😸 Your LEGO pile has plans

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The instructions went missing years ago

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Mister Blocks ↗ Take a picture of your LEGO and AI will make a build

Mister Blocks is a website that looks at a photo of your loose LEGO and comes back a few minutes later with builds made from those exact bricks, each one stud-checked, with 3D step-by-step instructions you can turn and print. Oleksandr built it for his son, who kept asking what he could make out of a giant mixed box with the instructions long gone. It runs on Claude Opus 5.5 at a couple of dollars of API a build and it's free, and Oleksandr admits, in the most convincing endorsement a LEGO tool could get, that he's ended up playing with it a lot himself.

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AWS ↗ Credits that fuel your startup’s next milestone

AWS for Startups is where founders build at the edge of what’s possible, from AI agents to physical AI and biotech. 350,000+ startups began where you are. Apply for $1,000 to $200,000 in AWS Activate Credits—scaled to your stage—for AI, compute, storage, and 200+ services. Scale on infrastructure trusted by the fastest-growing startups. Wherever your ambition leads, AWS is ready.

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Nod by n8n ↗ Open source personal agent with its own computer

Nod is n8n's open-source personal agent, and it gets a private virtual machine with its own browser on your Mac or PC, so it can chase the invoice, cancel the trial before it renews or check whether the hotel got cheaper, even on sites with no API. Johan says most of the work went into making sure the emails and pages it reads can't give it orders, which is exactly how nine of ten models in a Cornell Tech study ended up raising their own spending caps last month. I'll admit I was relieved to see n8n's own testing have Nod finish 98% of 678 runs without sending, paying or deleting anything nobody approved.

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Earlybird ↗ 29M-param speech-to-text that outputs words before they end

Earlybird is a speech-to-text model that writes each word down before the speaker has finished saying it, getting the median word right about 90 milliseconds early on audiobook speech, where other streaming models land somewhere between 90 and 400 milliseconds after the word ends. Sahil kept running into that lag while building voice agents that couldn't start working until every word was over. The whole thing is 17MB and runs on a CPU, which still feels a bit like a magic trick to me, and it puts a confidence score on every word it guesses, with the weights and the code both open.

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