Product-minded engineeringArchitecture decisions tied to user and business outcomes

Cross-stack executionMobile, backend, data and AI without unnecessary handoffs

Practical communicationClear trade-offs, progress and implementation details

For businesses

Ways I can help your product team

Useful when you need execution, technical ownership or an extra engineering hand without building a large team around one problem.

Mobile product development

Android, Kotlin, Jetpack Compose and React Native work across new features, architecture, background services, notifications, performance and release readiness.

Good for: product features · rewrites · production fixes

Backend & API engineering

Python services with FastAPI, Django and Flask, including REST APIs, authentication, databases, queues, real-time systems and deployment-oriented architecture.

Good for: APIs · dashboards · internal platforms · integrations

AI product integration

Turn AI from a demo into a usable feature with RAG, agents, MCP, structured tools, model APIs, prompt flows, search and cost-aware backend integration.

Good for: copilots · assistants · workflow automation

System design & rescue work

Review bottlenecks, unstable flows and scaling problems, then improve architecture with pragmatic changes instead of unnecessary rewrites.

Good for: performance · reliability · technical debt

Applied engineering

Problems I work on in real products

The site is not only a blog. Much of the material comes from implementation work involving mobile apps, backend systems, audio intelligence, databases, AI features and production debugging.

Mobile + background systems

Reliable Android background execution

Foreground services, application lifecycle, background listening, notifications and production behavior under app kills and OS constraints.

Audio intelligence

Music recognition & analysis pipelines

Recognition providers, metadata normalization, audio-feature extraction, backend orchestration and mobile integration.

See technical comparison →

Backend + scale

APIs, real-time systems and large datasets

FastAPI/Django services, WebSockets, PostgreSQL/Supabase, search, authentication and production-oriented data flows.

AI engineering

Agents, RAG and MCP

Agent loops, tool calling, orchestration, MCP servers and clients, observability, security and production trade-offs.

Explore the AI + MCP course →

Engagement model

Bring me a business problem, not a perfectly written specification.

I can help turn an unclear requirement into an implementation plan, identify the riskiest technical assumptions, build the feature and document the trade-offs.

Understand

Clarify the user flow, constraints, existing system and the outcome that matters.

De-risk

Prototype or inspect the risky parts first: APIs, background behavior, scale, AI quality or third-party dependencies.

Build

Implement in the existing stack where possible, with maintainable interfaces and practical observability.

Ship

Validate production behavior, edge cases and handoff details instead of stopping at a happy-path demo.

Technical authority

Focused technical content for engineers and technical buyers

The learning library now concentrates on AI agents, MCP, Python backend engineering, system design and applied product work—the areas I want to develop and publish deeply.

Tell me what you are trying to build or fix.

You do not need a polished scope. Share the product problem, current stack and what is blocking you. I can help you think through the technical path.

Email me about your project Review my technical work

I build mobile, backend and AI systems that are ready for real users.

Teams that need someone who can own a technical problem end-to-end.