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Your AI Agent Starts Every Session Like a New Hire - Killian Carlsen-Phelan, Sonar

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Machine Learning

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Judge a Transaction by the Company It Keeps — Somya Rai & MD Sharique, EXL

Judge a Transaction by the Company It Keeps — Somya Rai & MD Sharique, EXL

EXL developed an advanced fraud detection system that augments XGBoost with Graph Neural Network (GNN) embeddings. Traditional tabular models struggle to capture fraud signals residing in transaction neighborhoods. The system's innovative design includes meticulous sampling strategies, disjoint monthly graph construction for leakage control, and a GraphSAGE architecture that aggregates mean, max, and standard deviation of neighbor features to detect subtle fraud patterns. Emphasizing explainability for regulatory compliance and analyst trust, it also features a highly optimized serving architecture achieving 3ms P99 latency, pivoting to edge prediction to reduce cache footprint from 60GB to 2-3GB. This led to a 27-33% relative lift in true positive rates and a projected $65 million incremental fraud capture.

From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model

From 15% to 90% GPU Utilization: Fix the Data Pipeline, Not the Model

Tarun Sunkaraneni from Amazon AGI shows how a multimodal SFT pipeline that spent about 85% of its time waiting on data was brought to roughly 90% GPU utilization. He walks through concurrency with asyncio and Ray actors, prefetching, zero-copy transfer via Ray's object store, and a network-card bottleneck that appears only at scale, and argues that the hardest part of training throughput is often keeping GPUs fed rather than optimizing the model.

Small Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI

Small Models, Big Results: Training a Finance Agent for Under $500 — Charles Dickens, Snorkel AI

Snorkel AI and UC Berkeley's Sky Computing Lab show that a 4B Qwen3 model, trained with reinforcement learning for under $500 using the rLLM framework, beats its 235B sibling on expert-validated financial question answering built from SEC 10-K filings. The talk covers the FinQA dataset construction and verification, common failure modes of frontier models, transfer to multi-table and general tool-use tasks, and ablations showing that simple data and binary rewards outperform more elaborate setups, since the real bottleneck is disciplined tool use rather than reasoning depth.

Artificial Intelligence

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Your AI Agent Starts Every Session Like a New Hire - Killian Carlsen-Phelan, Sonar

Your AI Agent Starts Every Session Like a New Hire - Killian Carlsen-Phelan, Sonar

Killian Carlsen-Phelan of Sonar introduces Sonar Vortex, a plugin that gives coding agents a map of a codebase and its guidelines before they write, then deterministically verifies every edit. In a live demo, it catches a temp-file permissions bug that the agent's own tests missed and rejects the agent's first fix.

Please Stop Telling Your AI to “Search Harder”

Please Stop Telling Your AI to “Search Harder”

A discussion of how agent-driven traffic overwhelms APIs, gateways, and cloud infrastructure built for predictable load. It compares microservices with agent workloads, revisits SaaS multi-tenancy, and examines Agent Substrate's actor and worker model for suspend-and-resume agent sessions, with a critical view of whether most users will ever need this layer directly.

Why AI Could Turn Small Law Firms Into Billion-Dollar Businesses

Why AI Could Turn Small Law Firms Into Billion-Dollar Businesses

Eve CEO Jay Madheswaran joins a16z's Alex Rampell to explain how AI is automating plaintiff law end to end, expanding access to legal representation by making previously uneconomical cases viable, and why the economics point toward outcome-based pricing, agent-to-agent negotiation, and a fundamentally different law firm structure.

Technology

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Why Founders Are Betting Big on Factories, Mines, and Energy

Why Founders Are Betting Big on Factories, Mines, and Energy

Erin Price-Wright and Connor Love unpack the AD50 and the rebuilding of America's industrial base, covering how defense demand is financing manufacturing capacity for commercial markets, how AI is reshaping factory economics, how a new generation of founders applies lessons from SpaceX, Tesla, Anduril, and Palantir to mining, energy, and manufacturing, and why private capital is now willing to fund physical infrastructure before government demand is guaranteed.

Mark Cuban’s Plan to Make Healthcare Affordable

Mark Cuban’s Plan to Make Healthcare Affordable

Mark Cuban and Julie Yoo discuss how transparency, direct contracting, and AI could reshape healthcare economics, from Cost Plus Drugs and modular pod manufacturing to personalized medicine, the future of physicians, and advice for founders who want to use AI to learn rather than to stop thinking.

