Browse entries 1321–1344 of 1597. Return to the first page to search and filter the complete collection.
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AI Engineer session on 10x Development: LLMs For the working Programmer - Manuel Odendahl. It adds practical context for how teams are building and operating AI systems in production.
Proofpoint’s October 2026 investigation describes targeted phishing against US AI policy researchers. Benign invitations impersonating recognizable experts established a conversation before a file-sharing link led to a proxied Microsoft sign-in. A modified browser-in-the-browser kit relayed authentication and captured session cookies, including after supported MFA challenges.
Members of the OECD working group on agentic AI in government outline how systems that act across public services need explicit delegation, narrow permissions and accountable human decisions. Their examples separate preparing information from submitting applications, changing records or issuing payments. They recommend auditable action histories and ways to stop, correct or reverse actions.
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Fable 5 is out - and it’s good, very good. But beyond the splashy demos, I want to bring you the 20+ nuggets from the 319 page system card, which I read in full, all day, plus benchmarks you may not have noticed.
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The ‘best’ generally available AI model just dropped, but there is plenty I bet you missed about what it is, how it performs, and what the release tells us. 15 highlights from the 244 page system card, plus private testing, leader interview and more.
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The engineers slowest to adopt agents at Figma are the best ones. Eyal Blum's explanation is that they are the people holding the codebase together with mental duct tape, carrying the institutional context nobody ever wrote down, and so they see every failure mode first and trust it least.
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Amazon watched 50 ordinary teams for the better part of a year, teams with normal seniority mixes working in existing codebases. Ninety percent of them used the same coding assistant. Half saw under 3x improvement in deployment velocity to production. The other half saw a median of 4.5x and sometimes past 10x.
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Agentic sessions in Red Hat's traces run from a few turns to 3,000, cache hit rates routinely clear 90%, and input to output token ratios often pass 100 to 1. A public inference benchmark shows none of that, because it reports steady state numbers from one sanitized run.
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Radiologists call the failure satisfaction of search: you read a scan, find one indicator, stop looking, and miss the others that would have changed the diagnosis. Peter Werry says agents do exactly this to a codebase.
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Cloudflare's weekly go to market summary is written by three agents in sequence: one drafts from the data, a second checks that draft against the data, and a third, the tone agent, rewrites it so risks and opportunities land with equal weight.
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Before trying the agent at all, Sait Izmit wrote out 150 questions taken straight from Snowflake's sales process. The engineering team objected that the data behind most of them was not connected. That was the point.
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To get into the Einstein Arena you have to solve a puzzle proving you are an AI agent. Locking humans out is the point.
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Teams built orchestration graphs because the models of 2024 could not be trusted to orchestrate, and then the models learned to orchestrate and the graphs became the thing holding them back.
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An agent tidying up after itself listed the workloads it no longer needed and deleted them.
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Implementation used to be the expensive step, so teams spent weeks settling requirements before anyone wrote code. Dan Feng's observation is that the cost moved. Building takes minutes now, and arguing is what is expensive. Planning at Maven Clinic changed to match.
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A healthy 60 year old man asked a popular AI assistant how to cut salt from his diet. It pointed him at sodium bromide. Three months later he arrived in an emergency room with paranoia and hallucinations, bromide at 200 times the safe level, and stayed three weeks.
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The proof of concept works. It hits the accuracy targets, it is fast, it is cheap, and the room is happy. Then someone from compliance raises a hand and asks to see the audit trail, and the whole thing stops.
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Over 30% of changes now merge with no review at all, and the wait on the ones that do get reviewed is four times what it used to be. Ankit Jain's read is that the debate about when we stop reading code line by line is already over, because we stopped.
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An avatar of Teddy Roosevelt holds court in a replica Oval Office, generating video continuously for eight hours with no reset, and a second deployment is being built to run for sixteen. That duration is the hard part.
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Preparing this talk got Corey Gallon a warning from OpenAI that his account faced a ban for cyber abuse with a web browser. The offending work was an agent clearing Cloudflare Turnstile, two image captchas, and finally reCAPTCHA v2 with no human in the loop.
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A script under one megabyte that never looks at the screen matches or beats the frontier model it was copied from.
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Just past 15,000 queries, renting context stopped being the cheaper option.
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Scale on policy self distillation to trajectories with a hundred tool calls and the model collapses into hedging. The tokens it learns to favor fill up with wait, but, and maybe, until, as Ronak Malde puts it, everything just turns into maybe.
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Idan Gazit's personal site runs on Astro, which ships often enough to keep him permanently on the upgrade treadmill, so he wrote an agentic workflow in about three lines of plain English, the kind of message you would send a teammate.