T:Productivity
Productivity
Current source memberships across the atlas. A source can address more than one stream.
SE@PoliMi bibliography 32
- W001 — AI IDEs or Autonomous Agents? Measuring the Impact of Coding Agents on Software Development
Agarwal · 2026 - W002 — Code with Me or for Me? How Increasing AI Automation Transforms Developer Workflows
Chen · 2026 - W003 — The Effects of Generative AI on High-Skilled Work: Evidence from Three Field Experiments with Software Developers
Cui · 2026 - W004 — Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projects
He · 2026 - W005 — Early Adoption of Agentic Coding Tools by GitHub Projects
Raida · 2026 - W006 — Agentic Much? Adoption of Coding Agents on GitHub
Robbes · 2026 - W007 — Usage, Effects and Requirements for AI Coding Assistants in the Enterprise: An Empirical Study
Merler · 2026 - W008 — How Much Does AI Impact Development Speed? An Enterprise-Based Randomized Controlled Trial
Paradis · 2025 - W009 — Productivity Assessment of Neural Code Completion
Ziegler · 2022 - W010 — Writing Code vs. Shipping Code: Productivity Effects Across Generations of AI Coding Tools
Demirer · 2026 - W011 — The Productivity-Reliability Paradox: Specification-Driven Governance for AI-Augmented Software Development
Farrag · 2026 - W012 — Agentic Coding in the Wild: Characterizing GitHub Copilot Traces at Production Scale
Liu · 2026 - W013 — Quantifying the Expectation-Realisation Gap for Agentic AI Systems
Lobentanzer · 2026 - W014 — Adoption and Impact of Command-Line AI Coding Agents: A Study of Microsoft's Early 2026 Rollout of Claude Code and GitHub Copilot CLI
Murphy-Hill · 2026 - W015 — Agentic Delegation and the Language Frontier of Software Developers: A Model and Evidence from Claude Code on GitHub
Quispe · 2026 - W016 — The Impact of AI Coding Assistants on Software Engineering: A Longitudinal Study
Vella · 2026 - W017 — Randomized Controlled Trials for Conditional Access Optimization Agent
Bono · 2025 - W018 — Intuition to Evidence: Measuring AI's True Impact on Developer Productivity
Kumar · 2025 - W019 — Generative AI and labour productivity: a field experiment on coding
Gambacorta · 2024 - W020 — Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity
Becker · 2026 - W021 — The AI Engineering Report 2026: The Acceleration Whiplash
Faros AI · 2026 - W022 — AI Coding Agents: Adoption Trends
JetBrains Research · 2026 - W023 — Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
Becker · 2025 - W024 — 2025 State of AI-Assisted Software Development
Google Cloud DORA · 2025 - W025 — Estimating AI productivity gains from Claude conversations
Tamkin · 2025 - W026 — Accelerate State of DevOps Report 2024
Google Cloud DORA · 2024 - W027 — Beyond the Copilot: Scaling the Agentic Product Development Life Cycle
Relyea · 2026 - W028 — The AI Revolution in Software Development
Relyea · 2026 - W057 — How Do AI Coding Agents Contribute to Software Development? An Empirical Study of Agentic Pull Requests
Mazloomzadeh · 2026 - W074 — RovoDev Code Reviewer: A Large-Scale Online Evaluation of LLM-based Code Review Automation at Atlassian
Tantithamthavorn · 2026 - W118 — How AI Impacts Skill Formation
Shen · 2026 - W145 — ROI of AI-Assisted Software Development
DORA · 2026
Addy Osmani 4
- O029 — The reality of AI-Assisted software engineering productivity
Addy Osmani · 2025-08-16 - O042 — Beyond the 70%: Maximizing the human 30% of AI-assisted coding
Addy Osmani · 2025-03-13 - O044 — Speech-to-Code: Vibe Coding with Voice
Addy Osmani · 2025-02-28 - O049 — The 70% problem: Hard truths about AI-assisted coding
Addy Osmani · 2024-12-04
The Pragmatic Engineer 24
- P008 — IDEs with GenAI features that Software Engineers love
Gergely Orosz · 2024-11-26 - P014 — How AI-assisted coding will change software engineering: hard truths
Gergely Orosz; Addy Osmani · 2025-01-05 - P021 — Cross-platform mobile development with Expo
Gergely Orosz; Elin Nilsson · 2025-02-04 - P031 — What is Growth Engineering?
Gergely Orosz; Alexey Komissarouk · 2025-03-20 - P038 — What’s Changed in 50 Years of Computing: Part 4
Gergely Orosz · 2025-05-06 - P042 — Microsoft is dogfooding AI dev tools’ future
Gergely Orosz · 2025-05-27 - P047 — Learnings from two years of using AI tools for software engineering
Gergely Orosz; Birgitta Böckeler · 2025-06-24 - P048 — Software engineering with LLMs in 2025: reality check
Gergely Orosz · 2025-07-01 - P050 — The Pragmatic Engineer 2025 Survey: What’s in your tech stack? Part 1
Gergely Orosz; Elin Nilsson · 2025-07-15 - P052 — Cursor makes developers less effective?
