Your Agents Are Only As Good As Your Retrieval

Free Lesson

Your Agents Are Only As Good As Your Retrieval

Part of Context Camp

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Hosted by Atita Arora, Doug Turnbull (Maven), and Hugo Bowne Anderson

90 students

In this video

What you'll learn

Why agent failures often begin with retrieval

Trace confident agent mistakes back to the documents, tools, and evidence the system found—or failed to find.

How autonomy raises the cost of bad relevance

See why retrieval errors become more dangerous as agents take action instead of simply returning an answer.

What to evaluate before improving orchestration

Learn where to inspect retrieval quality before adding more tools, workflows, prompts, or agent complexity.

Why this topic matters

Agents can only reason over what they retrieve. As systems gain more autonomy—and MCP gives them access to more tools and sources—a weak relevance layer can turn one bad result into a confident, consequential action. Before investing in orchestration, teams need to know whether their agents are finding the right evidence in the first place.

You'll learn from

Atita Arora

Search & AI Strategist — formerly Voyager Search, Qdrant, OSC, Lucidworks

Atita Arora is an AI Search Expert with nearly 2 decades of hands-on engagements across ecommerce, health, media, finance, legal, enterprise, geospatial, and government platforms. She has held senior search and AI roles at Voyager Search, Qdrant, and OpenSource Connections, and runs an independent AI advisory and solution consulting practice.

Doug Turnbull (Maven)

Led teams at Shopify, Reddit, Wikipedia

In 2012, Doug got bit by the search bug and he's still trying to keep up. From full-text search, to Learning to Rank models, to search agents that generate their own code, he knows the endless landscape first hand. Yet Doug wants to deeply understand the what / how / why, and help teams use these technologies practically, distinguishing hype from reality.

He’s led search at Reddit, Shopify, and Wikipedia, authored Relevant Search and AI Powered Search, and advised 100+ organizations over the years - all in pursuit of the same question: how does search actually work?

Hugo Bowne Anderson

AI & data engineer, consultant, educator of 6+ million students

Hugo Bowne-Anderson is an independent data and AI consultant who has advised and taught teams building AI-powered systems, including engineers from Netflix, Meta, and Amazon. He hosts Vanishing Gradients and has written for Harvard Business Review and VentureBeat. Previously Head of Developer Relations at Outerbounds, he has also taught at Yale University, Cold Spring Harbor Laboratory, SciPy, and PyCon.

Previously At