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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

Jensen Huang: The Mindset That Built NVIDIA

Jensen Huang: The Mindset That Built NVIDIA

Jensen Huang, CEO of NVIDIA, shares critical lessons from NVIDIA's journey, emphasizing how early failures and a commitment to learning new technologies, like purchasing textbooks from Fry's to pivot the company, laid the groundwork for their success. He discusses NVIDIA's strategic vision, driven by accelerating algorithm domains and seeing AlexNet as a universal function approximator, which led to a reinvention of the computing stack. Huang also explores the future of AI with agents, the importance of fine-grained control, and the "Linux moment" of open-source AI, while also forecasting the rise of physical AI and job creation. He concludes with profound advice on resilience, systems thinking, and the "how hard can it be?" mindset for aspiring entrepreneurs in this unprecedented era of technological reset.

DeepSWE: A Contamination-Resistant Coding Benchmark — James Shi, Datacurve

DeepSWE: A Contamination-Resistant Coding Benchmark — James Shi, Datacurve

DeepSWE is a novel benchmark for evaluating AI models on software engineering tasks. It features 113 original, long-horizon problems from real open-source repositories, designed to resist contamination and provide clearer differentiation between models. The benchmark highlights unique failure modes and strengths of models like Claude and GPT, emphasizes realistic prompt design, and uses program-based verifiers focusing on observable behavior.

State of Data — Sean Cai, Independent / State of Data

State of Data — Sean Cai, Independent / State of Data

Sean Cai discusses the evolving landscape of AI data markets, highlighting the shift from raw annotation to high-quality, process-based data. He introduces "Verifier's Law" and its three axes to explain application layer maturity, critiques the shortcomings of current benchmarks, and predicts future AI trends by analyzing data market signals. Cai concludes by envisioning data companies transforming into "neo-labs" that provide enterprise-level reinforcement learning as a service and "Antikythera mechanisms" to manage and monetize real-world data assets.

Anthropic’s first technical PM on token maxing, the jagged edge, and living in the future

Anthropic’s first technical PM on token maxing, the jagged edge, and living in the future

Dianne Penn, Head of Product for Anthropic’s AI Research and Labs teams, discusses Anthropic's journey, the evolving AI landscape, and the changing role of product management. She highlights the importance of adaptability, 'evals as the new PRDs,' and how Anthropic's focus on alignment and safety makes Claude a more effective 'thinking partner' by enabling it to push back on user ideas.

Why AI Makes the Humanities More Important Than Ever

Why AI Makes the Humanities More Important Than Ever

Jeff Crume explores why humanities are crucial in an AI-driven world. While AI generates sophisticated answers, it lacks human understanding, purpose, and judgment. He argues that STEM fields explain 'how' but not 'why,' making humanities essential for ethical decision-making, interpreting AI outputs, understanding bias, and effective prompt engineering. Ultimately, AI amplifies the need for human critical thinking and judgment.

The Messy Reality of Scale: Synthetic Data and Pre-Training — Marah Abdin & Robert McHardy, poolside

The Messy Reality of Scale: Synthetic Data and Pre-Training — Marah Abdin & Robert McHardy, poolside

Poolside discusses their innovative approaches to synthetic data generation, pre-training validation, and distributed training challenges. They highlight how modular data pipelines, rigorous replica hash checks, and numerical stability fixes enabled them to scale their LLMs, culminating in the 118B parameter Laguna S model designed for agentic coding, which shows strong early results against leading open-weight models.

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