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6 live sessions · 6 office hours · 1 demo day · 20+ hours
⚡ Agent Harness Design: Build a observable perceive–think–act loop in Python with structured tracing, evolving from simple LLM calls to full agent systems with tools, reflection, and planning
⚡ Agentic RAG Systems: Create advanced RAG pipelines with routing, multi-hop reasoning, Knowledge Graph, and semantic caching to improve accuracy and efficiency
⚡ Real-Time Voice Agents: Engineer a streaming STT → LLM → TTS pipeline with turn-taking, interruptions, and sub-second latency across modern voice platforms
⚡ Multi-Agent Orchestration: Design coordinated agent systems using MCP and A2A with patterns like hierarchical, debate, and orchestrator-worker workflows
⚡ Guardrails & Evaluation: Build reliable systems with safety guardrails and trajectory-based evaluation using LLM-as-judge and validated benchmark tasks
⚡ Production Deployment: Ship multi-agent systems with Google ADK, MCP, A2A, Llama Guard, and GCP monitoring
👉 This bootcamp is for engineers who ship real agent systems
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The agentic world challenges traditional ways of building search. Traditionally we've built thick, complex search APIs - query understanding, rerankers, learning to rank, vector databases. Yet an agent can compete in deep research benchmarks with the dumbest of search tools.
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Guiding agents, not algorithms - Search developers won't train algorithms. They'll build harnesses
Steering with an LLM judge - Integrate human and clickstream feedback to guide the agent's judgment towards what users want
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Most search systems barely scratch the surface of what's possible. While others struggle with irrelevant results and frustrated users, you'll master the cutting-edge techniques that power the world's most successful search experiences—from Reddit and Spotify to the Fortune 500.
Why This Course Exists
The Problem: Many traditional search systems are stuck in the 2010s. But modern AI courses hyper focus on text embeddings and ignore many of the fundamentals of information retrieval. The result? Engineers who can't bridge the gap between amazing demos and production systems that actually work.
Our Solution: Stop downloading random embeddings from Hugging Face or OpenAI and hoping for the best. Learn to systematically analyze your users' actual intent, integrate domain context, and build search that truly understands what people (and agents) need—not just what they type.
This course helps you build cutting-edge AI Search systems that actually work.
Ready to level-up your AI Search skills?
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