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8 Folien18:27EN
AI Engineer· 26. Okt. 2026Daksh Gupta on Building a Better AI Code Review AgentDaksh Gupta · GreptileGreptile co-founder Daksh Gupta explains why a webhook plus a coding agent is not enough for reliable pull-request review—and how targeted prompts, incident data, model inversion, codebase context, browser testing, and task-specific model routing can help.Code review & verificationCoding-AgentenEntwicklungs-Workflows & Tests+2
23:48EN
20VC with Harry Stebbings· 26. Okt. 2026Podcast · 2 StimmenSatya Nadella on Zero Trust for AI and Why Every Company Should Own Its IntelligenceGast: Satya Nadella · Moderation: Harry StebbingsThe Microsoft CEO argues that capable agents need security boundaries even as alignment research remains unsettled, and explains why firms should retain the value created by their own AI use.Enterprise-KIAI securityEvals+2
3 Folien30:11ZH
硅谷101· 25. Okt. 2026AI 如何重构跨境支付:从交易路由、风控到智能体商务Gast: Leo Li, Apple Gao · Moderation: 陈茜硅谷101 从一笔跨境机票付款出发,拆解支付网络的复杂性,以及 Antom 如何把 AI 引入运营、风险判断和智能体交易。FintechAgentic commerceKI im Finanzwesen+2
12 Folien17:56EN
AI Engineer· 25. Okt. 2026How Bridgewater Keeps Its AI Analyst Inside Permission BoundariesNikhil Benesch, Aaron Linsky · turbopufferAaron Linsky and Nikhil Benesch explain why search over an enterprise vault must honor document permissions without sacrificing recall or speed. Their solution combines vector indexing with native filtering to search hundreds of millions of vectors in roughly 120 milliseconds.Enterprise-KIPrivacy & data governanceSearch & retrieval+2
7 Folien35:19EN
AI Engineer· 25. Okt. 2026SallyAnn DeLucia: How to Write Your First AI EvalSallyAnn DeLucia · Arize AITurn an agent’s real traces into concrete pass/fail criteria, then build an LLM judge you can test, align with people, and run in production.Evals & ObservabilityEvalsAgent Engineering+2
0:26EN
Matthew Berman· 25. Okt. 2026Sam Altman on Human Values and Problem-Solving in an AI WorldSam Altman · OpenAIIn a short interview excerpt, Altman considers the enjoyment of solving hard problems and the human role in interpreting results.Human-AI CollaborationFuture of WorkAI Strategy
9 Folien20:58EN
AI Engineer· 25. Okt. 2026Vinoo Ganesh on Making Financial AI Cite Every NumberVinoo Ganesh · KeplerKepler CEO Vinoo Ganesh explains why financial AI should retrieve and cite figures while deterministic software handles the math. His design makes traceability, retrieval quality, and tenant security part of the answer itself.KI im FinanzwesenEnterprise-KIRetrieval-Augmented Generation+2
10 Folien18:31EN
AI Engineer· 25. Okt. 2026Janie Gu and Suyeol Yun: Why Frontier Models Fail as Buy-Side AnalystsJanie Gu, Suyeol Yun · Google DeepMindJanie Gu explains why benchmark scores can mislead, while Suyeol Yun presents MandateBench, which tests whether a model can turn a fund mandate into a defensible investment memo. The two talks show why real workflows, reproducible grading, and evidence-backed reasoning matter.KI im FinanzwesenBenchmarksEvals+2
2 Folien0:36EN
Matthew Berman· 25. Okt. 2026Kimi K3.1 and a Rubik’s Cube Solver DemonstrationMatthew Berman · Forward FutureMatthew Berman shows a scrambled virtual cube being solved and gives the Kimi K3.1 test a favorable assessment.EvalsCoding-AgentenOpen-weight models
8 Folien15:27EN
AI Engineer· 25. Okt. 2026What 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.Agent EngineeringEvalsObservability & Zuverlässigkeit+2
7 Folien19:37EN
AI Engineer· 25. Okt. 2026Jay 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.Agent EngineeringComputer useWorkflow automation+2
4 Folien19:24EN
AI Engineer· 24. Okt. 2026Building an Agent Regression Loop from Production TracesSofia Jakovcevic · Arize AISofia Jakovcevic demonstrates how to compare agent changes across safety, task completion and other dimensions before deployment.Agent EngineeringEvals & ObservabilityEntwicklungs-Workflows & Tests+1
32 Folien1:50:48EN
