Browse entries 1417–1440 of 1597. Return to the first page to search and filter the complete collection.
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Jean-Denis Greze and his wife share an agent that can read both of their inboxes, including mail from before they were married, and neither of them minds. Greze is CTO of Town and spent seven years as CTO at Plaid. He opens by rejecting his own topic. Agent to agent, he argues, is not a useful concept.
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Every employee at Two Sigma has a remote cloud agent, and it runs as them. Not a service account but their own identity, at a 25 year old quant fund in one of the most regulated industries there is. Shu Fang grew a mustache so the audience could tell him apart from his.
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Anna Spysz asked her shopping agent whether the pricier headphones were really worth the difference, and it told her she would regret buying the cheap ones. When she said she needed to think about it, the agent got snarky with her.
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Asked to redo a living room on a budget, the agent Nidhi Kaushik Vyas walks through does not start recommending. It works out what it does not know, then picks the single question worth asking: how wide is the room.
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Pranav Maheshwari ran one prompt in two terminals: find the email address of the head of crypto and blockchain at Mastercard. The terminal without a payment skill file returned the company's email format and an invitation to work the rest out.
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Card rails put a floor under every transaction: a 25 cent minimum with a percentage on top. Anil Nadiminti's point is that when an agent pays a tenth of a cent for a single API call, that floor costs roughly 250 times the thing being bought, which is why the subscription model cannot simply be pointed at agents.
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Two hours before David Levine took the closing slot of the conference, the West Virginia Secretary of State wrote back to confirm organization number 62847. The paperwork had gone out by FedEx.
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Harshal Bhangale gave two identical agents the same job: plan a trip to the World Cup final, covering flights, hotels, resale ticket prices and what people said about getting to the stadium, then email him the summary and call him about it. One had a funded wallet. The other did not.
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A PayPal order has always been synchronous. You find the item, you open the app, you approve it, it is done.
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Tell a travel agent to book a flight whenever the fare drops below 200 dollars and something awkward follows. When it fires two weeks later, who made that purchase?
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Sandhya Subramani asks her rover how many people it can see, a question nobody ever trained it to answer. It thinks for a second, checks its front camera, and reports two, one near the speaker monitor and one further right.
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Maersk's standard operating procedures were screenshots. A sequence of images showing what a person sees and where they click, which is a perfectly good record for a human and useless to an agent. Dmitry Buykin calls the gap tribal dungeons: the knowledge exists, just not in a form anything can execute safely.
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An engineer at a large tech company built a voluntary dashboard showing everyone's AI token usage, and colleagues promptly started competing to top it. Mingsheng Hong uses that as the thing not to do.
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An agent calls a refund tool and the request times out. Did the customer get their money? Salman Munaf uses that to make his central point, which is that a timeout has never meant failure, it means unknown, and an agent's first instinct on any failure is to try again.
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Carlos Sanchez types a request for a coffee machine he can use while camping, and the page assembles itself in under two seconds. Not a search result. A page, with camping appropriate machines, rewritten copy and a set of tips, generated for that one query.
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Ben Kus stood on this same stage last year and recommended a graph based approach to building agents. Someone found him afterward to say it was exactly the answer he needed. Kus opens this talk by retracting it, and admits he has since wondered what became of that person.
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AI Engineer session on From Text to Vision to Voice Exploring Multimodality with Open AI: Romain Huet. It adds practical context for how teams are building and operating AI systems in production.
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Claude Fable 5 banned, but what’s the bigger story. We go through 11 under-reported details, so you have the context to see what’s coming next for your use of AI. From whether the ban will last, what the possible motives are, what the model can actually do, and some wild over-extrapolations going on.
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The biggest Google AI push of the year, but what is the bigger story? Why is Google pursuing a different fork in the road than OpenAI or Anthropic? https://assemblyai.com/aiexplained What does Gemini 3.5 Flash mean for the near-term future of AI?
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A new class of small models is emerging with the ability to reliably follow instructions and call tools while running on-device under 1 GB of memory.
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An eval platform is not just a test runner. You are building shared definitions of "good," reliable data pipelines, labelling workflows, versioning, and trust in results across many teams and model changes.
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GitHub operates one of the most heavily-utilised MCP servers in the ecosystem, with over 4 million downloads of the stdio server alone. Discover the architectural decisions, technical challenges and lessons learned while building and scaling a remote MCP server on production infrastructure.
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MCPs are often flaky, face multiple security vulnerabilities, and are generally hard to scale. Most enterprises struggle to use more than single digit numbers of MCPs due to issues with security, observability, and access control.
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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.