AAIF Community

One user request can trigger dozens of API calls. Agent traffic is bursty, unpredictable, and challenging to price. Erica Hughberg and @Dpbrinkm discuss API gateways, Kubernetes limits, and Google's Agent Substrate.

AI coding agents can diagnose bugs without producing maintainable code. Dexter Horthy of HumanLayer discusses software factories, background-agent infrastructure, and the operational work behind running agents at scale.

AI infrastructure is hitting physical limits: power, cooling, rack density, and hardware supply chains. Zachary Smith of Datum discusses the constraints and how data centers could reuse waste heat.

AI infrastructure is hitting physical limits: power, cooling, rack density, and hardware supply chains. Zachary Smith of Datum discusses the constraints and how data centers could reuse waste heat.

An AI agent recommended hiring another engineer. Applying the Google SRE handbook’s lens on operational toil changed the answer. Tim O’Reilly on domain expertise, context engineering, and building more reliable agents.

AI-generated code needs verification before it reaches a PR. Erica Hughberg and @Dpbrinkm discuss QA sub-agents, workflow-based tests, and using screenshots to catch broken behavior before human review.

AI coding ROI isn't measured in lines of code. Pepijn Senders shares how to track token spend against product value and why accepting code you don't understand can create risks in production.

AI agents can test thousands of attack paths in parallel. A small network vulnerability in a supposedly isolated sandbox can become an escape route. Erica Hughberg and @Dpbrinkm discuss agent security and bots with buying power.

Browser agents scraping DOMs and screenshots are slow, token-intensive, and unpredictable. Sarah Drasner of @Google explains how WebMCP exposes defined actions, flags consequential operations, and helps developers guide agents safely.

Can a narrowly scoped agent outperform a general-purpose setup? Justin Schroeder, co-founder of Standard Agents, explains how prompts, tools, models, and runtimes shape agent effectiveness - and why standards matter for sharing reliable agents.