Control plane

Harness Engineering: How to Build a Software Factory — Dru Knox, Tessl

Harness Engineering: How to Build a Software Factory — Dru Knox, Tessl

Dru Knox of Tessl discusses harness engineering, the discipline for building software factories with AI agents. He outlines a factory's three pillars—autonomy, automation, quality—and introduces inner, outer, and meta loops. Knox explains why this field is challenging and proposes a three-layer architecture: control plane, agent-ready stack, and improvement loops, concluding with key metrics to track progress towards an agent-driven software development future.

Operating Distributed Inference Systems at Scale — Nishant Gupta & Naman Ahuja, Meta

Operating Distributed Inference Systems at Scale — Nishant Gupta & Naman Ahuja, Meta

Meta's Nishant Gupta and Naman Ahuja explain how AI inference, the company's fastest-growing workload, requires a dedicated orchestration layer akin to Kubernetes for virtual machines. They detail the unique challenges of LLM serving compared to traditional microservices, emphasizing the intricate coupling of infrastructure layers, the distributed transaction nature of requests, and a seven-axis framework for scheduling. The talk concludes with the imperative to optimize for "cost per successful task" and the necessity of an inference-specific control plane to manage the complex interplay of latency, cost, and throughput.

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

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.

Platform Engineering • Ajay Chankramath & Nic Cheneweth • GOTO 2026

Platform Engineering • Ajay Chankramath & Nic Cheneweth • GOTO 2026

Ajay Chankramath and Nic Cheneweth discuss the critical elements of effective platform engineering, emphasizing a product mindset, the foundational role of control planes and API-first design, the common pitfalls of implementing Backstage, and the emerging impact of AI and agents on the platform landscape.