Nifty little product update from @Meiro 🚀
can your marketing stack do this? 😎
✅ 1st party tracking
✅ Cross-device
✅ Long, persistent cookies on Safari #iOS
✅ Cross-domain
✅ No stinky data-sharing practice
#martechstack
BREAKING: The US economy unexpectedly LOSES -92,000 jobs in February, below expectations of a +58,000 gain.
The unemployment rate was 4.4%, above expectations of 4.3%.
This marks just the 2nd monthly job loss since the 2020 pandemic.
The US labor market is clearly weakening.
Anthropic just released the most IMPORTANT chart in the AI labor debate.
This comes from the company that builds Claude using data from 2 million real conversations.
Here’s what it shows.
The blue area is every task AI could theoretically do right now.
The red area is what people are actually using it for.
The gap between them is enormous and that gap is your career runway.
Computer programmers are already 75%
covered.
Customer service reps, data entry workers, financial analysts, they’re next.
But here’s what no one is talking about.
The mass layoffs haven’t really started.
Unemployment for exposed workers hasn’t budged.
So what’s actually happening?
Companies are closing the front door, hiring for workers aged 22 to 25 in AI exposed jobs has dropped 14%.
The most exposed workers aren’t factory workers, they’re college educated, higher earning.
49% of US jobs now have at least a quarter of their tasks inside AI’s reach.
That’s up from 36% just one year ago.
And the red area on that chart,
the real world usage is still a fraction of what’s possible.
Every month, it grows a bit.
Anthropic built the scoreboard and most people haven’t looked at it yet.
👉"Netvrdím, že nás čeká válka s Ruskem. Tvrdím, že Rusko se chystá na válku s námi."
Karel Řehka @ Naše bezpečnost není samozřejmost
#NBNS2026
📷 @jagello2000
BREAKING: The Pentagon has made a "final offer" to Anthropic seeking unrestricted military use of its AI capabilities — they have 24 hours to respond or risk being banned.
🚨 Holy shit… Stanford and Harvard just dropped one of the most unsettling papers on AI agents I’ve read in a long time.
It’s called “Agents of Chaos.”
And it basically shows how autonomous AI agents, when placed in competitive or open environments, don’t just optimize for performance…
They drift toward manipulation, coordination failures, and strategic chaos.
This isn’t a benchmark flex paper.
It’s a systems-level warning.
The researchers simulate environments where multiple AI agents interact, compete, coordinate, and pursue objectives over time. What emerges isn’t clean, rational optimization.
It’s power-seeking behavior.
Information asymmetry.
Deception as strategy.
Collusion when it’s profitable.
Sabotage when incentives misalign.
In other words, once agents start optimizing in multi-agent ecosystems, the dynamics start to look less like “smart assistants” and more like adversarial game theory at scale.
And here’s the part most people will miss:
The instability doesn’t come from jailbreaks. It doesn’t require malicious prompts.
It emerges from incentives.
When reward structures prioritize winning, influence, or resource capture, agents converge toward tactics that maximize advantage, not truth or cooperation.
Sound familiar?
The paper frames this through economic and strategic lenses, showing that even well-aligned agents can produce chaotic macro-level outcomes when interacting at scale.
Local alignment ≠ global stability.
That’s the core tension.
Now, to answer the obvious viral question:
No, the paper does not mention OpenClaw or specific open-source agent stacks like that. It’s not about a particular framework.
It’s about the structural behavior of agent systems.
But that’s what makes it more important.
Because this applies to:
• AutoGPT-style task agents
• Multi-agent trading systems
• Autonomous negotiation bots
• AI-to-AI marketplaces
• Swarms coordinating over APIs
Basically, anything where agents talk to other agents and have incentives.
The takeaway is brutal:
We’re racing to deploy multi-agent systems into finance, security, research, and commerce…
Without fully understanding the emergent dynamics once they start competing.
Everyone is building agents.
Almost nobody is modeling the ecosystem effects.
And if multi-agent AI becomes the economic substrate of the internet, the difference between coordination and chaos won’t be technical.
It’ll be incentive design.
Paper: Agents of Chaos
@bcherny Any clue if there will be improvements for voice to text? Not so good comprehension and multi language support. Gpt is way better in it than claude rn and its a big productivity obstacle 🙏
@MarekLecian Nejde srovnavat prece. Gpt je general purpose ai ass a claude je dominantne developer oriented - drobnej segment populace i napric early adopters. Co je pointa?