Jun 28, 2026

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.

Jun 28, 2026

OpenClaw in Your Hand: Building a Physical AI Terminal - Lech Kalinowski, Callstack

Dr. Lech Kalinowski presents Vault, a unique AI-native handheld terminal built on an ESP32-S3, featuring a dual-display (OLED for live interaction, e-paper for static content) and powered by a single battery. It operates in four modes—shell, assist, control, and an LLM-native RPG—and controls autonomous OpenClaw agents against a local, self-hosted 120B parameter GPT model served by NVIDIA TensorRT-LLM. The talk delves into the AI-native architecture, why inference remains on the backend, real-time agent thinking surfacing on e-paper, engineering challenges, and LLM-native game design, highlighting the potential for calm, text-first AI interaction.

Jun 28, 2026

Building an Autonomous Engineering Org - Angie Jones, Agentic AI Foundation

Angie Jones details Block's journey in transforming its engineering organization into an autonomous one using AI agents. She outlines a five-stage AI maturity model, the strategic implementation of an 'AI Champions' program, and the technical steps taken to make repositories AI-ready and enable seamless agent delegation directly within developer workflows. The talk covers challenges in scaling multi-agent parallelism, including code review bottlenecks and resource management, and the development of an orchestrator ('Builder Bot') and 'Company World Model' to achieve full autonomy. It concludes with a critical reflection on the ethical implications of achieving such high levels of AI-driven automation.

Jun 28, 2026

Turbocharge Your Agent's Retrieval with TurboQuant - Shashi Jagtap, Superagentic AI

This talk introduces TurboQuant, a training-free compression method from Google Research that reduces embedding memory footprint by 5x (from 32-bit to 3-4 bits) without losing search quality. It details how TurboQuant works through scalar quantization and a crucial one-bit error correction step, QJL, enabling agents to remember more on existing hardware by optimizing both KV cache and RAG vector stores. A live demo showcases its effectiveness, making it a vendor-neutral solution for efficient AI agent retrieval.

Jun 28, 2026

Using Spec-Driven Development for Production Workflows - Erik Hanchett, AWS

Erik Hanchett discusses spec-driven development (SDD) as a structured approach to building complex software features with AI coding assistants. He explains how to guide AI "interns" through distinct phases of requirements, design, and implementation, emphasizing context management, the use of "skills," and the crucial role of the human in the loop for review. Hanchett highlights AWS's Kiro tool, which automates much of this process, and the Model Context Protocol (MCP) for integrating external data sources, offering a pathway to higher-quality code and more effective AI collaboration.

Jun 28, 2026

The 100-Tool Agent Is a Trap - Sohail Shaikh & Ankush Rastogi, Prosodica

This session unveils the "Fat Agent" trap in LLM agent architectures, where loading an entire tool catalog into the system prompt causes severe latency, cost, and accuracy problems. It presents the Semantic Tool Router pattern, a practical solution leveraging Just-in-Time Context Injection and vector search (RAG for tools) to dynamically provide only relevant tools, dramatically reducing prompt size, enhancing performance, and improving reliability across frontier models like GPT-4o and Gemini 2.0.