Feeding reviewed FigJam context back into implementation
Teams use FigJam as a shared source of reviewed context, then pull the board’s diagrams and decisions back into coding agents so implementation reflects earlier collaboration and design intent.
Why the human is still essential here
Humans remain responsible for reviewing comments, refining the plan, approving architectural decisions, and deciding when the work is ready to merge.
How people use this
Board-guided code scaffolding
After a FigJam board is reviewed, the approved diagrams and notes are passed to a coding agent to scaffold features that follow the agreed architecture.
FigJam / CursorComment-aware implementation updates
AI reads FigJam comments and decision notes, then revises the implementation plan and generated code so it reflects stakeholder feedback.
FigJam / Claude CodeDesign-intent merge checks
A coding assistant references the reviewed FigJam board during implementation and code review to keep flows, naming, and edge cases aligned with the approved plan.
FigJam / GitHub CopilotNeed Help Implementing AI in Your Organization?
I help companies navigate AI adoption -- from strategy to production. Whether you are building your first LLM-powered feature or scaling an agentic system, I can help you get it right.
LLM Orchestration
Design and build LLM-powered products and agentic systems
AI Strategy
Go from idea to production with a clear implementation roadmap
Compliance & Safety
Build AI with human-in-the-loop in regulated environments