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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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How to Decide What Your AI Agent Should Remember - Wojciech Pluta, Oracle

How to Decide What Your AI Agent Should Remember - Wojciech Pluta, Oracle

Wojciech Pluta, head of technical marketing for Oracle AI Database, argues that RAG gives agents a read path while memory gives them a write path, and that the write path is where business value lives. He explains memory promotion, a pipeline that admits, rejects, or escalates candidate memories, and demonstrates it with a mortgage agent that remembers preferences across sessions while refusing unsafe rules. The talk also covers short-term, long-term, and shared memory, why databases are a strong storage layer, and the context card that keeps prompts lean.

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.

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

From Blind Spots to Merged PRs: Continuous Agentic Performance Optimization - May Walter, Hud

From Blind Spots to Merged PRs: Continuous Agentic Performance Optimization - May Walter, Hud

May Walter, CTO of Hud, details a real-world case study on integrating AI agents into the SDLC for continuous performance optimization. The talk covers Hud's runtime intelligence layer, which uses production context to identify and fix high-ROI performance issues like N+1 queries and missing database indexes. It highlights the technical approach, challenges, and the development of a human-friendly reporting system that delivers measurable P90 latency improvements, enabling proactive optimization in mature codebases.

Why Netflix is betting on systems thinkers—not specialists—in the AI era | Elizabeth Stone (CPTO)

Why Netflix is betting on systems thinkers—not specialists—in the AI era | Elizabeth Stone (CPTO)

Elizabeth Stone, Netflix CPTO, discusses how AI is transforming product development and company culture. She highlights the increasing importance of "systems thinking," managing the influx of AI-generated output with clear guardrails, fostering "AI fluency" across all roles, and maintaining Netflix's unique "excellence as an operating system" through high talent density and a comfort with risk-taking. The conversation also explores AI's impact on content creation, the future of entertainment, and talent management.

A Practitioner's Guide to Graphs - Tim Ainge, Good Collective

A Practitioner's Guide to Graphs - Tim Ainge, Good Collective

A speed-run through the fundamentals of graphs for AI engineers, covering how to build effective graphs from unstructured text using schema-first approaches and entity resolution, and then exploring powerful graph-native algorithms like Personalized PageRank, Shortest Path, and Subgraph Matching, all illustrated with real-world applications to create smarter, cheaper, and more reliable AI solutions.

Content Is Code - Matt Palmer, Conductor

Content Is Code - Matt Palmer, Conductor

Matt Palmer discusses how code, empowered by AI, is becoming the fastest and most efficient medium for technical content creation, emphasizing that while code is cheap, structure and conscientiousness are now the most valuable assets for producing high-quality output. He predicts the rise of "content engineers" who leverage declarative pipelines to automate technical communication.

Agents Need Receipts, Not More Tool Calls - Armanas Povilionis, Alithea Bio

Agents Need Receipts, Not More Tool Calls - Armanas Povilionis, Alithea Bio

Armanas Povilionis introduces Froglet, an open-source protocol addressing the critical need for verifiable agent-to-agent collaboration in AI workflows, especially in scientific research. Froglet enables agents to discover, transact with, and receive tamper-proof receipts for services across organizational boundaries, transforming them into 'executive chefs' managing distributed supply chains rather than isolated 'cooks' with more tools. The protocol streamlines interactions into a signed flow (Descriptor -> Offer -> Quote -> Deal -> Receipt) and integrates with diverse agent harnesses and execution environments, abstracting complex operations for LLM-driven agents.

Agents Need Feature Flags - Sachin Gupta

Agents Need Feature Flags - Sachin Gupta

AI teams are deploying advanced agent systems without the fundamental safety mechanisms (feature flags, canaries, kill switches) that web teams adopted over a decade ago. This oversight leads to critical incidents like data deletion and financial loss. This talk introduces six agent-specific feature flag types—for prompts, tools, models, memory, autonomy, and sub-agents—and outlines a practical playbook for secure AI deployment, emphasizing the critical role of a pre-wired kill switch to manage the high blast radius of AI agents.

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