Aug 28, 2026

How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma

Figma's internal AI agent adoption journey faces challenges like reduced developer agency, skepticism from senior engineers, and communication inefficiency. Solutions include investing in verification, using a testing pyramid for agent review, prioritizing detailed planning over prompting, engaging skeptics to build AI safety roadmaps, and implementing attention-aware communication by clearly marking AI-generated content.

Aug 28, 2026

Building uReview, Uber’s Multi-Agent Code Review Engine — Will Bond & Ameya Ketkar, Uber

Uber's Will Bond and Ameya Ketkar present uReview, an in-house automated code review system developed to combat rising review times (3 to 9 hours for first review). They detail why Uber built it over buying—due to Phabricator, agentic SDLC integration, and distributed ownership—and its architecture, including comment deduplication. The presentation highlights their iterative approach using advanced observability (sentiment, addressal rate, agent trajectory) to tune model performance, acknowledging that "the model never knows that it is wrong." They discuss empowering hundreds of teams with custom review agents and skills, sharing impressive results: 25,000 comments weekly, 67% addressal rate, and 60% cost reduction. Finally, they explore the evolving role of human engineers in an agentic SDLC, predicting an "expanded outer loop" focused on architecture and domain expertise rather than direct code review.

Aug 28, 2026

Why Top Founders Are Racing Into AI Infrastructure

a16z's new Machine Age Fund addresses the unprecedented demand for AI infrastructure, shifting the bottleneck from models to the foundational hardware. The discussion highlights surging Hyperscaler CapEx, component supply crunch extending to 2028, and the exponential compute needs driven by reasoning and agents. It explores how AI turns engineering problems into capital/compute challenges, identifying opportunities for new infrastructure companies in chips, power, and data center redesign, and the emergence of experienced "systems founders" to rebuild the computing stack for this new era.

Aug 28, 2026

CLAUDE.md, AGENTS.md, Skills, Hooks and Subagents: A Field Guide to Steering AI Agents (Ep. 1022)

Episode 1022 dissects the crucial aspect of effectively steering AI agents by determining the optimal placement of instructions to ensure reliability and cost-efficiency. It explores seven distinct methods for instruction delivery, contrasting instructions as probabilities with hooks as guarantees, and highlights the industry-wide adoption of standards like `agents.md` and the importance of human-crafted guidance for superior agent performance.

Aug 27, 2026

LLM & AI Agent Benchmarks vs Reality: Why AI Applications Break

LLM leaderboard scores often don't reflect real-world performance. This video explains why and outlines a comprehensive approach to evaluate AI systems, focusing on the critical balance of accuracy, latency, and cost. It details model and system evaluation techniques, including handling different inference phases, workload shapes, and specific considerations for AI agents, emphasizing the need for realistic testing over generic benchmarks.

Aug 26, 2026

The Death of Developer Advocates — Stephanie Jarmak, Sourcegraph

Stephanie Jarmak argues that Developer Relations (DevRel) isn't dead, but its audience has shifted to include AI agents. She introduces the "Agent Advocate" role, focusing on measuring agent experience (e.g., through CodeScaleBench), optimizing for "Generative Engine Optimization" (GEO), and adapting traditional DevRel principles like enablement and community for this new user. The core message is that designing for agents, like a curb cut, ultimately improves the experience for all human developers.