Speaker Series¶

2025/09/11
in Speaker Series, RAG
6 min read

What Is the Coding Agents Speaker Series?

I hosted a series of conversations with the teams behind the most successful coding agents in the industry—Cognition (Devin), Sourcegraph (Amp), Cline, and Augment. Coding agents are the most economically viable agents today—they're generating real revenue, being used daily by professional developers, and solving actual business problems at scale.

This makes them incredibly important to study. While other agent applications remain largely experimental, coding agents have crossed the chasm into production use. The patterns and principles these teams discovered aren't just theoretical—they're battle-tested insights from systems processing millions of real-world tasks.

This series captures those hard-won lessons, revealing what works and what doesn't when building agents that actually deliver economic value.

Related Series

Context Engineering Series: Technical implementation patterns for agentic RAG systems, including tool response design, context management, and system architecture. This Speaker Series provides strategic insights, while Context Engineering offers implementation details.

RAG Master Series: Comprehensive guide to retrieval-augmented generation systems. Many coding agent insights (like why simple approaches beat complex ones) apply directly to RAG system design and optimization.

2025/09/11
in Speaker Series, RAG
10 min read

Domain Experts: The Lever for Vertical AI — Chris Lovejoy (Anterior)

I hosted a session featuring Chris Lovejoy, Head of Clinical AI at Anterior, who shared valuable insights from his experience building AI agents for specialized industries. Chris brings a unique perspective as a former medical doctor who transitioned to AI, working across healthcare, education, recruiting, and retail sectors.

2025/09/11
in Speaker Series, RAG
5 min read

Text Chunking - Anton (ChromaDB)

I hosted a special session with Anton from ChromaDB to discuss their latest technical research on text chunking for RAG applications. This session covers the fundamentals of chunking strategies, evaluation methods, and practical tips for improving retrieval performance in your AI systems.

2025/09/11
in Speaker Series, RAG, Coding Agent Series
8 min read

Why Grep Beat Embeddings in Our SWE-Bench Agent (Lessons from Augment)

I hosted Colin Flaherty, previously a founding engineer at Augment and co-author of Meta's Cicero AI, to discuss autonomous coding agents and retrieval systems. This session explores how agentic approaches are transforming traditional RAG systems, what we can learn from state-of-the-art coding agents, and how these insights might apply to other domains.

2025/09/11
in Speaker Series, RAG, Coding Agent Series
13 min read

Why Cognition does not use multi-agent systems

I hosted a session with Walden Yan, co-founder and CPO of Cognition, to explore why multi-agent systems might not be the optimal approach for coding contexts. We discussed the theory of context engineering, the challenges of context passing between agents, and how single agents with proper context management can often outperform multi-agent setups.

2025/09/11
in Speaker Series, RAG
10 min read

Stop Trusting MTEB Rankings (Kelly Hong, Chroma)

I hosted a session with Kelly Hong from Chroma, who presented her research on generative benchmarking for retrieval systems. She explained how to create custom evaluation sets from your own data to better test embedding models and retrieval pipelines, addressing the limitations of standard benchmarks like MTEB.

2025/09/11
in Speaker Series, RAG
10 min read

How Extend Achieves 95%+ Document Automation (Lessons from Eli Badgio)

I hosted a special session with Eli Badgio, CTO of Extend, to discuss AI-native document processing in the cloud. Extend helps companies achieve 95%+ extraction accuracy for customers like Brex and other Fortune 500s. This session covered mapping document workflows, building task-specific evaluations, and implementing partial automation with human-in-the-loop approaches.

2025/09/11
in Speaker Series, RAG
12 min read

The 12% RAG Performance Boost You're Missing (Ayush, LanceDB)

I hosted a session with Ayush, an ML Engineer at LanceDB, to explore how fine-tuning re-rankers and embedding models can significantly improve retrieval performance in RAG systems. We discussed practical approaches to enhancing retrieval quality, the trade-offs involved, and when these techniques make the most business sense.

2025/09/11
in Speaker Series, RAG
7 min read

Why Glean Builds Custom Embedding Models for Every Customer

I hosted Manav from Glean for a guest lecture on enterprise search and fine-tuning embedding models. This session revealed a surprisingly underutilized approach that can dramatically improve RAG system performance - building custom embedding models for each customer rather than using generic solutions.

2025/09/11
in Speaker Series, RAG
5 min read

Lexical Search - John Berryman

I hosted a session featuring John Berryman, who shared his expertise on lexical search and its application in RAG systems. John, who previously worked at GitHub and co-authored books on prompt engineering and information retrieval, provided valuable insights on how traditional search techniques can complement modern vector-based approaches for more effective retrieval augmented generation.