C:C05
Chapter 5: Quality, Architecture and Maintainability
A guide to the published second edition, with literal citations separated from wider editorial reading suggestions.
Chapter guide
Separates immediate correctness from architectural fit and maintenance obligations. Through duplication, post-merge evidence and a second change to the running service, it develops fitness checks and explicit stewardship instead of treating a passing test suite as complete quality assurance.
Sintesi in italiano
Distingue la correttezza immediata dalla coerenza architetturale e dagli obblighi di manutenzione. Duplicazioni, evidenze successive al merge e un secondo cambiamento al servizio guidano controlli di adeguatezza e responsabilità di manutenzione esplicite.
Learning goals
- review generated code for architectural fit as well as immediate correctness
- write fitness checks for critical system invariants
- locate who will maintain the result when the original agent and reviewer are gone
Obiettivi in italiano
Obiettivi di apprendimento
- sottoporre il codice generato a review non solo per la correttezza immediata, ma anche per la coerenza architetturale
- scrivere controlli di fitness per gli invarianti critici del sistema
- individuare chi si occuperà della manutenzione quando l'agent e il reviewer originari non saranno più disponibili
Chapter outline
- 5.1 What counts as code quality?
- 5.2 Reading AI-versus-human studies correctly
- 5.3 Code smells are signals, not incidents
- 5.4 Generated duplication and missed reuse
- 5.5 Architectural fit in a living codebase
- 5.6 Post-merge evolution and maintenance burden
- 5.7 Tracing quality across agents and projects
- 5.8 Authorship is not stewardship
- 5.9 A second change exposes the difference
- 5.10 Architecture fitness in the approval service
- 5.11 Worked engineering example: test the architecture, not just the output
- 5.12 Practice exercise: choose a maintainable implementation
Struttura del capitolo
- 5.1 Che cosa significa qualità del codice?
- 5.2 Come leggere correttamente gli studi che confrontano AI e sviluppatori
- 5.3 I code smell sono segnali, non incidenti
- 5.4 Duplicazioni generate e riuso trascurato
- 5.5 Coerenza architetturale in un codebase in evoluzione
- 5.6 Evoluzione dopo il merge e onere della manutenzione
- 5.7 Seguire la qualità tra agent e progetti
- 5.8 Scrivere il codice non significa esserne responsabili
- 5.9 È la seconda modifica a far emergere la differenza
- 5.10 Verificare l'architecture fitness nel servizio di approvazione
- 5.11 Esempio ingegneristico svolto: verificare l'architettura, non soltanto l'output
- 5.12 Esercizio pratico: scegliere un'implementazione manutenibile
Cited in the published chapter
18 linked atlas references from literal citations in the English and Italian editions. General bibliography membership and identifier-index entries are counted separately.
SE@PoliMi bibliography 17
- W001 — AI IDEs or Autonomous Agents? Measuring the Impact of Coding Agents on Software Development
Agarwal · 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 - W029 — Beyond Bug Fixes: An Empirical Investigation of Post-Merge Code Quality Issues in Agent-Generated Pull Requests
Cynthia · 2026 - W031 — More Code, Less Reuse: Investigating Code Quality and Reviewer Sentiment towards AI-generated Pull Requests
Huang · 2026 - W034 — Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance
Pinna · 2026 - W036 — On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub
Watanabe · 2026 - W039 — Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity
Cotroneo · 2025 - W044 — An Empirical Study of Code Clones from Commercial AI Code Generators
Wu · 2025 - W052 — What is the Difference Between Me and You? Benchmarking the Quality Gap Between Human-Written and AI-Generated Code
Improta · 2026 - W054 — Not All Agents Are Equal: Code Quality and Post-Merge Maintenance Across Five Autonomous Coding Agents in the Wild
Kraishan · 2026 - W055 — Debt Behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wild
Liu · 2026 - W057 — How Do AI Coding Agents Contribute to Software Development? An Empirical Study of Agentic Pull Requests
Mazloomzadeh · 2026 - W058 — Decoupling Code Complexity from Newcomer Participation: A Causal Study of AI Coding Agent Adoption in OSS
Xu · 2026 - W059 — AI-Generated Smells: An Analysis of Code and Architecture in LLM- and Agent-Driven Development
Zhu · 2026 - W175 — Code Ownership and Software Quality: A Replication Study
Greiler · 2015 - W182 — Don't Touch My Code! Examining the Effects of Ownership on Software Quality
Bird · 2011 - W189 — The Substrate Collapse: AI Code Generation Invalidates Authorship-Based Knowledge Metrics
Wheeler · 2026
Martin Fowler’s website 1
- F024 — Assessing internal quality while coding with an agent
Erik Doernenburg · 2026-01-27
Trace literal citations to chapter sections
Locations come from the supplied English and Italian source files. Chapter text and figure captions are identified separately; identifier-index references and general bibliography membership are not treated as chapter citations.
