why

  • Human-facing. Produces artefacts. Asks questions. Validates intent.
  • Owned by the Discovery Agent

Delivery Track — building it correctly and verifiably

  • Execution-focused. Implements. Tests. Passes QA.
  • Owned by the Delivery Agent

Discovery must complete before Delivery begins. This prevents the most common AI failure mode: building the wrong thing fast.

These two tracks are not just different phases — they are architecturally different systems:

Dimension Discovery Agent Delivery Agent
Primary interlocutor The human The backlog
Nature of work Conversation + clarification + artefact generation Deterministic execution against a plan
Output PRDs, Epics, Stories (~short, structured) Code, tests, QA reports
Expected interruptions Frequent — asks the human questions Rare — only escalates when blocked
Context requirement Conversational continuity is critical Phase isolation improves quality
Authorization source Human intent + project constraints Backlog item with status: refined
When it stops Never stops mid-conversation Stops on QA failure or ambiguity

This asymmetry is why Discovery and Delivery have different agents, different authority models, and different activation patterns. They are not interchangeable.


2. The Backlog (The Only Authorization Mechanism)

If it's not in the backlog, it must not be executed.

The backlog is not a to-do list. It is the only authority that permits the Delivery Agent to act.

  • Location: .gaai/project/contexts/backlog/active.backlog.yaml
  • Format: YAML (one file for all active items)
  • States: draftneeds-refinementrefinedin-progressdone

The Delivery Agent reads the backlog, picks the next refined item, and executes it. Nothing else.


3. Agents vs Skills

Agents reason, decide, and orchestrate. They have authority.

Skills execute. They do one thing and produce explicit output. They never decide anything.

Agent Skill
Interprets intent Yes No
Selects context Yes No
Decides strategy Yes No
Executes procedure No Yes
Produces artefacts No Yes

The Delivery Agent invokes the implement skill. The implement skill cannot decide what to implement. That separation is what makes AI execution predictable.

If a skill appears to think, it is wrongly designed.


4. Explicit Memory

Memory in GAAI is never automatically loaded. Agents select what context they need. Always.

This matters because:

  • Auto-loading all memory wastes tokens and introduces noise
  • Context pollution leads to drift and contradictions
  • Explicit selection makes agent behavior predictable and auditable

Memory lives in .gaai/project/contexts/memory/. The structure — project context, decisions log, patterns, summaries — is defined in .gaai/project/contexts/memory/README.memory.md. You can add domain-specific memory files; agents select them explicitly using memory-retrieve.


5. Artefacts as Evidence (Not Authority)

Artefacts (Epics, Stories, Plans) are documentation. They explain intent and decisions. They are not the authorization mechanism.

Documents intent Authorizes execution
Epic artefact Backlog item
Story artefact Backlog item with status: refined
PRD Backlog items it generates

An artefact with no backlog item cannot trigger execution. A backlog item with no artefact can still be executed (though artefacts are strongly recommended for clarity).


Putting It Together

Human intent
    ↓
Discovery Agent (reasons, produces artefacts, validates)
    ↓
Backlog items (status: refined — authorization granted)
    ↓
Delivery Agent (invokes skills, executes plan, runs QA)
    ↓
Done items (move to done/)
    ↓
Memory captures decisions for future sessions

Getting Started — set it up → Quick Start — try it now