Browse entries 1225–1248 of 1294. Return to the first page to search and filter the complete collection.
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A hands-on workshop covering the full lifecycle of AI-assisted development, from turning ambiguous requirements into agent-ready plans to running autonomous coding agents that ship production features.
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April 21, 2026 - all times in EST -- 9:00am - Welcome to Day 2 -- 9:10am - David House, G2i Transforming Programming Mindsets: Case Studies in Agentic Coding Adoption -- 9:35am - Sarah Chieng, Cerebras Help!
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An agent runs entirely on your phone, no cloud, and plays Space Invaders, perceiving the scene, predicting the aliens, and dodging bullets in a loop. Another solves the New York Times mini crossword with a constraint graph that backtracks when the fills stop fitting.
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An agent hands a doctor a clean, confident fact: the patient has a penicillin allergy. But that fact was synthesized from three sources, an EHR record, a lab report, and something the patient typed into an intake chatbot, and by the time it reaches the doctor, which one it came from is gone.
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In July 2025 Dex Horthy turned the lights off: an agent software factory where nobody read the code. It fell apart. An issue appeared that no amount of prompting could fix, the site was down, users were furious, and he was digging through a codebase he had stopped reading three months earlier.
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A second refund on the same order. A payout sent to the support desk instead of the buyer. An order status of "probably shipped." These are the kinds of mistakes a probabilistic agent makes and a paragraph of instructions cannot reliably stop.
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Your agent can reach your data and still get it wrong. Vector search hands it a slice, Text2SQL hands it another, and neither tells it what is actually relevant or how the pieces connect, so the answer comes back confident and wrong.
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Feed it 67 videos from the 2022 World Cup and ask for the near misses, the shots that almost scored but did not, each with a reason, and it returns them. Ask it to track Messi across the entire corpus and describe the camera framing, and it finds the moment he slaloms past a sliding defender.
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Tanmai Gopal plotted the daily edits to his own company brain expecting the usual shape, a burst of enthusiasm followed by neglect. The line kept climbing instead, and it surprised him.
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Gus Iwanaga opens by disowning his own session title, then shows the demo that did not work. His team asked their system for a sales report for Q1 four times over.
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Between the moment an x402 server verifies a payment signature and the moment it settles on the blockchain, nothing stops the buyer spending that money somewhere else.
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The team took captions from real videos, regenerated the same scenes with their own model, and ran a human eval. People largely preferred the generated version. Dumitru Erhan is quick to deflate that result.
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The fiber optic cable carrying data into California's financial fraud system has been cut in half. One end sits on the internet with a laser transmitter. The other end, inside the building, has only a receiver. There is no transmitter pointing outward, so data physically cannot leave.
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Long Lake does not sell software. It buys the company. Thirty five services businesses so far across property management, architecture and HR, plus a 6.3 billion dollar take private of the world's largest corporate travel platform.
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Something went wrong, please try again. Kanish Manuja opens on that message and then explains why it exists, which is more interesting than laziness. Once a response starts streaming you have committed to that provider.
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For a given internal pain point, Brian Lewis might find 10 to 15 startups worth a look, book two or three demos, run zero or one pilot, and sign roughly one contract for every four pilots. That works out to about 5% of demo calls ending in a signature, which turns out to match published benchmarks.
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Between NVIDIA's A100 in 2020 and the B200 in 2024, BF16 tensor core throughput improved 7.2x. Intra node communication improved 3x, and inter node communication only 2x.
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The champion just left. Do not contact this customer again. Blocked in legal. The facts that decide what a rep does next usually sit in someone's meeting notes, and Flora Liu's point is that an automation which cannot read them will eventually do something catastrophically wrong.
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Ask one data vendor for phone numbers across a set of countries and you get about half of them. Hence waterfalling: layer provider on provider until the field is filled, and run evals to know which to trust.
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Offer Pro V1 golf balls to golfers at East Coast construction companies. Arman Vaziri uses that as a running example and mentions in passing that it works really well. The golf balls are not the point.
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Two terminals run the same prompt, build me a spinning wheel app. On the left every request goes to a single premium model. On the right they go through a router that picks a model per task. Both finish at about the same time with comparable output, and by then the router's session has cost 8 cents against 25.
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A clinical note from a real consultation reads like a routine tension headache, and nothing in it is wrong. What never reached the page is that the patient also mentioned her jaw aches when she chews, which alongside a new headache over 50 is a red flag for a condition that can take her sight within days.
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A customer replied good morning to an outreach text and the model called him immediately. Another confirmed a Thursday appointment, said sounds good, and was told a call was happening right now.
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Roughly 70% of medical communication still moves by fax. What reaches Anterior is scanned fax bundles that can run past 300 pages, carrying handwriting, checkboxes, tables and images across one patient's entire clinical trajectory. Anuj Iravane calls it an observation through a fuzzy lens over a lifespan.