Tokenless

Tokenless

The Right Model for Each Coding Task

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
The Right Model for Each Coding Task

The Right Model for Each Coding Task

Weave co-founders Adam Cohen and Andrew Churchill explain how their engineering analytics platform evolved from measuring human productivity to optimizing coding agents. The conversation covers Weave Router, which automatically selects the best model for each coding task, cost per output as a better measure than raw token spend, an AI coach for engineers, and the design of autonomous software factories with automated validation.

The New AI Agents That Shop, Plan, and Gossip

The New AI Agents That Shop, Plan, and Gossip

David Pawlan, creator of Assistant Benchmark, joins Anish Acharya and Josh Elman to take stock of an agent landscape that changes almost weekly. Drawing on tests of more than 140 assistants and a survey of AI power users, they explore why trust is the dominant fear, how fences and permissions might make agents safe, and where privacy, embarrassment, and judgment fit in. The conversation then moves to multiplayer and gossipy agents, agent-to-agent networks that could spark serendipity, and the possibility that the most valuable agents will do more than save time, becoming a kind of secret superpower.

AI-Friendly Code: The Missing Link for Speed with Quality • Adam Tornhill • GOTO Copenhagen 2026

AI-Friendly Code: The Missing Link for Speed with Quality • Adam Tornhill • GOTO Copenhagen 2026

Adam Tornhill explores why AI agents produce fast early gains that often erode under growing code complexity, and how the Code Health metric, safeguarding loops, and codebase-specific refactoring can keep agentic development sustainable at scale, including a 300,000-line legacy case study.

Technology

View All
What iPhone Packaging Reveals About the Robotics Opportunity

What iPhone Packaging Reveals About the Robotics Opportunity

Tutor Intelligence CEO Josh Gruenstein explains why robotics is a systems problem spanning AI, hardware, manufacturing, and customers, and how deploying robots into real factories and warehouses, with human tutors as backup, generates the data that makes them more capable. The discussion covers the company's own robot designs, its focus on small and mid-sized businesses, the economics of flexible robotic labor, and the implications for American manufacturing and supply chains.

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.

Recent Post

Securing & Governing Autonomous AI Agents: Risks & Safeguards

Securing & Governing Autonomous AI Agents: Risks & Safeguards

Experts Jeff Crume and Josh Spurgin explore the critical security and governance challenges posed by autonomous AI agents. They detail common threats like prompt injection, data poisoning, and model theft, and discuss governance issues such as bias, transparency, and accountability, providing a set of actionable safeguards to build secure, trustworthy, and compliant AI systems.

How to Think About Scale, Funding & Competitive Positioning | David Solomon & Ben Horowitz

How to Think About Scale, Funding & Competitive Positioning | David Solomon & Ben Horowitz

Goldman Sachs CEO David Solomon and a16z cofounder Ben Horowitz discuss the current macro environment, the unique competitive dynamics of AI, enterprise adoption strategies like Goldman's "One GS 3.0" initiative, and the critical policy debates surrounding AI and crypto.

Real-time features, AI search, Agentic similarities

Real-time features, AI search, Agentic similarities

Varant Zanoyan and Nikhil Simha Raprolu of Zipline AI explain why traditional feature stores are the wrong abstraction. They detail the journey of Chronon, the open-source engine born at Airbnb and battle-tested at Stripe, which focuses on compute, orchestration, and real-time correctness to solve the hardest data engineering challenges in ML, from fraud detection to powering modern AI agents with features and embeddings.

State of the Art of Biological Computing • Ewelina Kurtys & Charles Humble • GOTO 2026

State of the Art of Biological Computing • Ewelina Kurtys & Charles Humble • GOTO 2026

Dr. Ewelina Kurtys of FinalSpark discusses the ambitious goal of building computers from living neurons, aiming for a 1-million-fold increase in energy efficiency over digital systems. The conversation delves into the technical challenges of neural encoding and plasticity, the use of brain organoids, and the profound ethical and philosophical questions surrounding determinism and consciousness in biological hardware.

Inside The New YC Website

Inside The New YC Website

YC's Aaron Epstein and Eve Bouffard detail the redesign of the YC homepage, shifting from a utilitarian, B2B-style site to an inspirational, founder-centric narrative. They discuss the new design's focus on storytelling, the unconventional AI-assisted development process, and the future of interactive web design.

State of the Art of DORA Metrics & AI Integration • Nathen Harvey & Charles Humble

State of the Art of DORA Metrics & AI Integration • Nathen Harvey & Charles Humble

Nathen Harvey, leader of Google's DORA research team, discusses the surprising findings from their latest research on AI's impact on software development. While initial AI adoption correlated with decreased stability and throughput, the latest data shows a reversal for throughput. The conversation explores why this happens, presenting AI as an amplifier of existing systems and introducing DORA's seven essential capabilities for successful AI adoption, including the critical roles of documentation, trust, and expertise.

← PreviousNext →

Stay In The Loop! Subscribe to Our Newsletter.

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