- F024 · Assessing internal quality while coding with an agent
- EN · What counts as code quality?
EN/chapters/chapter05.tex:14 - ITA · Che cosa significa qualità del codice?
ITA/chapters/chapter05.tex:14
- EN · What counts as code quality?
- W001 · AI IDEs or Autonomous Agents? Measuring the Impact of Coding Agents on Software Development
- EN · Code smells are signals, not incidents
EN/chapters/chapter05.tex:46 - ITA · I code smell sono segnali, non incidenti
ITA/chapters/chapter05.tex:46
- EN · Code smells are signals, not incidents
- W004 · Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projects
- EN · Code smells are signals, not incidents
EN/chapters/chapter05.tex:46 - ITA · I code smell sono segnali, non incidenti
ITA/chapters/chapter05.tex:46
- EN · Code smells are signals, not incidents
- W029 · Beyond Bug Fixes: An Empirical Investigation of Post-Merge Code Quality Issues in Agent-Generated Pull Requests
- EN · Reading AI-versus-human studies correctly
EN/chapters/chapter05.tex:28 - EN · Post-merge evolution and maintenance burden
EN/chapters/chapter05.tex:80 - EN · Post-merge evolution and maintenance burden
EN/chapters/chapter05.tex:85 - EN · Tracing quality across agents and projects
EN/chapters/chapter05.tex:103 - EN · Tracing quality across agents and projects
EN/chapters/chapter05.tex:105 - ITA · Come leggere correttamente gli studi che confrontano AI e sviluppatori
ITA/chapters/chapter05.tex:28 - ITA · Evoluzione dopo il merge e onere della manutenzione
ITA/chapters/chapter05.tex:80 - ITA · Evoluzione dopo il merge e onere della manutenzione
ITA/chapters/chapter05.tex:85 - ITA · Seguire la qualità tra agent e progetti
ITA/chapters/chapter05.tex:103 - ITA · Seguire la qualità tra agent e progetti
ITA/chapters/chapter05.tex:105
- EN · Reading AI-versus-human studies correctly
- W031 · More Code, Less Reuse: Investigating Code Quality and Reviewer Sentiment towards AI-generated Pull Requests
- EN · Generated duplication and missed reuse
EN/chapters/chapter05.tex:52 - EN · Architectural fit in a living codebase
EN/chapters/chapter05.tex:66 - ITA · Duplicazioni generate e riuso trascurato
ITA/chapters/chapter05.tex:52 - ITA · Coerenza architetturale in un codebase in evoluzione
ITA/chapters/chapter05.tex:66
- EN · Generated duplication and missed reuse
- W034 · Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance
- EN · Tracing quality across agents and projects
EN/chapters/chapter05.tex:109 - ITA · Seguire la qualità tra agent e progetti
ITA/chapters/chapter05.tex:109
- EN · Tracing quality across agents and projects
- W036 · On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub
- EN · Post-merge evolution and maintenance burden
EN/chapters/chapter05.tex:85 - EN · Tracing quality across agents and projects
EN/chapters/chapter05.tex:103 - ITA · Evoluzione dopo il merge e onere della manutenzione
ITA/chapters/chapter05.tex:85 - ITA · Seguire la qualità tra agent e progetti
ITA/chapters/chapter05.tex:103
- EN · Post-merge evolution and maintenance burden
- W039 · Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity
- EN · What counts as code quality?
EN/chapters/chapter05.tex:18 - EN · What counts as code quality?
EN/chapters/chapter05.tex:18 - EN · Reading AI-versus-human studies correctly
EN/chapters/chapter05.tex:34 - ITA · Che cosa significa qualità del codice?
ITA/chapters/chapter05.tex:18 - ITA · Che cosa significa qualità del codice?
ITA/chapters/chapter05.tex:18 - ITA · Come leggere correttamente gli studi che confrontano AI e sviluppatori
ITA/chapters/chapter05.tex:34
- EN · What counts as code quality?
