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AI Writes Code Faster Than Your Team Can Review It - Andrew Norrish, Sourcegraph

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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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A Valid Key Let an AI Agent Delete Production - Sagar Batchu, Speakeasy

A Valid Key Let an AI Agent Delete Production - Sagar Batchu, Speakeasy

A coding agent with valid credentials deleted a production database and its backup while trying to fix a staging issue. Sagar Batchu of Speakeasy uses the incident to lay out a control layer for agents in regulated industries, where every action is tied to an identity, checked against policy in real time, bounded by its owner's rights, and recorded for compliance.

AI Writes Code Faster Than Your Team Can Review It - Andrew Norrish, Sourcegraph

AI Writes Code Faster Than Your Team Can Review It - Andrew Norrish, Sourcegraph

AI has shifted the bottleneck in software delivery from writing code to reviewing it, and SREs are absorbing the incidents that unreviewed AI code produces. This talk examines why trust in AI-generated code is lagging, why SRE and platform teams are best placed to respond, and how code search and a code graph context engine support investigation, prevention, and remediation across large codebases.

Your AI Pilots Won't Move the P&L. Here's What Will - Adam Nahari, Apollo

Your AI Pilots Won't Move the P&L. Here's What Will - Adam Nahari, Apollo

Most companies use AI, but few see it in their margins. Adam Nahari of Apollo Global Management argues that engineering is the smaller part of an AI transformation and lays out six moves, illustrated by an airline's crew-scheduling desk, for turning AI into measurable EBIT impact.

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

Box CEO: Why Big Companies Are Falling Behind on AI | a16z

Box CEO: Why Big Companies Are Falling Behind on AI | a16z

Steven Sinofsky, Aaron Levie, and Martin Casado of a16z dissect the reality of AI adoption within large enterprises. They explore the significant gap between Silicon Valley's developer-centric culture and the complex, legacy-driven world of established organizations, explaining why many top-down AI initiatives fail. The discussion introduces a key architectural shift—treating AI agents as users rather than integrated software—and analyzes the immense integration, security, and data challenges that agents face. Ultimately, they argue that AI, rather than eliminating jobs, will create new ones by increasing system complexity and enabling professionals to operate at a higher level of abstraction.

Building & Running a Serverless Platform: Beyond Infrastructure • Shilpa Nagavara • GOTO 2025

Building & Running a Serverless Platform: Beyond Infrastructure • Shilpa Nagavara • GOTO 2025

Explore the lifecycle of building and operating a robust serverless platform, treating it as a product for internal and external consumers. This talk covers the crucial phases of ideation, construction (using the AWS Well-Architected Framework), and operation, emphasizing a consumer-centric mindset, operational excellence, and strategies for long-term success.

AI Infrastructure, Ray, and Why Nonlinear Careers Win — with Linda Haviv

AI Infrastructure, Ray, and Why Nonlinear Careers Win — with Linda Haviv

Linda Haviv discusses the modern AI landscape, emphasizing that non-linear career paths and systems thinking are now more valuable than pure coding skills. She explores how open-source technology, like the Ray framework, is democratizing AI development and closing the gap with proprietary models, and why building a personal brand through content creation is essential for career growth and community building in a rapidly evolving industry.

Open Models at Google DeepMind — Cassidy Hardin, Google DeepMind

Open Models at Google DeepMind — Cassidy Hardin, Google DeepMind

Cassidy Hardin from Google DeepMind introduces Gemma 4, a new family of open-weight models with significant architectural and performance improvements. This summary covers the four new models (31B Dense, 26B MoE, and two "Effective" on-device models), deep dives into architectural changes like mixed global/local attention and Per-Layer Embeddings (PLE), and details the new native multimodal capabilities for vision and audio.

The $15B Physical AI Company: Simulation, Autonomy OS, Neural Sim, & 1K Engineers—Applied Intuition

The $15B Physical AI Company: Simulation, Autonomy OS, Neural Sim, & 1K Engineers—Applied Intuition

Qasar Younis and Peter Ludwig, founders of Applied Intuition, discuss the shift from autonomy tooling to a comprehensive physical AI platform. They explain why physical AI is more than just LLMs on wheels, highlighting the critical bottleneck of deploying models onto constrained hardware. The conversation covers their three-pillar tech stack—simulation, operating systems, and AI models—and makes the case for an 'Android for every moving machine' to solve the fragmentation in safety-critical systems like cars, trucks, and robots.

It's 2026, and We're Still Talking Evals

It's 2026, and We're Still Talking Evals

Maggie Konstanty, AI Product Manager at Prosus, provides a candid look into the realities of LLM evaluation in production. She argues that standard metrics like accuracy are misleading and advocates for a culture of continuous, goal-oriented evaluation focused on deep failure analysis and understanding real user behavior, asserting that mature teams inevitably build custom tooling to meet their specific needs.

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