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An influential essay arguing that companies should favor mature, 'boring' technology for most problems, saving limited 'innovation tokens' for areas of true differentiation. It emphasizes the importance of known failure modes and global optimization over novelty.
Gergely Orosz comments that Meta uniquely treats engineers as a cost center, contributing to developer departures, while Ryan Nystrom encourages them to leave and join companies like Notion.
Gergely Orosz shares his earlier deep-dive on how OpenAI's Applied team ships ChatGPT so quickly, based on an exclusive interview with engineering lead Evan Morikawa. The article covers OpenAI's engineering culture, independent startup-like operations, tight research integration, and high talent density.
Opinion piece arguing that AI agents remove the speed limit on code changes, causing teams with weak engineering culture to accumulate unmanageable technical debt, making senior engineers' jobs review AI-generated PRs at scale.
A commentary questioning whether the surge in AI-agent-generated pull requests and token consumption metrics actually translates into meaningful business value, warning against optimizing vanity metrics over real impact.
Gergely Orosz comments on Hillel Wayne's interviews with engineers from other fields, who were surprised to learn about version control — a practice software engineers take for granted.
A DevOps engineer recounts interviewing the infrastructure team at ngrok to compare how other teams handle technical disagreements, prompting a personal reexamination of his own work relationships and career.
Gergely Orosz shares the Pragmatic Engineer deepdive on stacked diffs, explaining the concept popularized by Meta and Google, and how GitHub's new public preview makes it more accessible.
This essay by Addy Osmani explores the concept of software factories as scaled agent loops, distinguishing between light factories with human oversight and dark factories without, and emphasizes the importance of understanding and designing the loop, harness, and factory structures.
A discussion with Lucas Wargha on how software engineers can shift toward product engineering by focusing on customer outcomes, with examples like Gmail's background inbox loading.
This article uses the analogy of Mexican cavefish losing their eyes to explain how successful companies can develop 'competence blindness,' where they stop recognizing competence and suppress careful engineering due to a lack of external comparison.
Kent C. Dodds shares a podcast episode with Lucas Wargha discussing product engineering, user conversations, and engineering culture.
OpenAI's Codex app lead Andrew Ambrosino argues that companies abandoning dedicated product roles in favor of everyone being a 'builder' is a terrible idea, emphasizing the value of product discipline and best practices.
A long-tenured Meta engineer lost faith in leadership and eventually accepted a higher-compensation offer at a high-growth startup, illustrating a broader trend of Meta losing standout engineers due to mismanagement.
The article argues that evaluations for AI agents are only as reliable as the clarity of intent behind them, highlighting that traditional software engineering challenges with requirements and accountability are exacerbated in the context of autonomous agents. It questions how responsibility can be assigned given the misalignment between those who design, test, and are accountable for agent behavior.
Boris Cherny, head of Anthropic Claude Code, proposes five cognitive archetypes needed for teams in the AI era: Prototyper, Builder, Sweeper, Grower, and Maintainer, and discusses three selection criteria: cross-domain generalists, low ego, and empiricism.
A tweet shares an anecdote about NVIDIA's engineering culture, where the lack of layoffs fosters collaboration instead of internal competition.
A discussion between Kent C. Dodds and Sean Roberts on product engineering, planning with real business context, and the importance of conversations and curiosity over pure data.
The article analyzes the rapid decline of Meta's engineering culture, from a high-performance profit center to a demoralized cost center, driven by aggressive AI mandates, layoffs, and poor leadership decisions.
A tweet criticizes Coinbase's postmortem for their May 7, 2026 outage, noting that a $40B company should have basic resiliency like auto failover.