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Global AI market size — Grand View Research
Have adopted AI in at least one function — McKinsey
Annual value AI could add — McKinsey Global Institute
One real distribution or SEO trick per day. Stolen from products that grew without a marketing team.
A step-by-step guide for running Claude Code unsupervised on a spare Mac reached 152 points and 109 comments on Hacker News — on a technical, skeptical audience — by naming the exact risk of its own setup instead of selling a vision of AI agents.
AWS's billing tool told customers they owed billions of dollars they didn't owe, and a Hacker News thread about it hit 963 points and 611 comments. AWS's fastest visible move toward calming that panic wasn't a detailed technical explanation — it was one flat sentence on the status page saying the numbers weren't real.
Kimi K3 didn't try to win on being the cheapest option or claim to beat the frontier labs outright. It priced near the market rate and let its own benchmark sheet openly admit where it falls short -- and that honesty is what made the comparison to the frontier labs credible in the first place.
Every day, one trending AI idea turned into a step-by-step money-making guide.
The guide walks through isolating Claude Code on a spare Mac, run with "the `--dangerously-skip-permissions` flag on," so it can act unsupervised without touching your main machine. The author's own words: "Claude Code, especially with the `--dangerously-skip-permissions` flag on, carries inherent risk when run on your main machine." Commenters weren't debating the isolation setup — they were debating whether anyone should trust an agent they can't watch. That trust gap, not the setup itself, is the sellable service.
AWS's own "billing computation subsystem" — the tool customers are supposed to trust to know what they owe — started showing some accounts billions of dollars in charges that, per Amazon's own status page, "do not reflect actual usage and charges." One customer's estimate reportedly hit around $2.5 billion. HN commenters reported a budget alert crossing an "$18 threshold" that read "78 million," and one enterprise account reportedly showed "-3trillion and change." When the vendor's own dashboard can't be trusted, verifying what you actually owe — independently of that dashboard — becomes a sellable service.
Kimi K3 publishes a clean rate card -- "$0.30" per million cache-hit input tokens, "$3.00" cache-miss, "$15.00" output -- and strong scores at "max reasoning effort" (GPQA-Diamond "93.5", Terminal Bench 2.1 "88.3"). But a 2.8-trillion-parameter model that activates 16 of 896 experts and runs in a reasoning mode can burn wildly different token counts per task depending on the prompt. The headline $/M rate tells a buyer almost nothing about what a real workload will actually cost until someone runs their own tasks through it and counts the tokens.
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