Background
I build complex agentic systems for a living. Co-founder and CTO at Faltara, marketing AI and automation specialist at Wise, and a software engineer at my core. I ship AI that earns its complexity in production, not in demos.
My focus on learnwithparam is the part of agent engineering nobody likes to teach: auth, rate limits, observability, resilience, the dozen little decisions that turn a prototype into a service you can leave running unattended. If a topic makes a staff engineer nod knowingly, it probably belongs in my track.
I cover the patterns I actually use at work: tool design, session and tenant models, circuit breakers and fallbacks, Langfuse and Prometheus for tracing, and the deployment layer that keeps long-running agents alive. The goal is production-grade, not tutorial-grade.
What I cover
Specialty: Complex agentic systems.
- Production FastAPI + Uvicorn for long-running agent calls
- Multi-tenant user and session models for AI agents
- JWT auth, rate limiting, and input sanitization for agent APIs
- Tool design: bash, edit, search, and custom tools the model can trust
- Resilience: retries with Tenacity, fallback chains, circuit breakers
- Observability: Langfuse tracing and Prometheus metrics for agents
- Persistent memory and context window management at scale
- Stateful agents with LangGraph and checkpointed graphs
