// Topics / Productivity

Productivity

    Your AI Tool Needs an Adoption SLO Seat counts can't justify an AI tool renewal. Define one adoption SLI, governed completions over eligible cases, with guardrails and a breach rule. ai operations metrics Stop Building Internal AI Tools No One Uses Internal AI tools die quietly when teams optimize for launch over workflow fit, output trust, and post-launch ownership. One tool failed, one stuck. productivity ai leadership Why Most AI Platform Teams Become the New Bottleneck Canon post — AI platform teams become bottlenecks when they centralize decisions instead of capabilities. The warning signs, the metrics that expose it, and the fix. platform-engineering ai teams The Throughput Engineer: Why Headcount Is a Lagging Metric Canon post — Headcount is a lagging metric. The best engineering organizations measure throughput: decision speed, defect containment, and constraint removal. leadership productivity operations AI and Team Productivity: Shared Infrastructure Wins Individual AI speedups are a distraction. The real gains come from treating AI as team infrastructure, embedded in docs, decisions, and onboarding. productivity ai teams AI Pair Programming: It's a Junior Dev, Not a Wizard Treat AI coding assistants like a fast, literal junior dev: tight constraints, critical review, and no expectations of architectural insight. ai engineering productivity AI Coding Assistant Productivity: Three Months of Numbers Three months tracking Copilot and GPT-4 on real Go work: 25-30% faster on boilerplate, no gain on debugging, and a 15% review tax on AI-written code. ai developer-experience productivity GitHub Copilot After Six Months: Faster Drafts, More Review Six months with Copilot in real projects. What it actually helps with, where it quietly makes things worse, and why the productivity claims are overblown. ai developer-experience productivity Engineering Metrics: DORA, Error Budgets, and DevEx Signals Most engineering metrics measure activity. The few worth tracking: DORA, user-facing reliability with error budgets, developer friction, and outcomes. metrics leadership productivity DORA Metrics: Keep Them Off Performance Reviews DORA metrics work until someone puts them on a performance review. How to define, collect, and use them at team level without gaming. metrics devops productivity GitHub Copilot: First Impressions From a Go Developer Early notes from GitHub Copilot's technical preview on Go code: strong on boilerplate and tests, wrong on domain logic, unresolved on licensing. developer-experience ai go Remote Work for Engineering Teams: Benefits and Dangers Years of running distributed engineering teams: what remote work gives you, where it hurts (isolation, blurred boundaries, eroding trust), and what works. remote-work leadership teams Developer Productivity Metrics: Why I Only Trust DORA Lines of code, commit counts, and velocity charts fail as developer productivity metrics. The four DORA metrics, tracked per team, are worth your time. productivity metrics engineering Developer Experience: Internal Platforms vs Ad-Hoc Tooling Purpose-built internal platforms versus the scripts and Makefiles teams grow themselves, and the team size and pain at which each one wins. developer-experience platform-engineering devops