Agent-development systems
Agent Fabric
A multi-agent development system built around a repeatable Research, Plan, Implement, and Validate methodology.
- Audience
- Software teams and AI-assisted developers
- Role
- Methodology creator, architect, and builder
The problem
Parallel coding agents produced activity without durable continuity.
Agents could generate code quickly, but research, plans, decisions, and validation often disappeared between sessions. Multiple agents needed a shared operating method and a way to preserve what had already been learned.
The solution
RPIV made agent work explicit, reviewable, and repeatable.
I created the Research, Plan, Implement, and Validate method and embedded it in a coding system for coordinated agents. The workflow separated investigation from action, retained decisions and outcomes, and made validation part of the work rather than a final afterthought.
Outcomes
The result was a change in operating capacity.
These outcomes describe what this implementation made possible. They are not generic product promises.
Established a repeatable operating method for multi-agent software work.
Preserved research, decisions, plans, and results across coding sessions.
Improved continuity between parallel agents and later work.
How it worked
The architecture followed the work.
The system was organized around an operating sequence people could understand, govern, and improve.
Research
Understand the system and preserve relevant evidence.
Plan
Turn findings into an explicit sequence of accountable work.
Implement
Execute the approved plan in a controlled environment.
Validate
Test the result and retain what the system learned.
My contribution
I created the methodology and the system that operationalized it.
Agent Fabric connected my work in architecture, coding harnesses, recursive intelligence, and decision continuity. RPIV later informed other development and go-to-market systems.
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