Exploits Now Beat Patches: Open Source Security in the AI Era - Patrick Smyth, Chainguard

Exploits Now Beat Patches: Open Source Security in the AI Era - Patrick Smyth, Chainguard

Patrick Smyth of Chainguard examines how frontier AI has compressed the time between vulnerability disclosure and exploitation, leaving 30-day remediation cycles obsolete. The talk covers AI-assisted attacks, waves of supply chain malware, four attack surfaces spanning malware, known CVEs, zero days, and side doors like CI/CD, developer laptops, and agent skills, and practical defenses including cooldown periods, faster CVE remediation, and signing artifacts with SLSA and Sigstore.

Recent Post

Evals-Driven Development for a Mental Health AI Coach — Akele Reed & Dave Revere, SonderMind

Evals-Driven Development for a Mental Health AI Coach — Akele Reed & Dave Revere, SonderMind

SonderMind's AI mental health coach, Sonder, pioneers an eval-driven development approach balancing effectiveness and safety. This involves a clinical feedback loop turning human therapist insights into machine-readable evaluations, an Ethics Engine with modular, LLM-as-a-judge guardrails for evolving clinical guidelines, and a shift from single-prompt agents to a Supervisor/Executor/Evaluator architecture with human oversight to ensure safety and quality in high-stakes mental health conversations. They also open-source clinically reviewed datasets to foster community safety.

Loop Engineering from First Principles — Kyle Mistele, HumanLayer

Loop Engineering from First Principles — Kyle Mistele, HumanLayer

Kyle Mistele, in this presentation, argues that fixing the problem of unreviewable 40,000-line pull requests generated by coding agents doesn't lie in better prompts but in better, control theory-inspired loops. He details how to build agentic control loops with distinct sensors, controllers, and actuators, ensuring incremental, verifiable code changes. Using a practical example of RPC API migration, he demonstrates how to implement these loops with tools like ASGrep, integrate them into CI/CD, enable human feedback, and manage workflow to prevent overwhelming reviewers, ultimately leading to more robust and readable agent-generated code.

Why Large? Tiny LMs & Agents on Edge/Robotics — Cormac Brick, Google

Why Large? Tiny LMs & Agents on Edge/Robotics — Cormac Brick, Google

Cormac Brick from Google AI Edge discusses how the increasing constraint of DRAM cost on edge devices necessitates the development and deployment of increasingly smaller AI models. He outlines the work of his team in optimizing models like Gemma, achieving 2.9 bits per weight for a 2 billion parameter model capable of running on a Raspberry Pi at 7.6 tokens/second, or on an NPU at 31 tokens/second decode for vision tasks. The talk delves into 'tiny models' (50M-500M parameters) that extend AI to older devices and enable features like robust voice-to-function calling via fine-tuning with synthetic data, exemplified by an offline voice dictation app.

What Actually Makes A Startup Durable

What Actually Makes A Startup Durable

YC partners discuss how founders should navigate the AI era, emphasizing the rapid decrease in AI costs, the evolving definition of a 'hard problem' for startups, the critical importance of human connection and co-founders, and practical advice on building AI-native loops, pivoting, and achieving distribution in a world where software is easy to build.

What Big Tech Missed And How Startups Can Still Win

What Big Tech Missed And How Startups Can Still Win

Alexandre LeBrun, CEO of AMI Labs, discusses his career building and selling AI companies, emphasizing his strategy of tackling problems "20 years too early." He delves into AMI Labs' contrarian bet on "world models" over traditional LLMs, highlighting their ability to learn directly from real-world sensory data, unlike LLMs which learn from human-written text. LeBrun explains how this approach is critical for developing intelligent robots and avoiding the pitfalls of Vision-Language Assistants (VLAs). He also touches upon the challenges of securing talent, data, and compute for such an ambitious project, the strategic choice of location, and the importance of holding an extremely large vision while solving a narrow problem for early founders.

Why Physical AI Is the Next Platform Shift

Why Physical AI Is the Next Platform Shift

Encord Co-CEO Eric Landau reflects on his transition from a lucrative quant career to founding an AI startup, driven by a deep belief in AI's paradigm-shifting potential. He discusses Encord's slow, compounding path to product-market fit, the pivotal role of Physical AI, and the importance of embracing the emotional rollercoaster of startup life.

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