- W044 · An Empirical Study of Code Clones from Commercial AI Code Generators
- EN · Generated duplication and missed reuse
EN/chapters/chapter05.tex:52 - ITA · Duplicazioni generate e riuso trascurato
ITA/chapters/chapter05.tex:52
- EN · Generated duplication and missed reuse
- W052 · What is the Difference Between Me and You? Benchmarking the Quality Gap Between Human-Written and AI-Generated Code
- EN · What counts as code quality?
EN/chapters/chapter05.tex:18 - EN · What counts as code quality?
EN/chapters/chapter05.tex:18 - EN · Reading AI-versus-human studies correctly
EN/chapters/chapter05.tex:34 - ITA · Che cosa significa qualità del codice?
ITA/chapters/chapter05.tex:18 - ITA · Che cosa significa qualità del codice?
ITA/chapters/chapter05.tex:18 - ITA · Come leggere correttamente gli studi che confrontano AI e sviluppatori
ITA/chapters/chapter05.tex:34
- EN · What counts as code quality?
- W054 · Not All Agents Are Equal: Code Quality and Post-Merge Maintenance Across Five Autonomous Coding Agents in the Wild
- EN · Reading AI-versus-human studies correctly
EN/chapters/chapter05.tex:30 - EN · Post-merge evolution and maintenance burden
EN/chapters/chapter05.tex:80 - EN · Post-merge evolution and maintenance burden
EN/chapters/chapter05.tex:85 - EN · Tracing quality across agents and projects
EN/chapters/chapter05.tex:103 - EN · Tracing quality across agents and projects
EN/chapters/chapter05.tex:105 - EN · Tracing quality across agents and projects
EN/chapters/chapter05.tex:109 - ITA · Come leggere correttamente gli studi che confrontano AI e sviluppatori
ITA/chapters/chapter05.tex:30 - ITA · Evoluzione dopo il merge e onere della manutenzione
ITA/chapters/chapter05.tex:80 - ITA · Evoluzione dopo il merge e onere della manutenzione
ITA/chapters/chapter05.tex:85 - ITA · Seguire la qualità tra agent e progetti
ITA/chapters/chapter05.tex:103 - ITA · Seguire la qualità tra agent e progetti
ITA/chapters/chapter05.tex:105 - ITA · Seguire la qualità tra agent e progetti
ITA/chapters/chapter05.tex:109
- EN · Reading AI-versus-human studies correctly
- W055 · Debt Behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wild
- EN · Code smells are signals, not incidents
EN/chapters/chapter05.tex:46 - ITA · I code smell sono segnali, non incidenti
ITA/chapters/chapter05.tex:46
- EN · Code smells are signals, not incidents
- W057 · How Do AI Coding Agents Contribute to Software Development? An Empirical Study of Agentic Pull Requests
- EN · Tracing quality across agents and projects
EN/chapters/chapter05.tex:109 - ITA · Seguire la qualità tra agent e progetti
ITA/chapters/chapter05.tex:109
- EN · Tracing quality across agents and projects
- W058 · Decoupling Code Complexity from Newcomer Participation: A Causal Study of AI Coding Agent Adoption in OSS
- EN · Authorship is not stewardship
EN/chapters/chapter05.tex:117 - ITA · Scrivere il codice non significa esserne responsabili
ITA/chapters/chapter05.tex:117
- EN · Authorship is not stewardship
- W059 · AI-Generated Smells: An Analysis of Code and Architecture in LLM- and Agent-Driven Development
- EN · Architectural fit in a living codebase
EN/chapters/chapter05.tex:66 - ITA · Coerenza architetturale in un codebase in evoluzione
ITA/chapters/chapter05.tex:66
- EN · Architectural fit in a living codebase
- W175 · Code Ownership and Software Quality: A Replication Study
- EN · Architectural fit in a living codebase
EN/chapters/chapter05.tex:66 - ITA · Coerenza architetturale in un codebase in evoluzione
ITA/chapters/chapter05.tex:66
- EN · Architectural fit in a living codebase
- W182 · Don't Touch My Code! Examining the Effects of Ownership on Software Quality
- EN · Authorship is not stewardship
EN/chapters/chapter05.tex:117 - ITA · Scrivere il codice non significa esserne responsabili
ITA/chapters/chapter05.tex:117
- EN · Authorship is not stewardship
- W189 · The Substrate Collapse: AI Code Generation Invalidates Authorship-Based Knowledge Metrics
- EN · Authorship is not stewardship
EN/chapters/chapter05.tex:117 - ITA · Scrivere il codice non significa esserne responsabili
ITA/chapters/chapter05.tex:117
- EN · Authorship is not stewardship
Editorial reading mappings
Broader topical suggestions can overlap the cited sources. A mapping does not add a citation to the published edition or establish that a practice is effective.
