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Hands-on workshops and focused webinars. Build something real, watch a production RAG stack come together, or map the AI agent path that actually ships.
Hosted by Param Harrison
18 sessions
How to draw the real architecture behind a production AI system, from ingress to eval.
The architecture patterns that stay standing when AI lands on top of your product.
Build a multi-agent system that converts natural language to SQL with guardrails and visualizations.
The path from a working notebook to a real service: extract, wrap, deploy, observe.
Reverse-engineer Claude Code and build your own AI coding agent from scratch.
The foundations, branches, and distractions on the AI engineer skill tree.
From your first SELECT to production PostgreSQL mastery with 100K+ real orders.
The reference architecture behind production RAG: query rewriting, multi-stage retrieval, rerankers, evals.
API design rebuilt for AI-first backends: streaming, idempotency, cost-based rate limits, prompt versioning.
Ship a deployed MCP server that Claude Desktop and Cursor can call against your own APIs and docs.
The habits, signals, and mistakes that separate senior engineers from juniors in production.
The portfolio projects hiring managers at AI-native companies actually read past the first line.
The architecture patterns that keep multi-agent systems shippable: supervisor, isolation, message shapes, evals.
Event-driven patterns for AI: queues, workers, idempotent consumers, cost-aware scaling, observability.
Build an agent with short-term, episodic, and semantic memory, deployed on PostgreSQL checkpointer.
Logs, metrics, traces: the observability layer that gets your first production service through on-call.
The technical leaps from mid-level to senior engineer: ambiguity, scope, depth versus shipping, system reading.
Wire Phoenix tracing and a 4-layer eval harness into an agent, with CI that blocks regressions.

Cofounder of AEOsome.com and Chief Mentor at learnwithparam.com with 15+ years building production systems. I've trained 100+ engineers on AI engineering - these programs distill what actually works into structured paths you can follow at your own pace.
Every workshop maps to an interactive course you can take anytime.
Workshops vs webinars, live vs on-demand, refunds, and how teams expense sessions.