AI Engineer

Mousepower: agents that can’t be measured, can’t be managed. — Maximillian Piras, Yutori

The Design-Code Roundtrip That Isn't — Jonathan Gordon, ReWeaver AI

The Spatial Harness: Bringing Agents to the Canvas — Max Drake, tldraw

ACP: The Universal Remote Control for AI Agents — Alex Hancock, Block

MCP Apps: Give the Model Data, Give the User a UI — Dustin Mihalik, Indeed

How long can your skills be before your agent forgets what you told it? — Laurie Voss, Arize AI

Your agents lack context: Here's how to fix "You're absolutely right!" — Brandon Waselnuk, Unblocked

500 Skills, Zero Fine-Tuning: LinkedIn's Playbook for AI Agents — Ajay Prakash, LinkedIn

It’s Tokens All The Way Down: How RLMs are Different — Kevin Madura, AlixPartners

Build-Time vs. Run-Time: Why Dev Tools Fail in Production — Averi Kitsch & Prerna Kakkar, Google

Deep dive on LLM Inference at Scale — Harshul Jain, Audible & Tanmay Sah, Independent AI Researcher

LLM inference requires balancing memory, latency, and throughput to maintain cost-effective, high-quality production services. The primary bottlenecks—memory consumption, time-to-first-token (TTFT), and inter-token latency—stem from the compute-intensive nature of transformer layers and the sequential generation of tok...

Why AI Agents Need Million-Token Context — Thomas Wolf & Olive Song, MiniMax

From coding to Knowledge work agents — Karan Vaidya, Composio

Your company brain will leak secrets: how we stopped it for big banks — Tanmai Gopal, PromptQL

Agents' next frontier: agent-to-agent and network effects — Jean-Denis Greze, Town

Tethered: Our Agents Are Us — Shu Fang, Two Sigma

Everyone Gets A Software Company — Benjamin Guo, Zo Computer

Beyond the Lethal Trifecta: Agentic Commerce on the Open Internet — David Levine, Kiduna Club

The End of the Static Screen: Architecting Intent-Driven UX — Gus Iwanaga, commercetools

Agent Spending Without Controls — Rodrigo Coelho & Pranav Maheshwari, Edge & Node