SE@PoliMi bibliography 56
- W001 — AI IDEs or Autonomous Agents? Measuring the Impact of Coding Agents on Software Development
Agarwal · 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 - W021 — The AI Engineering Report 2026: The Acceleration Whiplash
Faros AI · 2026 - W024 — 2025 State of AI-Assisted Software Development
Google Cloud DORA · 2025 - W029 — Beyond Bug Fixes: An Empirical Investigation of Post-Merge Code Quality Issues in Agent-Generated Pull Requests
Cynthia · 2026 - W030 — Workspace Topology as an Attack Vector in Agentic Coding Assistants
Day · 2026 - W031 — More Code, Less Reuse: Investigating Code Quality and Reviewer Sentiment towards AI-generated Pull Requests
Huang · 2026 - W032 — Understanding the Impact of AI Code Assistants on Security API Usage
Mousavi · 2026 - W033 — How AI Coding Agents Modify Code: A Large-Scale Study of GitHub Pull Requests
Ogenrwot · 2026 - W034 — Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance
Pinna · 2026 - W035 — Security in the Age of AI Teammates: An Empirical Study of Agentic Pull Requests on GitHub
Siddiq · 2026 - W036 — On the Use of Agentic Coding: An Empirical Study of Pull Requests on GitHub
Watanabe · 2026 - W037 — After the Party: Growth, Governance, and Security Scanning in the OpenClaw Agent Skill Ecosystem
Xiong · 2026 - W038 — Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation
Yan · 2026 - W039 — Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity
Cotroneo · 2025 - W040 — Security Weaknesses of Copilot-Generated Code in GitHub Projects: An Empirical Study
Fu · 2025 - W041 — Security Vulnerabilities in AI-Generated Code: A Large-Scale Analysis of Public GitHub Repositories
Schreiber · 2025 - W042 — Security Degradation in Iterative AI Code Generation: A Systematic Analysis of the Paradox
Shukla · 2025 - W043 — We Have a Package for You! A Comprehensive Analysis of Package Hallucinations by Code Generating LLMs
Spracklen · 2025 - W044 — An Empirical Study of Code Clones from Commercial AI Code Generators
Wu · 2025 - W045 — Is Vibe Coding Safe? Benchmarking Vulnerability of Agent-Generated Code in Real-World Tasks
Zhao · 2025 - W046 — Do Users Write More Insecure Code with AI Assistants?
Perry · 2023 - W047 — Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants
Sandoval · 2023 - W048 — Asleep at the Keyboard? Assessing the Security of GitHub Copilot's Code Contributions
Pearce · 2022 - W049 — The Range Shrinks, the Threat Remains: Re-evaluating LLM Package Hallucinations on the 2026 Frontier-Model Cohort
Churilov · 2026 - W050 — Understanding the (In)Security of Vibe-Coded Applications
Deng · 2026 - W051 — From Conversation to Contribution: Characterizing Coding Agent in Open-Source Software
Fang · 2026 - W052 — What is the Difference Between Me and You? Benchmarking the Quality Gap Between Human-Written and AI-Generated Code
Improta · 2026 - W053 — Scanning the Harness: Configuration Exposures in AI Coding-Agent Supply Chains
Kapner · 2026 - W054 — Not All Agents Are Equal: Code Quality and Post-Merge Maintenance Across Five Autonomous Coding Agents in the Wild
Kraishan · 2026 - W055 — Debt Behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wild
Liu · 2026 - W056 — A Large-Scale Comprehensive Measurement of AI-Generated Code in Real-World Repositories
Mao · 2026 - W057 — How Do AI Coding Agents Contribute to Software Development? An Empirical Study of Agentic Pull Requests
Mazloomzadeh · 2026 - W058 — Decoupling Code Complexity from Newcomer Participation: A Causal Study of AI Coding Agent Adoption in OSS
Xu · 2026 - W059 — AI-Generated Smells: An Analysis of Code and Architecture in LLM- and Agent-Driven Development
Zhu · 2026 - W060 — Your AI, My Shell: Demystifying Prompt Injection Attacks on Agentic AI Coding Editors
Liu · 2025 - W061 — 2025 GenAI Code Security Report
Veracode · 2025 - W062 — Vibe Security Radar
Zhao · 2026 - W063 — An Endless Stream of AI Slop: How Developers Discuss the Burden of AI-Assisted Software Development
Baltes · 2026 - W067 — (Don't) Trust, but (Don't) Verify: Developers' Attention to Security in AI-Generated Code
Khalid · 2026 - W073 — The Effect of Complexity and Provenance on Code Review Decisions: Evidence from a Controlled Experiment
Singh · 2026 - W077 — Evaluating and Mitigating the Misguidance Effect of Buggy Code in LLM-Generated Unit Tests
Zhao · 2026 - W091 — Automation bias and verification complexity: a systematic review
Lyell · 2017 - W095 — Beyond Code Generation: Reliability, Verification, and Cost Economics in the Agentic Software Development Lifecycle
Bhati · 2026 - W104 — Coding with Enemy: Can Human Developers Detect AI Agent Sabotage?
