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 22, 2026

The Agent Behind the Curtain: Building the Oz Cloud Agent Platform — Safia Abdalla, Warp

Safia Abdalla discusses Warp's cloud agent platform, emphasizing its core principle of absorbing complexity from the user. She details features like flexible sandboxes, multi-harness support, and API-driven agent orchestration. The talk highlights how agents manage Warp's open-source repository—from issue triage to PR review—and introduces the "potter's workshop" analogy as a superior model to the "software factory" for modern, human-centric software development.

Aug 22, 2026

FinOps for AI Agents: Who Spent All the Tokens? — Tisha Chawla & Susheem Koul, Microsoft

TokenOps introduces a novel control plane for managing AI agent costs, shifting from simple throttling to proactive steering. By integrating an out-of-band system that annotates agent methods and provides a policy-driven governor, TokenOps can dynamically modify agent behavior—like making outputs more succinct—to reduce token consumption and prevent runaway loops. This approach significantly cuts average spend (78%) and dramatically improves run completion rates (from 67% to 96%) compared to traditional halting mechanisms, offering granular, attributable cost control for the agentic era.

Aug 22, 2026

Give the Agent a Budget, Not a Token — Sachin Malhotra, Anthropic

Sachin Malhotra's talk outlines a critical framework for safely deploying autonomous agents in production, moving beyond simple token-based access. He introduces 'asymmetric verbs,' refilling 'rate limits,' 'trip wires' for aggregate monitoring, and the 'undo test' as a lens. A central tenet is that infrastructure (via a proxy) must stamp an agent's identity, preventing agents from circumventing controls and ensuring accountability, thus providing a "budget" instead of an unbounded "token."

Aug 21, 2026

Building Agents Is Trivial Now, Context Is the Next Frontier — Jeff Ng, Unblocked

Building AI agents is now easier than ever, but they frequently make confident yet incorrect decisions. This is because agents often lack critical context that humans provide, such as historical discussions, postmortems, and tribal knowledge. The solution proposed is a 'context engine' that synthesizes and grounds information from across an organization's documents, code, tickets, and conversations, providing agents with a holistic and reconciled view, thus bridging the 'context gap' that current LLMs often miss.

Aug 19, 2026

MCPs for Observability Stacks

Diana Todea, Head of Developer Relations at VictoriaMetrics, demonstrates how Model-Controller-Pair (MCP) servers enhance observability stacks for faster, smarter troubleshooting. She highlights the use of AI-driven anomaly detection, natural language querying, and customizable "skills" to investigate production issues, manage metrics, and generate alerts, showcasing practical applications with two interconnected MCP servers.