Developer tools

We Cut 94% of AI Coding Tokens With a Local Code Index - Rajkumar Sakthivel, Tesco

We Cut 94% of AI Coding Tokens With a Local Code Index - Rajkumar Sakthivel, Tesco

Rajkumar Sakthivel details how an unexpected surge in AI coding tool costs led to the discovery that sending excessive, irrelevant context was the primary culprit. He introduces the Code Context Engine (CCE), a local retrieval layer that intelligently prunes context using AST-aware chunks, hybrid search, and relevance scoring, resulting in up to 94% token reduction and significant cost savings. The talk emphasizes that optimizing input context, not just the AI model, is paramount for efficient and accurate AI-assisted coding.

Turn 10,994 Notes Into Memory - Paul Iusztin, Decoding AI & Louis-François Bouchard, Towards AI

Turn 10,994 Notes Into Memory - Paul Iusztin, Decoding AI & Louis-François Bouchard, Towards AI

Paul Iusztin and Louis-Francois Bouchard unveil their AI Research OS, a powerful system that transforms notes, documents, videos, and code repositories into a dynamic, personalized memory for AI agents. They detail a three-layered architecture (raw files, index, wiki) that efficiently manages context and enables continuous learning and evolution, addressing the limitations of static research and generic AI tools.

Building Agent Interfaces: Lessons from Chrome DevTools (MCP) for Agents — Michael Hablich, Google

Building Agent Interfaces: Lessons from Chrome DevTools (MCP) for Agents — Michael Hablich, Google

Michael Hablich from the Chrome DevTools team shares hard-won engineering lessons on building effective and secure interfaces for AI agents. The talk covers moving from raw data to semantic summaries, measuring interface efficiency with 'tokens per successful outcome', designing for error recovery, and the critical importance of trust boundaries and deliberate friction in UI design for agents.

How Google DeepMind Runs Agents at Scale — KP Sawhney & Ian Ballantyne, Google DeepMind

How Google DeepMind Runs Agents at Scale — KP Sawhney & Ian Ballantyne, Google DeepMind

KP Sawhney from Google DeepMind discusses the internal strategies for scaling agentic AI, including managing token-hungry workflows, curating a 'Darwinian' skills library, and evolving the Deep Research pipeline from large context blobs to a collaborative file system.

The Missing Primitive for Agent Swarms — Lou Bichard, Ona

The Missing Primitive for Agent Swarms — Lou Bichard, Ona

The talk argues that while agent runtimes and orchestration are solved problems, the crucial missing piece for building scalable 'software factories' is a dedicated coordination layer. Current tools like GitHub are inadequate, and a new primitive, potentially a CLI gateway, is needed for agents to manage tasks, pass messages, and navigate the software development lifecycle.

From Zapier for Devs to Powering 90% AI Agents

From Zapier for Devs to Powering 90% AI Agents

Co-founders of Trigger.dev discuss their journey through three product versions to find product-market fit, how their async infrastructure positioned them perfectly for the AI agent era, and their vision for the future of computing: programmatic checkpoint and restore.