Y Combinator· 24. Okt. 2026Why Inference Matters 12× More Than TrainingFrançois Chaubard, Dan Fu, Jeff Morgan, Joe Fioti, Liangsheng Yin · Y CombinatorYC Paper Club walks the inference stack from an API request down to GPU kernels. Four talks from Together AI, Ollama, Luminal, and SGLang argue that serving quality, not just training FLOPs, is where most of the compute and the money now sit.InferenceGPU programming & kernelsKV caching & prefix reuse+2
5 Folien27:09EN
AI Engineer· 24. Okt. 2026Laurie Voss on the Product Engineer After AI Coding AgentsLaurie Voss · Arize AIAs code generation accelerates, Voss argues that review, operations and defining user needs become successive constraints—and that junior training must change.Software engineeringDeveloper productivityFuture of Work+2
2 Folien0:21EN
Matthew Berman· 24. Okt. 2026An AI-Generated Kimi Benchmark Chart Used Invented ScoresMatthew Berman · Forward FutureMatthew Berman asks for a graph of Kimi K3.1 Pro benchmarks, then discovers that the displayed figures are illustrative placeholders.BenchmarksEvalsGenerative media
21:52EN
PragerU· 24. Okt. 2026Josef Witt-Doerring on Gen Z Mental Health, Isolation, and Psychiatric PrescribingShabbos Kestenbaum, Josef Witt-Doerring, Scott Galloway · PragerUOn The Brief, Shabbos Kestenbaum and psychiatrist Josef Witt-Doerring discuss why young adults are struggling, how prescribing incentives shape care, and the place of relationships and daily habits in treatment.Mental HealthSocial MediaRelationships+2
5 Folien16:44EN
AI Engineer· 24. Okt. 2026How Bridgewater Built the Vault for Human Researchers and AI AgentsSam Green, Aaron Linsky · Bridgewater AssociatesSam Green and Aaron Linsky explain how Bridgewater organized more than 100 million documents and built search and proactive research tools around them.KI im FinanzwesenSearch & retrievalAgent Engineering+2
6 Folien25:50EN
Matthew Berman· 24. Okt. 2026Kimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.Open-weight modelsBenchmarksAI cost & performance+1
1:13:26EN
20VC with Harry Stebbings· 24. Okt. 2026Podcast · 2 StimmenNaveen Rao on Energy, AI Hardware, Verification and the Future of RoboticsGast: Naveen Rao · Moderation: Harry StebbingsThe Unconventional AI founder argues that energy efficiency will shape AI hardware, while the growing volume of model output makes verification more valuable.EnergySemiconductorsInference+2
2 Folien0:43EN
Theo - t3․gg· 23. Okt. 2026Theo Distinguishes Security Vulnerabilities from Active AttacksTheo Browne · Ping LabsA short explanation of why disclosed software flaws and reported attacks are different kinds of security news.CybersecuritySoftware engineering
2 Folien32:20EN
Matthew Berman· 23. Okt. 2026Who Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.Local inferenceOpen-weight modelsAI cost & performance+1
0:54EN
Matthew Berman· 23. Okt. 2026Sam Altman: Seek Major Life Advice From People, Not AISam Altman · OpenAIThe OpenAI CEO distinguishes practical AI assistance from consequential life advice and argues for assistants that can push back.Human-AI CollaborationDecision MakingAI Alignment
5 Folien34:11EN
GOTO Conferences· 23. Okt. 2026Anatoliy Bilenko and Alberto Carretero: Making Database Protocols Reliable with Formal Methods and AIAnatoliy Bilenko, Alberto Carretero · CanonicalCanonical’s database engineers connect executable specifications, model-based tests, failure exploration, and reconstructed execution histories—and explain why none of these techniques proves a real system correct on its own.Entwicklungs-Workflows & TestsCode review & verificationObservability & Zuverlässigkeit+2
6 Folien1:03:37EN
Matthew Berman· 23. Okt. 2026Matthew Berman’s Team Tests Kimi K3.1 on Animation, Games, and ChartsMatthew Berman, Alex, Brian · Forward FutureA live team AMA turns into an informal test of Kimi K3.1, from personal-agent workflows to motion graphics, a browser game, and a benchmark chart.Coding-AgentenGenerative mediaEvals+2
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