Stack Overflow blogstackoverflow.blog · 3 September 2026

In this episode, Stack Overflow Director of Platform Engineering Peter O'Connor continues his conversation with Andi Gutmans, this time digging into what changes when you're running dozens or hundreds of agents instead of a handful of humans clicking buttons. Andi explains why he thinks the model itself is rarely the bottleneck anymore. In his view, the harder problem is figuring out the least amount of context needed to get a reliable outcome at the lowest cost, and why "token maxing" is the wrong goal entirely. He also shares how a weekend prototype changed the calculus on de-risking new ideas, and lays out what platform engineering teams need to build to treat "the agent" as a persona in its own right.The discussion also:Breaks down why cost governance matters more at agent scale, where a single employee might be responsible for dozens of agents working around the clock.Covers Google's approach to "hill climbing" model and data together, and why Andi is skeptical of vendors claiming to have solved the context problem.Explores what new tooling and observability platform teams need to bui

Michael Truell, Cursor CEOx.com · 3 September 2026

Grok Bot for enterprise is out today. We're making it free for all Grok and Cursor enterprise customers for the next two weeks. Deploying Bot has felt like onboarding thousands of capable teammates to our company. It is both the most internally adopted and most powerful AI product we've seen so far.

github.comgithub.com · 2 September 2026 · not counted as a party

Show HN: Aura – a Rust agent that investigates and fixes production incidents

r/LLMDevsreddit.com · 1 September 2026

Frank Coyle at UC Berkeley recently gave a talk called "Why Agentic Systems Need Ontologies" (YouTube ID Sir59K8ZDPU). His broader argument is neuro-symbolic: probabilistic LLM plus formal ontology reasoning as guardrail. One memorable line from the talk: "Pydantic at the door, ontology at the ledger". I've been running a lighter, schema-shape ve

Shreya Shankar, incoming CMUx.com · 31 August 2026

https://t.co/pCOIhFgZMG very nice article on the post ai data stack by @iandmacomber . h/t @debnilsur The premise is that now data analysis codegen has become free, so what next? It is getting the data agents to obtain the (1) correct and (2) consistent answers --- which is very hard when data and context is so messy and fragmented. So the job of the data team is to "encode expert judgement into the infrastructure that allows agents to produce correct analysis *without* the data scientist in the room," as Ian says all data products and UIs are going to undergo serious change. business decisions are made not by looking at a dashboard but by asking an agent what to do. on the pipelines/systems