Ye · 2026 - W106 — Code Review Agent Benchmark (c-CRAB)
Zhang · 2026 - W149 — Making AI Visible, Not Vanished: How AI Policies Reshape Developer Experience on GitHub
Chen · 2026 - W150 — We Permit the Use of AI, but [...]: The Landscape of AI Policies in Popular Open Source Projects
Hora · 2026 - W152 — Agentic Software Engineering: Foundational Pillars and a Research Roadmap
Hassan · 2026 - W154 — Comprehension Debt in GenAI-Assisted Software Engineering Projects
Ahmad · 2026 - W161 — Examining ownership models in software teams: A systematic literature review and a replication study
Koana · 2024 - W164 — Program Comprehension and Code Complexity Metrics: An fMRI Study
Peitek · 2021 - W174 — Impact of Developer Turnover on Quality in Open-Source Software
Foucault · 2015 - W175 — Code Ownership and Software Quality: A Replication Study
Greiler · 2015 - W182 — Don't Touch My Code! Examining the Effects of Ownership on Software Quality
Bird · 2011 - W189 — The Substrate Collapse: AI Code Generation Invalidates Authorship-Based Knowledge Metrics
Wheeler · 2026
Addy Osmani 5
- O007 — Agentic Code Quality
Addy Osmani · 2026-08-08 - O027 — How modern browsers work
Addy Osmani · 2025-09-13 - O037 — Vibe Coding is not an excuse for low-quality work
Addy Osmani · 2025-04-18 - O039 — Vibe Coding: Revolution or Reckless Abandon?
Addy Osmani · 2025-04-03 - O051 — Agentic Verification
Addy Osmani · 2026-10-14
The Pragmatic Engineer 31
- P013 — How Shopify Built Its Live Globe for Black Friday
Gergely Orosz · 2024-12-17 - P015 — Bug management that works (Part 2)
Gergely Orosz; Elin Nilsson · 2025-01-07 - P017 — Cross-platform mobile development
Gergely Orosz; Elin Nilsson; Fatos Morina · 2025-01-14 - P020 — Taking on Google search: Perplexity and Kagi
Gergely Orosz · 2025-01-28 - P021 — Cross-platform mobile development with Expo
Gergely Orosz; Elin Nilsson · 2025-02-04 - P027 — Robotics for software engineers: Part 1
Gergely Orosz; Sandor Felber · 2025-02-25 - P032 — AI Engineering in the real world
Gergely Orosz · 2025-03-25 - P037 — Humanoid robots for software engineers (Robotics for software engineers, Part 2)
Gergely Orosz; Sandor Felber · 2025-04-29 - P039 — Building, launching, and scaling ChatGPT Images
Gergely Orosz · 2025-05-13 - P041 — The AI Engineering Stack
Gergely Orosz; Chip Huyen · 2025-05-20 - P044 — Real-world engineering challenges: building Cursor
Gergely Orosz · 2025-06-10 - P049 — Skills useful to learn for robotics engineering (Robotics for software engineers, Part 3)
Gergely Orosz; Sandor Felber · 2025-07-08 - P051 — Why reliability is hard at scale: learnings from infrastructure outages
Gergely Orosz · 2025-07-22 - P053 — Building great SDKs
Gergely Orosz; Quentin Pradet · 2025-07-29 - P063 — Inside Google’s Engineering Culture: the Tech Stack (Part 2)
Gergely Orosz; Elin Nilsson · 2025-09-30 - P066 — What is good software architecture?
