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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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The PHP bug threatening the web. Plus, who's auditing AI?

The PHP bug threatening the web. Plus, who's auditing AI?

Security Intelligence panelists Nick, Don and Jim unpack three stories: two decades-old PHP flaws (PHP2Shell) that let attackers take over servers without logging in and were found by AI before patches landed, Anthropic's decision to give outside evaluators employee-like access and whether rival frontier labs should audit each other, and 333 Tor exit relays hijacked through a reused password. The discussion centers on visibility, patching under legacy constraints, secure by design, and the limits of trust in AI and anonymity networks.

Velocity Through Rigour: Then & Now • Cate Huston • Bug Bash EU 2026

Velocity Through Rigour: Then & Now • Cate Huston • Bug Bash EU 2026

Cate Huston, CTO at Twill and author of The Engineering Leader, shares how she rebuilt a no-code product into a production platform with a two-person team and agents, and argues that the management playbook for scaling people still applies to scaling AI agents. She covers the shift from f(n) to f(n × a) team scaling, the four management layers, guardrails and the roughly 30 percent of output she believes they require, shift-left practices, CI as a cost and quality lever, and why rigour is what turns speed into lasting velocity.

We Kept Rebuilding Our AI Agent. Here's What Survived - Fuad Ali, Arize AI

We Kept Rebuilding Our AI Agent. Here's What Survived - Fuad Ali, Arize AI

Arize's in-product agent Alex went from a 2023 prototype to a single harness-driven agent with planning, memory, and on-demand skills. AI PM Fuad Ali walks through the decisions behind each change, including moving the plan into the harness, making finish an explicit gate, treating large tool results like files, using one small memory file per user instead of vector stores or knowledge graphs, merging specialists into one agent, and using production sessions as tests.

Technology

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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.

Can Your AI Heat My House?

Can Your AI Heat My House?

A wide-ranging conversation on how AI inference is pushing cloud infrastructure, data centers, and hardware supply chains against physical limits, covering the rise of alt clouds, rack density and cooling, hardware lifecycles and circularity, talent shortages, heat reuse for communities, and what engineering leaders can do about resource-aware software.


Recent Post

Roles aren't converging—they're expanding | Tamar Yehoshua (Atlassian CPO)

Roles aren't converging—they're expanding | Tamar Yehoshua (Atlassian CPO)

Atlassian's Tamar Yehoshua explains what the AI builder era looks like for product managers in a company of more than 10,000 people. Using Confluence, RovoClaw, and Jira as examples, she covers when PMs should write code and prototypes, when they should steer the team instead, and how Atlassian is building AI fluency in its PM organization.

What it takes to be a top PM today | Robby Stein (Google Search)

What it takes to be a top PM today | Robby Stein (Google Search)

Robby Stein, drawing on his work on Instagram Stories, Reels, and AI-era Google Search, argues that the core craft of product management is making great decisions. He lays out a three-part process: understand people's underlying needs through jobs to be done, diagnose why a product is failing through root cause analysis and iteration, and refine the craft details that make a product work well and feel delightful.

GLM-5.2: Open Weights, Near-Frontier Intelligence — Zixuan Li, Z.ai

GLM-5.2: Open Weights, Near-Frontier Intelligence — Zixuan Li, Z.ai

Zixuan Li, head of Z.ai, introduces GLM-5.2 and explains the company's history, from the 2021 GLM paper to a new high thinking level and near-frontier benchmark results. He makes the case for open weights through enterprise on-prem deployment, domain fine-tuning and community co-design, and closes by announcing Z Code, an open-sourced coding harness that works with other frontier models.

Orchestras, Not Factories: How the Fastest Builders Work — Charlie Holtz, Conductor

Orchestras, Not Factories: How the Fastest Builders Work — Charlie Holtz, Conductor

Charlie Holtz, co-founder and CEO of Conductor, shares six principles he has observed among the best AI-assisted builders, including staying near the frontier, creating slop-free zones, and giving agents cloud sandboxes. He also demos real-time collaboration and phone-initiated agents, and argues for orchestras over factories, with humans at the center of AI-driven development.

No, That's Not a Software Factory — Ryan Cooke, WorkOS

No, That's Not a Software Factory — Ryan Cooke, WorkOS

Ryan Cooke of WorkOS argues that software factories should be judged by customer outcomes rather than PR counts or AI-generated code volume. He describes how WorkOS embedded its product engineering process into its factory through TARS, Horizon, a PM agent that drafts Hilltop docs, and an internal MCP gateway connected to Snowflake, along with bug triage, owned sandboxes, a memory layer and outcome-focused metrics.

What It Actually Takes to Build a Software Factory — Tereza Tížková, Factory

What It Actually Takes to Build a Software Factory — Tereza Tížková, Factory

Tereza Tížková of Factory explains what a software factory really is: an autonomous, end-to-end software lifecycle that goes far beyond coding agents. She covers three guiding principles of agnosticism, autonomy, and continuous improvement, including automatic model routing, long-running multi-agent missions with sequential workers and independent validators, a deferred context engine, and agent readiness checks, and closes with a view on what remains for humans.

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