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Day 2 · Oct 14
Ramp Labs' Alexander Shevchenko argues that an application-layer company should not wait for the next frontier model, and shows three Ramp cases where applied research closed the gap: a post-trained Qwen 3.5 specialist, KV-cache cartridges, and 10,000-agent pen-test swarms.
Day 2 · Oct 14
Sonar CEO Tariq Shaukat argues that agentic coding makes code abundant and confidence scarce, and presents a four-part code confidence formula (intent, guardrails, verification, evidence) for engineering trust into agentic software factories.
Day 2 · Oct 14
Coinbase engineering manager Evan Kormos maps policy-driven workflows as deterministic DAGs on the outside, lets agents loop adaptively inside each node, and turns autonomy on only when measured evaluation quality clears a policy threshold.
Day 2 · Oct 14
Joseph Kim, head of ChatGPT for financial services at OpenAI, presents the month-old product built with Morgan Stanley and Evercore, frames it as a way to close the "capability overhang", and predicts models will outperform the best human experts on financial judgment tasks by 2027.
Day 2 · Oct 14
Bloomberg's Andrey Rybka walks through a catalog of unnamed real agent incidents — runaway agents, a July 26 sandbox escape with 17,600 actions in 4.
Day 2 · Oct 14
A former Coatue VP and Compound AI co-founder explains how Compound rebuilt Excel, PowerPoint, and Word from scratch with coding agents so multiplayer, long-running agents can move buy-side finance work from copilot to autopilot.
Day 2 · Oct 14
A SemiAnalysis research analyst argues that identical GPUs deliver very different amounts of useful intelligence depending on who operates them, so compute buyers, benchmarks, and futures markets must grade the operator, not just the chip.
Day 2 · Oct 14
Evan Conrad of San Francisco Compute explains why a compute market only works if it is physically settled, why credit (not power) is the number-one AI bottleneck, and what happens to startups if nobody builds one.
Day 2 · Oct 14
Jump Trading's compute trading leads map the unlit, chat-brokered over-the-counter market for physical GPU compute, from Jevons-paradox demand and the prepayment squeeze on middle-market buyers to the microstructure and policy that could turn compute into a real market.
Day 2 · Oct 14
Carmen Li, CEO of both Compute Exchange and Silicon Data, argues for a neutral GPU exchange that owns no hardware, verifies both sides of every trade, and publishes the term-structure curves and residual values that now feed CME futures, NVIDIA's investor deck, and bank appraisals.
Day 2 · Oct 14
A recorded, off-agenda talk in which a senior staff engineer from Intuit Credit Karma shows how to move AI agents from experiment to enterprise: an MCP gateway with JWT auth and Redis sessions, security-reviewed FastMCP servers, OpenTelemetry-based monitoring, LangGraph with human-in-the-loop, memory, eval tables, a PI…
Day 2 · Oct 14
Michele Grant, creator of Leading at Scale, uses a $15 billion M&A integration case to argue that a working agent earns enterprise trust only through a written value case with baselines, assigned ownership under the three lines model, and engineering evidence gated by a four-stage autonomy scorecard.
Day 2 · Oct 14
Jellyfish research on the industry's largest engineering-workflow-plus-AI-telemetry dataset shows AI is only about 2.5% of the cost of a merged PR, so token bills are still cheap relative to salary - track cost per merged PR, not the token bill.
Day 2 · Oct 14
Nori Agentic's CEO Amol Kapoor and CTO Clifford Ressel, joined on screen by their agent Jiro, explain in a podcast-format online-track talk how cloud agents can maintain a securities master whose every cell change today sends a person hunting for provenance in Google Drive, email, and contract PDFs.
Day 2 · Oct 14
A fireside chat in which Scott Worland (CTO, Norm Ai) interviews John Stecher (CTO, Blackstone) on keeping a technology roadmap durable while frontier AI jumps every few months: fix the data strategy first, treat evals as the quality bar, build throwaway POCs fast, and leave conduits open for frontier intelligence inst…
Day 2 · Oct 14
Kepler CEO Vinoo Ganesh argues that Wall Street's distrust of AI is structural, not a model-quality problem, and shows how making code write every number through deterministic pointers yields citations that are verified, corrected at search time, or refused.
Day 2 · Oct 14
Philipp Schmid of Google DeepMind builds "Bug", an autonomous Wall Street co-worker, live on Gemini managed agents — with skills, MCP connectors, write-only credentials behind a network proxy, hooks, cron triggers, and a Gemini 4.0 recap.
Day 2 · Oct 14
Citadel Securities' Joao Wenzel argues that the one person who "seems to know everything" is a company's only world model, and shows the state-estimator loop (update, age, observe, grade, correct) his team uses to bootstrap one from decks, Slack, meetings, code changes, and agent traces — a job RAG cannot do.
Day 2 · Oct 14
Will Brown of Prime Intellect argues that after chatbots, reasoners, agents, and innovators, the next stage of AI progress is the AI-native enterprise: an organization that compounds its implicit institutional knowledge by continually training its own open-source models, instead of re-teaching agents in context on ever…
Day 2 · Oct 14
Jemima Abu (CAIS) argues that letting AI agents ship inaccessible products wastes tokens, time, and money — her experiment saw a 58% cost reduction and one-third the build time when the agent ran with an accessibility skill.
Day 2 · Oct 14
Coder staff product manager Zhao Chenjiang opens a talk about three real incidents of AI usage gone wrong at real companies by arguing they were all preventable with infrastructure controls you mostly already own — not with a smarter, more expensive frontier model — but the stream cut to a music interstitial before the…
Day 2 · Oct 14
Rowspace co-founder Michael Manapat interviews Jack McDonald, COO of Apollo's Redding Ridge Capital, about turning AI from a nice-to-have into mission-critical infrastructure for structured credit and CLO management.
Day 2 · Oct 14
Basis co-founder Mitchell Troyanovsky argues that agents only earn end-to-end production use when they are simple and reliable, and shows three tools — behavior specs, forking, and simulations — that supervise the process of long-horizon work, not just the outcome.
Day 2 · Oct 14
Runway co-founder Cristóbal Valenzuela argues that next-frame prediction, scaled far enough, turns video models into universal simulation engines, and demos Continuum, a video-model operating system that Runway plans to release within 8 to 12 months.