Tokenless

Developer productivity

AI Writes the Code. So What's Left for Engineers? - Laurie Voss, Arize AI

AI Writes the Code. So What's Left for Engineers? - Laurie Voss, Arize AI

Laurie Voss, head of developer relations at Arize AI and co-founder of npm, argues that coding agents have made writing code nearly free, so the bottleneck keeps moving first to code review, then to operations and security. What agents can't take over is discovering what people actually need and defining what 'good' means. He introduces the product engineer as the role that remains, examines the collapse in junior engineering hiring, and offers practical advice for engineering leaders.

Better AI Models Won't Fix Your Engineering Team — Nicholas Arcolano, Jellyfish

Better AI Models Won't Fix Your Engineering Team — Nicholas Arcolano, Jellyfish

Nicholas Arcolano of Jellyfish uses data from about 50,000 engineers across 447 companies to test what really drives AI coding output. A natural experiment forcing users onto Grok barely moved merged PRs. The analysis breaks throughput into tool, skill use, token consumption, company and team, and individual engineer, finding the individual and organization matter far more than the model.

A Bank Built Its Own Coding Agent. It Took Off — Felipe Felisola Caso & Francesco Galletta, Monzo

A Bank Built Its Own Coding Agent. It Took Off — Felipe Felisola Caso & Francesco Galletta, Monzo

Felipe Felisola Caso and Francesco Galletta from Monzo explain how an internal Slack agent grew from a viral emoji trigger into a teammate authoring over 10% of merged PRs and running more than 1,800 tasks a day. They attribute its speed to existing platform capabilities, an MCP gateway, a sandboxed orchestration system suited to a regulated bank, and an agent designed as a composable building block for incidents, on-call data quality and non-engineer contributions.

Why AI Can Write Code But Can’t Keep It Running (Yet)

Why AI Can Write Code But Can’t Keep It Running (Yet)

Grepr CEO Jad Naous talks with a16z's Martin Casado about how coding agents have changed a 10-person engineering team, with projects that once took six months now finishing in about ten days. They examine whether AI can reason about and troubleshoot production distributed systems, why operations is a harder problem than code generation, and where AI adoption is likely to go next.

AI Writes More PRs. Who Validates Them? — Ali-Reza Adl-Tabatabai, Sonar

AI Writes More PRs. Who Validates Them? — Ali-Reza Adl-Tabatabai, Sonar

Ali-Reza Adl-Tabatabai, co-founder of Gitar (now part of Sonar), explains why AI-driven growth in PR volume and size turns CI and code review into a bottleneck, and presents agentic validation as the way out: automated review, CI failure analysis, autofix, and auto-merge, built up step by step as trust grows, combined with traditional program analysis in SonarQube.

The Software Factory: From Bug Report to Production Code — Davis Palmie, Factory

The Software Factory: From Bug Report to Production Code — Davis Palmie, Factory

Davis Palmie of Factory explains the software factory, a system of agents that turns bug reports and user feedback into production code. He covers leadership concerns about cost, model choice, engineering roles, and org structure, argues that coding was never the bottleneck, and lays out principles for a factory: model agnosticism, sovereign deployment, and SDLC-wide integration. He also describes eight pillars of agent readiness, starting with narrow use cases like incident triage, and closes with why outcome metrics should replace token counts.

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