Context engineering

Aug 17, 2026

Context Engineering in 2026 — Louis-François Bouchard, Omar Solano & Samridhi Vaid, Towards AI

Experiments with an AI tutor reveal that not compacting context often outperforms summarization, leading to better recall, lower cost, and faster responses, primarily due to LLM API prompt caching. Compaction invalidates the cache, making it unexpectedly expensive. While cloud environments benefit from full history, local hardware limits necessitate compaction, highlighting the need to prioritize actual constraints over default compaction strategies.

Jul 30, 2026

Jeff Dean: The 1% Rule for Building in AI

Jeff Dean discusses the evolution of AI, drawing parallels between Google's past breakthroughs (like fitting search in RAM and the origin of TPUs) and current challenges. He emphasizes that AI is becoming an energy problem, driving the need for specialized inference hardware. Dean highlights 'context engineering' and multi-agent systems as crucial for long-running, complex AI tasks, and offers advice for startups on finding niches where they can outperform larger entities by focusing on specific domains, data, and models. He stresses the importance of clear specifications for agents and 'taste' in problem selection, encouraging founders to question fundamental assumptions and automate the scientific method to build 'AI that builds AI.'

Jul 17, 2026

On AI and Knowledge — Pablo Castro, Distinguished Engineer & CVP for AI Knowledge, Microsoft

Pablo Castro explores the three pillars of AI knowledge—intrinsic, extrinsic, and learned—explaining how models leverage parametric memory, agents integrate with enterprise data through sophisticated RAG systems like Foundry IQ, and how continuous learning loops, facilitated by tools like the Agent Optimizer, enable self-improving agents, driving the next wave of AI applications.

Jul 17, 2026

Closing Keynote: Garry Tan, Y Combinator

Garry Tan, President of Y Combinator, details how AI-native companies are achieving unprecedented productivity and scale with lean teams. He introduces the concept of "wiring the work" by treating AI as a workforce where organizational components are encoded into markdown "skill files." Tan explains how "company brains" act as a library and librarian, managing institutional knowledge to overcome human memory limits. He emphasizes the discipline of "skillifying" every task to ensure continuous learning and calls on founders to build these new AI-native infrastructures to "boil the ocean"—tackling previously insurmountable problems.

Jun 09, 2026

[404] – Developer Not Found: The Continuing Developer Evolution • Derek Bingham • YOW! 2025

Derek Bingham explores the rapid evolution of developer tools with AI, from coding assistants to autonomous agents. He emphasizes the shift from prompt engineering to context engineering, introduces Spec-Driven Development (SDD) as a framework for quality AI-generated code, and dispels fears about AI replacing developers, arguing instead for increased demand and the necessity of new skills like ethical and systems thinking.

May 08, 2026

Agentic Search for Context Engineering — Leonie Monigatti, Elastic

Leonie Monigatti from Elastic provides a practical guide to agentic search, arguing that effective context engineering is not just a retrieval problem, but a search problem. The workshop explores the trade-offs between specialized tools (like semantic search) and general-purpose tools (like shell and SQL execution), offering a "low floor, high ceiling" framework for building a robust and efficient retrieval stack for AI agents.