Friday, June 5, 2026 · San Francisco
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AI News

Anthropic Embeds Engineers in the NSA to Deploy Mythos for Offensive Cyber

Anthropic Embeds Engineers in the NSA to Deploy Mythos for Offensive Cyber

Anthropic placed about half a dozen engineers inside the National Security Agency to deploy Mythos, its most capable cyber model, for offensive operations, the Financial Times reported. The same company is suing the Pentagon over the "supply-chain risk" label it earned by trying to keep Claude out of mass surveillance and autonomous weapons, and it calls Mythos too dangerous to release publicly. What the line it will and won't cross says about a safety-first lab racing to a $1 trillion IPO.

By Marcus Schuler · 11 min read ·
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5 Tools & Workflows
Gemma 4 12B Brings Local Multimodal AI to 16GB Laptops
AI News

Gemma 4 12B Brings Local Multimodal AI to 16GB Laptops

Google's Gemma 4 12B looks like the local AI model many developers have been waiting for: multimodal, open-weights and small enough for 16GB laptops. The hardware story is tighter than the launch line suggests. Google's own table puts 8-bit weights at 13.4GB before context overhead, while the encoder-free design shifts more work into the model itself. For teams weighing privacy, latency and cloud bills, the next proof will come from real laptop tests.

11 min read ·
Odysseus Gives Local AI Users a Safer Way to Test an Agent Workspace
Tools & Workflows

Odysseus Gives Local AI Users a Safer Way to Test an Agent Workspace

PewDiePie’s Odysseus became the rare local AI project that ordinary users noticed, with a June 2 research snapshot showing nearly 30,000 GitHub stars. The safer first step is less exciting than the launch: run it on localhost, keep authentication on, use dummy data and understand why its own security guide treats shell, email, memory and model serving as privileged tools before any mailbox, API key or home network enters the test. That is where the risk starts.

10 min read ·
A Raspberry Pi Is the Durable Way to Run OpenClaw as Labs Narrow Model Access
Tools & Workflows

A Raspberry Pi Is the Durable Way to Run OpenClaw as Labs Narrow Model Access

OpenClaw's creator just joined OpenAI, the project is moving to a foundation, and the big labs are quietly narrowing the model access it depends on. The most control-preserving way to run a personal AI assistant in 2026 is a Raspberry Pi that costs about $100 and a few watts. The catch: the Pi only runs the gateway, the intelligence stays rented, and the security liability that used to be the vendor's now sits on your shelf.

11 min read ·
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Pi, the Coding Agent Behind the Harness-Engineering Hype, Explained

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Hermes Agent Installs in One Command. The Hard Part Is Deciding What It Can Touch.

Hermes Agent is not another chatbot wrapper. It is a server-side personal agent with memory, skills, tools, cron jobs, and chat channels. Here is how it works, what hardware it needs, where OpenClaw differs, and how to test it without over-permissioning it.

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Four GitHub Tools That Stop Claude, Codex, and Gemini From Shipping Bad Code

Four open-source tools fix four different failure modes in terminal AI. Superpowers teaches the agent how to work. Context7 feeds it current docs. Serena gives it IDE-grade code navigation. ccusage tells you what the other three cost. Here is how to install them and the commands that actually matter

7 Analysis
Anthropic Candidates Spend $4,600 Coaching for a No-Code Interview
Analysis 14 min read

Anthropic Candidates Spend $4,600 Coaching for a No-Code Interview

Candidates who land Anthropic or OpenAI offers spend an average of $4,600 preparing, much of it for a round with no coding. Here is how the interview gauntlet works, from the recruiter screen to the culture round that fails most people, to the team-matching limbo that decides who gets hired.

Landing a job at Anthropic, now the world's most valuable AI startup, runs through a coaching market where candidates spend an average of $4,600 to prepare. Most of that effort points at one round that involves no coding, the culture interview, where recruiters say more strong engineers wash out than at any technical test. Here is how the full gauntlet works, from the recruiter screen to the weeks of silence at team matching, and why clearing every round still may not get you an offer.

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