Agents need boundaries.
Gravis and DevBridge explore the loop around a coding agent: scoped work, verification, recovery and operator visibility. A bounded repair budget is a concrete example of deciding when automation should stop.
Behind the interface.
Inside the decisions.
Useful AI is a workflow: inputs, context, execution, verification and a clear place for human judgment.
01Understand
Define the job and its constraints.
02Orchestrate
Connect context, models and tools.
03Verify
Check results and handle failure.
04Deliver
Make the output usable and reviewable.
Evidence belongs in the design.
Fortrua maps career evidence into generated drafts. Crossed Out supplies retrieved context to its AI guide. Both make the source of a response part of the implementation, while retaining the need to review output.
Some rules should stay deterministic.
Made Easy’s signature, waiver and deposit checks are explicit business logic. A language model can help draft an estimate; the authorization decision should be inspectable.
Explore the
implementations.
PLANEXECUTEVERIFYRECOVER
GGRAVIS
02 / AGENT SYSTEMS
↗Gravis + DevBridge
An AI development ecosystem separating the orchestration of work from the runtime that executes it.
EVIDENCE E01
Experience.
With a source.
REQUIREMENT → EVIDENCE → DRAFT
05 / APPLIED AI
↗Fortrua
An AI career workspace connecting job discovery, evidence-based matching and reviewable application drafts.
How this portfolio works
The opening scene uses a custom WebGL point field, procedural geometry and pointer-driven camera movement. Project navigation stays in semantic HTML. Motion can be paused, reduced-motion preferences are honored, and the content remains accessible without the scene.