Gergely Orosz · 2025-07-24 - P056 — The Pragmatic Engineer 2025 Survey: What’s in your tech stack? Part 2
Gergely Orosz; Elin Nilsson · 2025-08-19 - P061 — How tech companies measure the impact of AI on software development
Gergely Orosz; Laura Tacho · 2025-09-16 - P078 — Frictionless: why great developer experience can help teams win in the ‘AI age’
Gergely Orosz (introduction/interview); Nicole Forsgren; Abi Noda (excerpts) · 2025-12-10 - P083 — Inside a five-year-old startup’s rapid AI makeover
Gergely Orosz · 2026-01-27 - P084 — I replaced a $120/year micro-SaaS in 20 minutes with LLM-generated code
Gergely Orosz · 2026-01-29 - P085 — Deepdive: How 10 tech companies choose the next generation of dev tools
Gergely Orosz · 2026-02-03 - P089 — AI Tooling for Software Engineers in 2026
Gergely Orosz; Elin Nilsson · 2026-03-03 - P091 — Are AI agents actually slowing us down?
Gergely Orosz · 2026-03-17 - P100 — Revisiting “No Silver Bullets” in the age of AI
Gergely Orosz · 2026-05-12 - P103 — Ideas: slow down to speed up when working with AI agents
Gergely Orosz · 2026-06-02 - P107 — Slow down to speed up: so much has changed in 6 months’ time
Gergely Orosz · 2026-06-23 - P112 — How building software is changing at Anthropic
Gergely Orosz · 2026-07-28 - P121 — Why has Shopify dropped React Native?
Gergely Orosz · 2026-09-29 - P122 — The state of the tech industry in 2026
Gergely Orosz · 2026-10-06
Martin Fowler’s website 6
- F001 — The toolchain
Birgitta Böckeler · 2023-07-26 - F003 — In-line assistance - when is it more useful?
Birgitta Böckeler · 2023-08-01 - F017 — Building Custom Tooling with LLMs
Unmesh Joshi · 2025-05-14 - F020 — Partner with the AI, throw away the code
Matteo Vaccari · 2025-07-31 - F029 — Experiences with local models for coding
Birgitta Böckeler · 2026-07-08 - F035 — When Software Meets Hardware
Kuldeep Singh · 2026-10-15
Earlier Non-Deterministic books 35
- B001 — Introduzioni alle parti — Non-Deterministic Software Engineering
Enrico Papalini · - B003 — Summary
Enrico Papalini · - B009 — Measuring What Matters---The Data Behind AI's Real Impact
Enrico Papalini · - B010 — The Adaptation Imperative---What Companies Must Do Now
Enrico Papalini · - B016 — PART IV: Organizational Foundation
Enrico Papalini · - B017 — Pattern Recap: Quick Reference Guide
Enrico Papalini · - B018 — Antipatterns: What Not to Do
Enrico Papalini · - B019 — Tools \& Practices
Enrico Papalini · - B020 — Understanding Tool Maturity Levels
Enrico Papalini · - B021 — Getting Started: Choosing Your Primary Tool
Enrico Papalini · - B029 — Measurement \& Observability
Enrico Papalini · - B031 — First 90-Days Implementation Roadmap
Enrico Papalini · - B032 — Quick Reference Guides
Enrico Papalini · - B033 — Expert Insights
Enrico Papalini · - B037 — Preface
Enrico Papalini · - B043 — Limitations and Judgment
Enrico Papalini · - B046 — Playbook Quick Reference
Enrico Papalini · - B048 — Preface
Enrico Papalini · - B052 — The Ecosystem: A Map of Public Frameworks
Enrico Papalini · - B057 — The Comparison: Patterns, Divergences, and Convergences
Enrico Papalini · - B058 — Design Boundaries: What to Adopt, What to Avoid
Enrico Papalini · - B062 — Autonomous Execution: Modes, Budgets, and Governance
Enrico Papalini · - B064 — Limitations and Professional Judgment
Enrico Papalini · - B066 — Installation and Setup
Enrico Papalini · - B069 — Framework Reference Cards
Enrico Papalini · - B084 — Preface
Enrico Papalini · - B096 — Safety, Security, and Risk Management
Enrico Papalini · - B098 — Tool Reference
Enrico Papalini · - B099 — Troubleshooting and Debugging
Enrico Papalini · - B100 — Ralph Loops with VS Code and GitHub Copilot
Enrico Papalini · - B103 — Summary
Enrico Papalini · - B106 — The Economics of Loop Engineering
Enrico Papalini · - B108 — Building a Full Local AI Loop
Enrico Papalini · - B109 — Choosing the Right Loop
Enrico Papalini · - B110 — References — 85 voci bibliografiche
Enrico Papalini ·
Software Engineering Practices 16
- PAT:003 — Background Agent CI
- PAT:009 — CI-as-Backpressure
- PAT:010 — Inference-Healed Code Review
- PAT:019 — Subagent Spawning and Fan-Out
- PAT:022 — Trust Calibration
- PAT:031 — Worktrees: Isolate the Write Domains
- PAT:032 — Multi-Loop Coordination: One Owner per Target
- PAT:035 — Daily Triage: rank the rare urgent item
- PAT:039 — PR babysitter
- PAT:052 — Review Gauntlet
- PAT:056 — Parallel Work Orchestration
- PAT:057 — Structured Enablement Program
- PAT:059 — Measurement & Learning
- PAT:074 — Anti-Sycophancy Enforcement
- PAT:075 — Convergence Review
- PAT:084 — Escalation Protocol