Developer experience

Oct 22, 2026

Token Maxxing Is Over and Here Is What Comes Next

Pepijn Senders, a principal engineer and former AI enablement lead at HelloFresh, explains how his team rebuilt a banking platform in six months with about 800,000 lines of code, mostly written by Sonnet, and why choosing a model that keeps developers involved matters more than raw autonomy. He covers measuring AI ROI through token spend versus output, keeping humans in control of code, the risks of agent recommendations, team refinement sessions, prompt word effects, and a meta harness built on Claude Code.

Oct 21, 2026

The AI Content System Behind 200M Views — Sarah Chieng, Cerebras & Cova Lee, OpenAI

Sarah Chieng (Cerebras) and Cova Lee (OpenAI) walk through an agent-powered content system spanning ideation, scripting, recording, editing, repurposing, and publishing, emphasizing swipe files, voice-driven scripts, design systems, API-based editing, and weekly process reviews as ways to free creators to focus on craft over generic AI output.

Sep 07, 2026

Inside the Team That Killed Mandatory Code Review — Quinn Slack, AMP

Quinn from AMP discusses a paradigm shift towards cloud-native AI agents and remote development, advocating for the end of local development and traditional code review. He details how AMP's 'Orbs' enable parallel, secure, and remote execution, and how agents are transforming internal tools ('jellyware'), diminishing the role of GitHub and traditional CI/CD, and fostering a lean, high-trust company structure.

Sep 04, 2026

Open Models Change The Economics of AI

Ollama Co-founder Jeffrey Morgan discusses the enterprise shift to open models, driven by cost, customization, and coding agents, leading to a 150X token growth. He highlights the dominance of Chinese models in cloud consumption, the hardware renaissance enabling local LLMs, and the rise of ultra-efficient "flash" models. Morgan also shares Ollama's journey, from its YC pivot to its monetization strategy, and reflects on lessons for building AI companies.

Aug 28, 2026

AI-Native Organisations Run on Skills: How to Structure and Scale Them — Imad Touil, QuantumBlack

Imad Touil explores the critical need for governing AI skills within organizations, asserting that skills represent the true repository of enterprise know-how. He contrasts simplified coding agent loops with complex, real-world product lifecycles, demonstrating how ungoverned skills lead to technical debt—including duplication, quality degradation, security risks, and lack of discoverability. Proposing a microservices-inspired approach, Touil outlines a centralized skills platform and human-led governance model essential for achieving deterministic workflows, boosting productivity, and mitigating risks in AI-native enterprises.

Aug 28, 2026

How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma

Figma's internal AI agent adoption journey faces challenges like reduced developer agency, skepticism from senior engineers, and communication inefficiency. Solutions include investing in verification, using a testing pyramid for agent review, prioritizing detailed planning over prompting, engaging skeptics to build AI safety roadmaps, and implementing attention-aware communication by clearly marking AI-generated content.