Tokenless

Tokenless

Why We Rebuilt Microsoft Office From Scratch for AI Agents - Yijia Liang, Compound AI

Interactive discovery

Explore the topic map

Follow the connections between themes, people, and ideas across the Tokenless archive in an interactive topic modeling map.

Open the map Browse posts

Machine Learning

View All
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

View All
Why We Rebuilt Microsoft Office From Scratch for AI Agents - Yijia Liang, Compound AI

Why We Rebuilt Microsoft Office From Scratch for AI Agents - Yijia Liang, Compound AI

Yijia Liang, founder of Compound and former finance analyst, explains why personal agents succeeded and what finance needs beyond them: multiplayer agents with their own inboxes, a headless Office engine rebuilt with agents, and agent swarms that navigate massive data rooms and models while keeping every output grounded in citations.

Most of Your Docs Readers Are Now AI Agents - Hahnbee Lee, Mintlify & Lincoln Murr, Coinbase

Most of Your Docs Readers Are Now AI Agents - Hahnbee Lee, Mintlify & Lincoln Murr, Coinbase

Hahnbee Lee of Mintlify and Lincoln Murr of Coinbase discuss what changes when AI agents become the main users of software products. They cover why documentation now needs to be optimized for context windows and accuracy rather than design, how Coinbase is exposing its business through APIs, and how the x402 payment standard and crypto microtransactions let agents pay for services and gain greater autonomy.

If Your AI Scores 100%, Your Eval Is Wrong - Ramakrishnan Lokanathan, eslams.com

If Your AI Scores 100%, Your Eval Is Wrong - Ramakrishnan Lokanathan, eslams.com

Ramakrishnan Lokanathan argues that AI evals are broken because they are overcomplicated, and lays out a practical framework for building them for high-stakes applications: define the most ambitious version of success, test every step of a workflow, combine automated checks with human review and adversarial tests, guard against regressions, and turn real user failures into tests. He also introduces eSlams, an open-source package where models compete in games like chess, Go, and poker as a window into how they reason.

Technology

View All
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

Context Is the New Code — Patrick Debois, Tessl

Context Is the New Code — Patrick Debois, Tessl

Patrick Debois argues that as AI coding agents become more capable, the context that drives them—prompts, rules, and memory—needs its own engineering discipline, akin to how we manage code. He introduces the Context Development Lifecycle (Generate, Evaluate, Distribute, and Observe) to make context a shared, repeatable, and improvable part of software delivery, creating a flywheel effect where better context leads to better agent output and continuous improvement.

Human-in-the-Loop Automation with n8n — Liam McGarrigle

Human-in-the-Loop Automation with n8n — Liam McGarrigle

Liam McGarrigle demonstrates how to build secure, observable, and controllable AI agents in n8n. The workshop covers creating a human-in-the-loop workflow for managing Gmail and Google Calendar, focusing on n8n's visual system for tool configuration, prompting strategies, and implementing essential approval steps to prevent unintended actions.

I Gave an AI Agent the Keys to My Life (Here's What Happened) — Radek Sienkiewicz, Velvet Shark

I Gave an AI Agent the Keys to My Life (Here's What Happened) — Radek Sienkiewicz, Velvet Shark

A deep dive into the practical, long-term experience of giving a personal AI agent (Open-Claw) incremental control over one's digital life. The talk covers the gradual "permission creep," the pivotal role of an Obsidian knowledge base for providing context, the ecosystem of overnight cron jobs for self-maintenance, and the philosophy of using an agent to "optimize for your future self."

Software Engineering Is Becoming Plan and Review — Louis Knight-Webb, Vibe Kanban

Software Engineering Is Becoming Plan and Review — Louis Knight-Webb, Vibe Kanban

As AI handles more of the coding, the role of a software engineer is shifting from writing code to planning and reviewing the work of AI agents. This talk explores the implications of this shift, the new workflows it demands, and the tools required to manage them effectively.

Why cultivating agency matters more than cultivating skills in the AI era | Max Schoening (Notion)

Why cultivating agency matters more than cultivating skills in the AI era | Max Schoening (Notion)

Max Schoening, Head of Product at Notion, discusses how AI is reshaping software development. He argues that agency—the drive to effect change—is now more critical than specific skills, as AI makes the first 10% of any project 'free'. Schoening introduces his 'tiny core' theory for great products, debates the 'SaaSpocalypse', and emphasizes the growing importance of software quality and taste in an era of exploding software quantity.

How RAG, GraphRAG, and Context Engineering Improve AI Performance

How RAG, GraphRAG, and Context Engineering Improve AI Performance

Martin Keen explains that context, not model intelligence, is the biggest bottleneck in AI. He introduces Context Engineering, its four pillars (Connected Access, Knowledge Layer, Precision Retrieval, Runtime Governance), and advanced techniques like GraphRAG to build more reliable, context-aware AI systems.

← PreviousNext →

Stay In The Loop! Subscribe to Our Newsletter.

Get updates straight to your inbox. No spam, just useful content.