The world's AI leaders converged on Davos this week with a stark message: the disruption window is closing faster than anyone expected. Meanwhile, we're getting unprecedented transparency into how AI systems actually work—and new approaches to making them more human-centered.

AI'S CONSTITUTIONAL MOMENT

Anthropic just made history by releasing Claude's full "constitution"—the thirty-five thousand token document that guides the model's core values and behavior. This isn't just a system prompt. It's baked into Claude's training itself.

The story started when researcher Richard Weiss discovered he could coax Claude Opus four-point-five into revealing what he called a "soul document." Amanda Askell from Anthropic quickly confirmed its authenticity. Now it's public domain.

Here's what's fascinating: the acknowledgments reveal fifteen external contributors who helped shape Claude's values. Two are Catholic clergy—Father Brendan McGuire, a pastor with computer science credentials, and Bishop Paul Tighe, who specializes in moral theology.

This represents unprecedented transparency in AI development. We're seeing the actual ethical framework that shapes billions of conversations. It's over ten times longer than Claude's published system prompt—showing just how much thought goes into AI alignment at the constitutional level.

DAVOS DELIVERS DISRUPTION TIMELINE

The World Economic Forum became ground zero for AI reality checks this week. Dario Amodei from Anthropic, Demis Hassabis from Google DeepMind, and Satya Nadella from Microsoft painted a picture of accelerating change.

Amodei dropped the most concrete timeline: we may be just six to twelve months away from AI models that handle "most, maybe all" of what software engineers do end-to-end. That's not theoretical—that's based on current progress trajectories.

Hassabis expects AI-driven slowdowns in junior hiring this year. But he argues AI tools could ultimately create more skill-building paths than traditional education. Meanwhile, Nadella warned that companies can't "just coast" anymore—big organizations that don't adapt will "get schooled by someone small."

The geopolitical tensions are real too. Amodei criticized recent U.S. policy allowing AI chip sales to China, comparing it to "selling nuclear weapons to North Korea." The stakes couldn't be higher.

THE HUMAN-CENTRIC COUNTER-MOVEMENT

Not everyone's racing toward full automation. A new startup called Humans& just raised four hundred eighty million dollars in seed funding—at a four-point-four-eight billion dollar valuation after just three months.

The company emerged from researchers who left Anthropic, xAI, and Google specifically to build AI that enhances human collaboration rather than replacing it. Co-founder Andi Peng left Anthropic over what she saw as excessive focus on autonomy—models that "churned for eight, twenty-four, fifty hours by themselves."

Their vision? AI that works like an intelligent group chat—requesting context, storing memory, and coordinating teams. The founding team includes Google's seventh employee, Georges Harik, plus former xAI researchers who worked on Grok.

That valuation shows massive investor appetite for any team with frontier lab credentials. But it also signals growing interest in human-AI collaboration over pure automation.

TECHNICAL BREAKTHROUGHS ACCELERATING

The pace of capability advances keeps surprising everyone. Lightricks just launched audio-to-video generation—where you start with voice, music, or sound effects and generate matching video. The model understands rhythm and beat, syncing motion and lip movements directly to uploaded audio.

Meanwhile, Liquid AI released a reasoning model small enough to run on smartphones while matching larger rivals on math benchmarks. And Node.js creator Ryan Dahl declared the era of humans writing code syntax directly is over—though software engineering work continues.

The message from Davos is clear: whether you're building human-centric AI or pushing toward full automation, the transformation is happening faster than expected. The question isn't whether disruption is coming—it's whether organizations can adapt quickly enough to survive it.