How I can help
I’m interested in problems that need both judgment and implementation: shaping the product, proving the critical path, building it properly, and connecting the result to the way it reaches people.
Clarify
Turn a promising but ambiguous idea into a product direction that can be tested, explained, and built.
Format: Focused discovery or prototype collaboration
Build
Design and ship a focused product or major capability with the technical foundation and product quality treated as one problem.
Format: Scoped product or feature collaboration
Systemize
Connect the product, design language, and launch production so every public asset feels like it came from the same system.
Format: Launch-system or workflow collaboration
Context-aware product systems
I build and operationalize MCP integrations that connect AI assistants to project knowledge, real workflows, and human-approved actions. The protocol is only the interface; the product still needs clear state, permissions, review, and failure behavior.
A project brain keeps the mission, evidence, constraints, decisions, progress, and outcomes attached to the product. MCP exposes only the context and actions a workflow actually needs.
A development-only MCP boundary can validate and export declarative product models or stage a change for review. The running application—not the protocol client—owns approval.
A private Marketing Brain grounds campaign and profile work in project evidence, while external publishing actions remain separated behind preview, immutable approval, and explicit confirmation.
The claim is practical: production-minded integrations and product workflows—not generic protocol demos, autonomous access, or unevidenced commercial outcomes.
AI-enabled delivery
I use AI to shorten the path from an ambiguous question to a reviewed, useful output. The leverage comes from fitting models into a clear product workflow—not asking them to replace context, verification, or responsibility.
Synthesize research, test alternative directions, and create rapid prototypes before committing to the expensive path.
Use engineering assistance for implementation, failure-case exploration, QA, tests, and documentation—then verify it against the real product.
Connect content variation, launch assets, and production steps into workflows with explicit review and approval points.
A lighter format
For situations where the most valuable next step is a sharper decision rather than a larger build.
Review tradeoffs, reduce unnecessary surface area, and identify the risks worth solving early.
Untangle a stalled product, clarify the critical path, and turn broad frustration into a workable sequence.
Identify where models can create useful leverage, define the guardrails, and turn the strongest opportunity into one small, testable workflow.
Selective conversations
No polished request for proposal required. A clear problem, current stage, and honest constraint are enough.
