The LGTM (Page 58)

The LGTM

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Gemini 3.1 Deep Think Is Google’s Agentic Coding Flex — But Bring Your Own Eval Harness

Google’s Gemini 3.1 update is not subtle about the audience it wants: developers choosing which model gets to touch a terminal, a repo, a browser session, and eventually production-adjacent workflow state. The DeepMind model page now presents Gemini 3.1 Pro and Gemini 3.1 Deep Think less

Codex Hooks Going GA Makes Agent Policy Programmable — and Also Reviewable

Codex Hooks Going GA Makes Agent Policy Programmable — and Also Reviewable

Hooks are the kind of feature that rarely wins a launch-day popularity contest and then quietly becomes the thing enterprises cannot deploy without. OpenAI’s Codex Hooks going generally available is not glamorous. It is also one of the more important Codex platform moves this week, because it gives teams

OpenClaw 2026.5.12-beta.8 Is Shrinking the Core and Hardening the Edges

OpenClaw 2026.5.12-beta.8 Is Shrinking the Core and Hardening the Edges

OpenClaw’s newest beta is not trying to win the release-notes beauty contest. Good. The interesting work in v2026.5.12-beta.8 is mostly the kind of platform plumbing people notice only after it fails: dependency boundaries, fallback boundaries, inbound queue boundaries, credential boundaries, and sandbox roots. That is the

A 100B-Class NVFP4 Quant on 2× DGX Spark Is the Most Useful Kind of Messy Benchmark

A 100B-Class NVFP4 Quant on 2× DGX Spark Is the Most Useful Kind of Messy Benchmark

The most useful benchmark posts are usually the messy ones. A fresh NVIDIA Developer Forum thread on quantizing a 100B-class Llama-derived model to NVFP4 across two DGX Spark systems is valuable because it does not sand off the parts operators actually trip over: unified-memory misdetection, exporter quirks, vLLM sidecar fixes,

The Best Local Coding-Agent Post Today Says the Quiet Part: The Model Is a Worker, Not the Authority

The best local coding-agent post today does not ask whether Qwen 3.6 is smart enough to write code. It asks the more useful question: what should the model be allowed to decide? Manolo Remiddi’s writeup on building a local coding-agent setup with Qwen 3.6, OpenCode, Hermes, and

Hermes on DGX Spark Shows Local Agents Are Becoming a Hardware Product — With a Reliability Bill Attached

Hermes on DGX Spark Shows Local Agents Are Becoming a Hardware Product — With a Reliability Bill Attached

NVIDIA’s latest RTX AI Garage post is not really about one more agent framework. It is about local agents becoming a hardware product. Hermes Agent, Qwen 3.6, RTX PCs, RTX PRO workstations, and DGX Spark are being bundled into a single story: keep the agent near your files,