Gergely Orosz; Matthew Hawthorne · 2025-10-21 - P067 — What caused the large AWS outage?
Gergely Orosz · 2025-10-23 - P076 — Downdetector and the real cost of no upstream dependencies
Gergely Orosz · 2025-12-05 - P079 — How AWS deals with a major outage
Gergely Orosz · 2025-12-16 - P081 — Design Systems for Software Engineers
Gergely Orosz; Michael Abernethy · 2026-01-13 - P082 — The Product-Minded Engineer: The importance of good errors and warnings
Gergely Orosz (interview/introduction); Drew Hoskins (excerpt) · 2026-01-20 - P094 — What is inference engineering? Deepdive
Gergely Orosz (introduction); Philip Kiely (guest excerpt) · 2026-03-31 - P097 — How will AI change operating systems? Part 1: Ubuntu and Linux
Gergely Orosz · 2026-04-28 - P101 — AI’s impact on software engineers in 2026: key trends, Part 2
Gergely Orosz; Elin Nilsson · 2026-05-19 - P105 — Why is Meta destroying its engineering organization?
Gergely Orosz · 2026-06-16 - P106 — Reliability fail: No automated zone failover for Coinbase’s global trading service
Gergely Orosz · 2026-06-23 - P111 — Pushing software engineering limits with “napkin math”
Gergely Orosz · 2026-07-21 - P113 — Software engineering at a proprietary trading company: Optiver
Gergely Orosz; Ivan Klaric; Jesse Spevack · 2026-08-11 - P120 — How will AI change operating systems? Part 2: Windows
Gergely Orosz; Ivan Klaric · 2026-09-22 - P121 — Why has Shopify dropped React Native?
Gergely Orosz · 2026-09-29 - P124 — Building resilient AI-powered software, and planning for when things go wrong
Gergely Orosz (introduction); Sam Newman (excerpts) · 2026-10-13
Martin Fowler’s website 17
- F002 — Median - A tale in three functions
Birgitta Böckeler · 2023-07-27 - F004 — In-line assistance - how can it get in the way?
Birgitta Böckeler · 2023-08-03 - F007 — How is GenAI different from other code generators?
Birgitta Böckeler · 2023-09-19 - F009 — Onboarding to a 'legacy' codebase with the help of AI
Birgitta Böckeler · 2024-08-15 - F010 — Building an AI agent application to migrate a tech stack
Birgitta Böckeler · 2024-08-20 - F011 — Expanding the solution size with multi-file editing
Birgitta Böckeler · 2024-11-19 - F013 — The role of developer skills in agentic coding
Birgitta Böckeler · 2025-03-25 - F014 — Guiding an LLM for Robust Java ByteBuffer Code
Unmesh Joshi · 2025-04-17 - F017 — Building Custom Tooling with LLMs
Unmesh Joshi · 2025-05-14 - F018 — Autonomous coding agents: A Codex example
Birgitta Böckeler · 2025-06-04 - F019 — I still care about the code
Birgitta Böckeler · 2025-07-09 - F020 — Partner with the AI, throw away the code
Matteo Vaccari · 2025-07-31 - F022 — Anchoring AI to a reference application
Birgitta Böckeler · 2025-09-25 - F024 — Assessing internal quality while coding with an agent
Erik Doernenburg · 2026-01-27 - F026 — Harness Engineering - first thoughts
Birgitta Böckeler · 2026-02-17 - F030 — The Economic Benefit of Refactoring
Giles Edwards-Alexander · 2026-07-30 - F035 — When Software Meets Hardware
Kuldeep Singh · 2026-10-15
Earlier Non-Deterministic books 8
- B008 — The Quality Crisis (And How to Prevent It)
Enrico Papalini · - B014 — PART II: Quality Assurance
Enrico Papalini · - B026 — Development Practices Enhanced by AI
Enrico Papalini · - B054 — The Specification Toolkits: Spec Kit and OpenSpec (openspec.dev)
Enrico Papalini · - B059 — Constitution and Architecture: The Framework Foundation
Enrico Papalini · - B072 — OpenSpec (openspec.dev)
Enrico Papalini · - B081 — AIDD
Enrico Papalini · - B107 — The Ralph Loop: Persistent Progress Through Fresh Context
Enrico Papalini ·