Technical guides, research notes, and operator dispatches on AI agents, model infrastructure, and secure deployment.
Google dropped Gemini 3.1 Flash-Lite into General Availability the week before I/O, targeting sub-second latency at roughly a third of the cost of GPT-4o Mini. That's not a product launch — it's a price war signal aimed directly at the inference economics that OpenAI has been building on.
MCP (Model Context Protocol) is the plumbing that separates a demo AI from a production one. This is the practical guide to setting up your first MCP server connection and getting your AI to actually do things.
Every vendor is bragging about their million-token context window. Nobody is asking the right question: why are you stuffing your entire codebase into a prompt and calling it reasoning?
While most developers were arguing about which model to use, a quiet team at LMSYS was building the serving layer that makes those models actually usable at scale. SGLang has become the infrastructure backbone for serious LLM deployments—and if you're not running it, you're probably leaving performance on the table.
Google confirmed it this week — a criminal group used an LLM to identify and exploit a zero-day vulnerability. That's not a thought experiment anymore. That's a live incident. And the security industry is woefully unprepared for what comes next.
Zhipu AI's GLM-5.1 just became the first open-source model to match proprietary coding benchmarks — 744 billion parameters, 8-hour autonomous execution, and a SWE-Bench Pro score that puts it in the same conversation as Claude Opus 4.7. Here's what actually changes.
Show me a production-ready agentic system that isn't held together with brittle prompts, hallucinated tool calls, and prayer. Because I've looked. They don't exist yet.
Skip the API bills and latency. Here's how to run a capable open-source LLM entirely on your own hardware using LM Studio — and integrate it into your agentic workflows.
A comprehensive 2500+ word guide to building autonomous AI agents with Google Antigravity. Covers the RAPS framework, Agent Manager, multi-agent teams, and a complete code review workflow.
Anthropic's latest flagship tops SWE-bench at 87.6%, ships a 1M token context window, and rewrites what agentic coding looks like at scale.
OpenAI's latest tops Terminal-Bench by 13 percentage points over Opus 4.7, but the real story is what research-focused reasoning means for knowledge work.
Everyone's watching GPT-5.5 and Opus 4.7, but the model enterprises are actually deploying at scale is Gemini 3.1 Pro — and here's why the Google ecosystem advantage is structural.
Most AI agents reset after every session. Hermes Agent doesn't — and that changes everything about long-running development work.
Most AI agents are chatbots with delusions of grandeur. OpenClaw is something different: an operating system for AI that actually does things. Here's why the comparison matters.
Skills aren't prompts. They aren't agents. They're something better — bounded, purposeful capabilities that make AI actually useful. Here's what changed when I started thinking in skills.
On May 10th, an open-source agent called Hermes processed 224 billion tokens in 24 hours and overtook OpenClaw — not because it was smarter, but because it remembered. This is the part of the agent story that nobody in the mainstream press is covering correctly.
In the last 48 hours Microsoft shipped Microsoft Execution Containers at Build 2026 and NVIDIA shipped the Vera CPU plus Nemotron 3 Ultra plus NemoClaw at Computex 2026. Together they mark the moment the agent stack stopped being an application pattern and started being an operating-system pattern. The platform vendors just declared war on the agent-framework layer. Most of the agent-framework companies have not noticed yet.
OpenAI confidentially submitted its draft S-1 to the SEC on June 8, 2026, a week after Anthropic did the same and a month after SpaceX. Reuters reports a $1T valuation target, with a public offering as early as September. The story is not 'AI is going public.' The story is that every agent build-vs-buy decision for the next eighteen months just got repriced, the closed API tier is now a public-equity bet, and the open-weights stack is no longer the alternative — it is the only rational hedge.
Claude Fable 5's government-forced blackout, open-weight models closing the capability gap, AI search rewriting SEO, the enterprise deployment paradox, a price war nobody is winning, and the quiet data that should be driving your roadmap.
seo-auditor — Claude-Code skill on mr.technology. Audit verdict: PENDING.
monorepo-navigator — Claude-Code skill on mr.technology. Audit verdict: PENDING.
changelog-generator — Claude-Code skill on mr.technology. Audit verdict: PENDING.
tech-debt-tracker — Claude-Code skill on mr.technology. Audit verdict: PENDING.
runbook-generator — Claude-Code skill on mr.technology. Audit verdict: PENDING.