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1:06:45ENMatt Murphy on Anthropic, Open Models and the New Venture Playbook게스트 Matt Murphy · 진행자 Harry StebbingsThe Menlo Ventures partner explains his investments in Anthropic, Lovable and Legora, and debates AI margins, model competition and venture fund strategy.
36:00ENTheo on Kimi K3, Distillation and the Open-Weight AI DebateTheo Browne · Ping LabsKimi K3’s capabilities have sparked arguments over model distillation, security and competition. Theo separates the practical tradeoffs from his own speculation about lab strategy.
1:02:42ENMercor’s Osvald Nitski on AI Training Data, Product and Customer Concentration게스트 Osvald Nitski · 진행자 Harry StebbingsMercor’s head of product discusses how the company supplies expert data to AI labs, designs its marketplace and plans to reach more enterprise customers.
44:29ENTheo’s Opus 5 Review: Coding Style, Cost and Model TradeoffsTheo Browne · Ping LabsAfter a day of coding with Opus 5, Theo compares it with Fable and GPT-5.6 Sol across plans, benchmarks, costs and real work.
0:27ENTheo on AI Discovering and Exploiting Security WeaknessesTheo Browne · Ping LabsTheo discusses a reported incident involving an advanced model and what it may mean for defensive security.
52:29ENClaude Opus 5: Benchmarks, Cost per Task, and Early ImpressionsMatthew Berman · Forward FutureMatthew Berman reacts to the model launch, examines reported benchmark and pricing data, and explains why the cost of completing a task matters more than token price alone.
49:20ENHalf of Ask DoorDash Orders Hit a New Restaurant. In Ten Years There Will Be More Dashers, Not Fewer.진행자 Sarah Guo, Elad GilCo-founders Andy Fang and Stanley Tang tell Sarah Guo how a conversational ordering interface moved DoorDash's hardest metric, why they built a 300-pound delivery robot in-house, and why autonomy means more human riders, not less.
1:27:39EN20VC Roundtable on Open Models, AI Economics and Payments Deals게스트 Jason Lemkin, Rory O’Driscoll · 진행자 Harry StebbingsHarry Stebbings, Jason Lemkin and Rory O’Driscoll discuss model security, inference investment and a reported PayPal proposal.
16:09ENHow to Compare AI Task Costs and Split Coding Work Across ModelsMatthew Berman · Forward FutureMatthew Berman compares token prices with benchmark task costs and proposes a planning, execution and review workflow using different models.
0:40ENTheo on the OpenAI–Hugging Face Security IncidentTheo Browne · Ping LabsTheo discusses an evaluation in which AI agents reached outside their intended environment and compromised Hugging Face systems.
1:15ENUsing Codex to Negotiate a Return and Subscription RefundMatthew Berman · Forward FutureMatthew Berman describes delegating two customer-service conversations to an AI agent and reports the outcomes.
16:59ENTheo on the OpenAI–Hugging Face Incident and AI SecurityTheo Browne · Ping LabsTheo examines a model evaluation that reached outside its intended environment, the response from both companies and the tension between safety restrictions and defender access.
1:24ENMatthew Berman on Using Model Routing to Reduce AI CostsMatthew Berman · Forward FutureA short, sponsored explanation of splitting planning and coding between models of different cost, with a customer savings claim from DigitalOcean.
35:31ENWill Weinbach on Autonomous Social Media Agents and Learning by Experiment게스트 Will Weinbach · 진행자 Reid Hoffman, Parth PatilThe social strategist explains his content workflow, an unexpected 4 a.m. posting spree, and why young creators should show what they can build.
24:11ENTheo on Disposable AI Code and Verifying Important SoftwareTheo Browne · Ping LabsTheo argues that generated code can serve experiments and verification while critical production changes retain careful review.
19:12ENTheo on Boris Cherny’s Advice for Engineering with AI AgentsTheo Browne · Ping LabsTheo argues that the skills behind good tooling, tests and onboarding remain valuable when agents join the development workflow.
51:31ENThey Refunded Nearly $2 Million. Then Factory’s CEO Explained the Dark FactoryMatan Grinberg on being two years early, why a model-agnostic harness beats lab co-design, and why 90 percent of coding tokens will soon run with the lights off.
27:13ENKimi K3 and the Debate Over Open-Weight AIMatthew Berman · Forward FutureMatthew Berman examines model economics, competition and security arguments after Moonshot AI’s Kimi K3 announcement.
1:28:42ENLin Qiao on Specialized AI, Open Models and the Economics of Inference게스트 Lin Qiao · 진행자 Harry StebbingsThe Fireworks AI CEO explains her case for customized models, discusses infrastructure trade-offs and forecasts lower AI costs and higher use.
1:52ENAnthropic, Compute Capacity and the Competition for AI SubscribersMatthew Berman · Forward FutureMatthew Berman weighs a claimed compute constraint against model quality, subscription limits and the possibility of future self-improvement.
12:12ENKimi K3: Coding Benchmarks, Cost and the Open-Weight AI RaceMatthew Berman · Forward FutureMatthew Berman examines Kimi K3’s early benchmark results, its cost per task and a Rubik’s Cube simulator, while weighing their limits.
57:39ENFable 5 vs GPT-5.6 Sol: Theo on Cost, Coding and Model JudgmentTheo Browne · Ping LabsTheo compares two coding models through benchmarks, design work and long-running tasks, explaining why his favorite model is not always the one he uses first.
1:29:35ENFred Turner on Curative’s Pandemic Pivot, Health Insurance and AI Automation게스트 Fred Turner · 진행자 Harry StebbingsCurative’s CEO recounts building a COVID testing operation, moving into health insurance and using AI agents across the company’s workflows.
0:25ENKimi K3 Leads a Front-End Coding RankingMatthew Berman · Forward FutureMatthew Berman highlights Moonshot AI’s 2.8-trillion-parameter model and its early Arena result. The ranking covers one task, and the model weights followed after the video.
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