필터 결과
24개정렬
18:56ENJohn Feminella: Five Controls for AI Agents, and the $900 Million Bank ErrorJohn Feminella · Two SigmaA payment mistake shows why good intentions and approval prompts are not enough. Feminella describes practical controls for giving agents useful autonomy.
18:12ENTim Tyler: An Accountability Framework for AI Agents as a Digital WorkforceTim Tyler · GraviteeThe Gravitee speaker applies identity, sponsorship, authority and oversight to agents, drawing on how organizations manage human work.
23:22ENNoyan Tokgozoglu: How Optiver Builds an AI Platform for Fast, Measurable DecisionsNoyan Tokgozoglu · OptiverThe trading firm’s AI engineering lead explains same-day model adoption, on-premises infrastructure, cost controls and the limits of replaying agent evaluations.
16:38ENAiden Sochowski: Securing 300 Agents in a 60-Person CompanyAiden Sochowski · RunlayerRunlayer’s founding engineer explains what session monitoring revealed about agent permissions, prompt injection, tool errors and runaway cost.
29:40ENHow Reddit Proto Connects Design, Live Data and Production Code게스트 Blair Metcalf · 진행자 Claire VoBlair Metcalf demonstrates Reddit’s internal prototyping harness and its design-system mapping for Figma and Cursor.
19:43ENJack Wotherspoon on Building a Team of Managed AgentsJack Wotherspoon · Google DeepMindGoogle DeepMind’s Jack Wotherspoon introduces Gemini Managed Agents: cloud sandboxes that let teams run coding and research agents with a single API call. He explains how persistent environments, reusable skills, proxy-injected credentials, schedules, and specialized agents fit together.
20:55ENJesse Hall: Build Voice Agents for Conversations, Not LeaderboardsJesse Hall · LiveKitLiveKit’s Jesse Hall explains how to evaluate voice agents as real-time systems: understand callers, handle interruptions, keep talking while tools run, and measure the delay people actually hear.
15:27ENWhat AI Engineers Do Now: Build the Loop Around AgentsAparna Dhinakaran · Arize AIAparna Dhinakaran argues that AI engineers are moving from shipping individual features to building systems that let agent teams improve them. At Arize, that means tracing agent behavior, evaluating its work against human judgment, and feeding those signals back into an always-on agent.
19:37ENJay Sahnan and Arik Bird on Building Financial Agents for the Whole WebJay Sahnan, Arik Bird · BrowserbaseBrowserbase’s Jay Sahnan and Arik Bird show how browser agents reach financial data hidden behind logins and bot defenses. Their Ramp, Bill, and Stripe examples connect reliable cloud browsers with Stagehand’s more adaptive controls.
18:34ENModel Routing for AI Coding: A Worked Cost ExampleMatthew Berman · Forward FutureMatthew Berman separates planning, implementation and review to explain how different models can fit different tasks.
16:11ENSeven AI Coding Agent Loops and When to Use ThemMatthew Berman · Forward FutureMatthew Berman explains how triggers, goals and repeatable checks can turn coding tasks into agent workflows, with examples for performance, documentation and product quality.
27:15ENMeta-Harness: Searching for Better AI Agent InfrastructureMatthew Berman · Forward FutureMatthew Berman reviews a paper on using a coding agent to iteratively improve model harnesses and discusses its experimental limits.
22:31ENMatthew Berman’s OpenClaw Setup: Models, Workflows, and SecurityMatthew Berman · Forward FutureA walkthrough of a personal AI assistant’s configuration, scheduling, integrations and practical automations, with attention to the risks of granting it access.
27:19ENThe Turing Test Passed. Warp's CEO Says Nobody Seemed to Care진행자 Sarah Guo, Elad GilZach Lloyd on distilling intelligence without consciousness, why a 40-year-old terminal is the front door for coding agents, and why senior engineers just got more expensive.
15:54ENClaude Sonnet 4.5: Coding, Long Tasks and a Simulated DesktopMatthew Berman, Dario Amodei · Forward FutureMatthew Berman reviews Anthropic’s launch claims and tries a generated-interface demo.
19:06ENSleep-Time Compute: Preparing AI Context Before a QuestionMatthew Berman · Forward FutureMatthew Berman reviews a 2025 paper on moving some reasoning ahead of a user query, and explains where its experiments found benefits and limits.
27:32ENOpenAI’s Responses API and Agents SDK: A Launch WalkthroughMatthew Berman · Forward FutureMatthew Berman reacts to a launch demonstration of web and file search, computer use, agent handoffs and tracing.
19:06ENBuilding Effective AI Agents: Patterns, Trade-offs and EvaluationMatthew Berman · Forward FutureMatthew Berman discusses Anthropic’s guide to workflows and agents, adding examples from his own projects.
27:07ENAfter adding $100 billion a month, Jensen Huang says NVIDIA is selling the data center진행자 Sarah Guo, Elad GilSarah Guo and Elad Gil clip their favorite 2024 No Priors conversations into a year-end reel of NVIDIA, Karpathy, Sierra, Sora, Waymo, Figma, and Scale.
29:28ENDevin Will Not Replace Engineers. It Will Multiply Them, Says Cognition’s Scott Wu진행자 Sarah Guo, Elad GilThe IOI champion behind Devin explains why an AI software engineer that you can watch over the shoulder creates more human engineers, not fewer.
16:22ENHarrison Chase on Planning, Interface Design and Memory for AI AgentsMatthew Berman, Harrison Chase · Forward FutureThe LangChain CEO outlines open questions for agent builders, with commentary from Matthew Berman on oversight, workflows and memory.
27:32ENFrom a side project to 700 integrations: Harrison Chase on what still blocks agents진행자 Sarah Guo, Elad GilThe LangChain CEO walks through a two-year churn of patterns, and why memory, planning, and few-shot data still matter more than swapping models.
15:11ENBuilding a Transcript-to-Article Team in AutoGen StudioMatthew Berman · Forward FutureMatthew Berman configures a retrieval skill, two agents and a group workflow, then troubleshoots missing credentials and output.
29:09ENPlan in 90-Day Windows: How OpenAI's Product Leaders Ship Fast Without Losing the Plot진행자 Lenny RachitskyOpenAI's Tara Seshan and Nan Yu tell Claire Vo how they ship imperfect features, design agents people can follow, work with research, and think about 2027.









