Using Claude to generate code and CodeRabbit to review it has proven eye-opening.
The reviewer frequently flags substantial problems that slip past the generator. Clear evidence that layered AI workflows expose weaknesses single models tend to miss.
🚨 LATEST: Claude maker Anthropic is calling for a global pause in AI development, warning that models are approaching the ability to self-improve without human intervention.
Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.
It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx
🚨THE AI COST CRISIS HAS STARTED
Valve reportedly told engineers to stop using Claude because AI bills were exploding, while the CEO says its entire yearly AI budget was already destroyed by April.
🚨BREAKING: THE AI BUBBLE HAS STARTED TO BURST
MICROSOFT JUST TOLD 100,000 ENGINEERS TO STOP USING CLAUDE BECAUSE THE BILLS EXPLODED.. UBER BURNED ITS ENTIRE ANNUAL AI BUDGET BY APRIL..
Microsoft invested $5 billion in Anthropic.. gave 100,000 engineers Claude Code access.. encouraged adoption.. watched usage explode.. then the invoices arrived.. and issued an internal order to cancel nearly all Claude Code licenses by end of June and force everyone onto their own cheaper tool..
the company that bet $5 billion on Anthropic just told its own engineers to stop using Anthropic's product because it costs too much..
Uber rolled out Claude Code in December 2025.. by March 84% of their 5,000 engineers were using it.. 70% of all committed code was coming from AI.. heavy users burning $500 to $2,000 per month each.. the CTO spent $1,200 in a single two-hour demo.. they built internal leaderboards gamifying AI consumption.. and blew the entire annual budget by April with eight months remaining..
then Nvidia's VP of applied deep learning said it out loud.. "for my team the cost of compute is far beyond the costs of the employees".. a VP at the company that sells the chips said using AI costs more than paying humans..
but here's the part that broke my brain..
Goldman Sachs forecasts a 24x increase in token consumption by 2030.. Gartner says even as per-token prices drop 90% total enterprise AI costs go UP because agents consume exponentially more tokens per task.. the more powerful and useful the AI becomes the more expensive it is to run at the scale that makes it transformative..
every CEO for two years said the same thing on every earnings call.. AI reduces headcount and cuts costs.. the stock went up every time.. workers got fired.. stock went up.. AI strategy announced.. stock went up..
$725 billion in AI infrastructure spending this year across Big Tech..
and the first companies to actually deploy these tools at real scale are already pulling back because the invoice arrived before the productivity gain was large enough to cover it..
the gap between what the earnings call said and what the invoices say..
is the most important number in markets right now..
and nobody on Wall Street has priced it in yet.
In software, this is especially absurd. The field moves at breakneck speed.
Frameworks rise and fall in a few years. Languages and tools that were “must-haves” five years ago are now legacy.
And AI has completely changed the game.
What mattered most yesterday, a Computer Science degree from Stanford or a senior title at Google, frequently tells you far less about a candidate than whether they can actually ship reliable software, debug complex systems under pressure, or learn new paradigms quickly.
It’s time to stop treating résumés (CVs) like report cards that define someone’s worth in software.
Degrees from prestigious universities, job titles at FAANG-level companies, and shiny awards often say more about someone’s starting advantages, risk tolerance, or ability to play the credential game than about their actual talent, creativity, or engineering character.
It won’t be free forever. AI companies will need to start making money when the seed capital dries up. Unlike previous Silicon Valley startups ups, whose primary expense was people, AI companies need so much compute there isn’t enough to go around. That’s why Anthropic have signed a crazy deal with SpaceX, they didn’t have any other option.