Anthropic released Claude Mythos Preview on April 7, 2026 - and immediately announced it won’t be publicly available. The reason? It’s too dangerous. Despite being the most powerful AI model yet, scoring double-digit improvements over competitors across nearly every benchmark, Mythos is restricted to just 12 major tech companies for defensive cybersecurity work through Project Glasswing. But before diving into why, let’s look at what makes Mythos so exceptionally capable. ...

Running AI Models Locally with Ollama: From Setup to OpenClaw Ollama has quietly become the go-to tool for developers who want to run large language models on their own machines without relying on APIs. No cloud costs, no rate limits, no sending your prompts to third-party servers. Just you, your hardware, and a surprisingly capable AI model running locally. What is Ollama? Ollama is a lightweight platform designed to make running open-source language models accessible. It handles the complexity of model management—downloading, optimization, memory management—so you just run a command and start prompting. ...

Two weeks ago, GitHub made a quiet but significant announcement: they are now an official sponsor of OpenClaw. This is not a casual endorsement. This is GitHub putting resources and weight behind what has become the fastest-growing open source project in history. The Numbers Are Staggering If you have been paying attention to GitHub trends, OpenClaw’s rise has been unlike anything the platform has ever seen. The project broke React’s 10-year GitHub record in 60 days. ...

In an era of AI-generated melodies and infinite DAW power, the physical hardware sequencer has transitioned from a niche tool to a vital mental anchor for the modern producer.

A deep dive into the shifting economics of the data landscape in 2026. Why the choice between Snowflake and Databricks is increasingly an accounting decision, and where the open-source DIY stack actually saves you money.

After six months of daily use, here is how the two heavyweights of AI-assisted coding compare: the terminal-native Claude Code and the IDE-integrated Cursor.

Copy Protection Wars: The Ingenious Schemes Of 1980s Software Before the era of always-online DRM and AI-powered anti-tamper software, the battle against software piracy was fought with cardboard, plastic, and clever manipulation of magnetic disk geometry. In the 1980s, developers faced a simple problem: floppy disks were incredibly easy to copy. Their solutions, however, were anything but simple. This was the “Copy Protection War,” an arms race between software houses and the burgeoning “cracker” scene that birthed the Demoscene and defined digital culture for a generation. ...

There is a specific sound that defines the childhood of a generation: the high-pitched screech and rhythmic thrum of a data cassette loading into an 8-bit computer. In the early 1980s, the United Kingdom underwent a transformation that was arguably more profound than the arrival of the internet a decade later. While the US was falling in love with the office-centric IBM PC and the “appliance” feel of the Apple Macintosh, the UK was building a nation of bedroom coders. ...

The automation paradox is quietly reshaping what we pay for. Every time AI gets better at a specific task—writing code, analyzing documents, generating designs—the monetary value of doing that task falls. Commodity work becomes commodified. And yet, the people who thrive are not those who do the task fastest; they’re the ones who decide whether it should be done at all. The Direction Problem In 1997, Deep Blue beat Kasparov at chess. The immediate prediction was obvious: computers will replace chess players. ...

The Shape of Engineer Burnout Creative burnout in engineering looks different than burnout in other fields. It’s not just exhaustion from long hours (though that’s part of it). It’s the specific fatigue that comes from: Infinite scope. Features that seemed scoped end up needing architecture work, documentation, refactoring, and support. The work expands to fill available time. Context switching. Ping-pong between your own work, meetings, code reviews, unplanned incidents, and people asking “quick questions” that aren’t quick. Invisible work. You spend days thinking about a problem before writing a line of code. To everyone else, you look idle. Pressure mounts. Decision fatigue. Every technical choice branches into five more questions. Should we use library A or B? Refactor or ship? Upgrade or wait? Your judgment gets spent before lunch. The expectation to be always-on. Slack notifications, on-call rotations, “can you just look at this?” messages at 6 PM. The mental boundary between work and life dissolves. This burnout doesn’t announce itself with a bang. It creeps in through a thousand small surrenders: skipping lunch, saying yes to projects you don’t have time for, staying late “just one more time,” working weekends to catch up. By the time you notice it, you’ve already lost the energy to fix it. ...