Context Is the Source of Truth.
Software Is the Deliverable.
With proper context saved, AI can re-build the solution with no intervention
Context Driven Development
AI-driven requirements interview captures intent as structured context
Context is created, reviewed, and approved before solutioning
Multi-AI solution design and project plan development
Tasks assigned to specialized AI subagents for parallel execution
All context saved on GitLab Kanban boards with human approval gates
Five Phases of Context Driven Development
Context flows forward through every phase — each step enriches the next
AI-Driven Requirements Interview
Structured Specification
Interview produces a formal requirements document. Reviewed and approved by the human before any solutioning begins.
AI Collaboration
An interactive session between human and AI to ensure the AI has a deep understanding of the vision and key requirements for a complete specification.
GitLab Board Created
A dependency chain is automatically created on GitLab, tracking the feature from requirements through execution. Human controls pacing.
Multi-Model Solution Design
Broad reasoning across system boundaries. Workflows, integration, scalability.
Code-focused analysis. Catches structural issues, validates feasibility.
Practical execution and infrastructure fit. Synthesizes into unified design.
When Does the Review Board Fire?
Solution design • Solution critique • Plan generation • Plan peer review • Architecture decisions • Spec validation • Debugging 2nd opinions
AI Review Board: Critique Loop
All three AIs attack the solution for over-engineering. Refactored and re-synthesized based on critique.
Your AI Software Development Team
Coordination
Task sequencing
ADRs
Integration
Network rules
Compliance
Databases
Implementation
CI pipelines
Validation
Agents divide tasks and work in parallel — just like a real engineering team
Plan Vetted by 3 AIs, Tasks Assigned to 5 Agents
Grey areas flagged as DECISION cards for human judgment before execution begins
Plan Becomes GitLab Cards
Every Commit Triggers a 5-Stage Pipeline
20 E2E test blocks • media pipeline checks • 9 smoke test functions
Board-Driven Workflow
Human in the Loop
AI never closes issues. Humans approve, reject, or redirect at every stage. DECISION cards pause execution until the human picks an option.
Free-Form Comments
Any card supports optional free-form comments. Check the "Read comment" box and the AI reads your feedback and adjusts course mid-task.
Context Is the Source of Truth.
Software Is the Deliverable.
With proper context saved, AI can re-build the solution with no intervention
