Product systems / senior product leadership

Product judgment for systems that cannot be reduced to a roadmap.

14 years across fintech, Amazon Pay infrastructure, marketplaces, AI workflow systems, and 0->1 products.

I work where product direction, architecture constraints, and operating cadence have to meet. The work below moves from signal to proof to the artifacts behind the decisions.

Signal

The pattern should be clear before the first click.

I translate infrastructure pressure into product clarity.

I draw the boundary before I pick the model.

I make the system legible before asking teams to scale it.

Proof path

Every project is treated as evidence of a product decision.

Amplify Engine Dashboard-shaped request. Workflow-intelligence product. AWS Bedrock / Lambda RAG / sub-second experience target / seller recommendation workflows SproutRoute Hybrid AI travel planner with facts, memory, and deterministic boundaries. Google Places / Gemini / Railway / Supabase / 350+ tests / latency redesign Sprout Math Offline-first iOS learning product where restraint is the product strategy. Native SwiftUI / local state / 2,400+ templates / 2,500+ audio clips / no accounts AI Eval Control Tower A release operating layer for quality, safety, latency, and cost. 7 models / 3 product domains / hard safety floors / decision memo workflow RAG Guardrails Grounded retrieval connected to safety checks and release logic. Dual-domain RAG / guardrails / eval traces / PASS-WARN-BLOCK release gate AI Safety Audit Tool Governance belongs in the launch review. 540-case benchmark / fairness by segment / red-team probes / explicit verdicts

Artifacts

Evidence should be easy to inspect.

The detail pages keep the same vertical language and shift into evidence rooms: shipped screens, architecture diagrams, benchmark tables, legal pages, live-tool wrappers, and repository links sit in one system.

SproutRoute screens Shipped travel flow Runtime architecture System boundaries Sprout Math worlds Offline product craft Model benchmark Safety and cost gates Safety audit Fairness launch review Legal and tools Privacy, terms, live builds

Operating model

How I work before the answer has a shape.

Name the real problem. Most first requests are approximations. I look for the product decision behind the ask.
Separate facts from generation. Models synthesize. Product systems decide, constrain, explain, and recover.
Design for day two. Adoption, latency, cost, governance, and workflow fit matter as much as launch.
Make tradeoffs inspectable. The team should know why a system behaves the way it does before scaling it.

Next action

If the role needs someone who can shape the product and stay close to the system, we should talk.

Best fit: Principal/Staff PM and AI Product Lead roles where marketplace economics, AI systems, fintech infrastructure, and 0->1 execution intersect.

hello@nitishprasad.com Resume Open SproutRoute Site archive