exploring-generative-ai

name	exploring-generative-ai
description	Use when evaluating coding assistants, agent autonomy, AI-assisted development workflows, context engineering, local coding-model viability, or software-engineering trade-offs using Martin Fowler's Exploring Generative AI series.

Exploring Generative AI

Series: Martin Fowler, Exploring Generative AI Sources: 29 official articles, published 2023-07-26 through 2026-07-08

How to Use

• Start with the Topic Index for a decision; then read every named chapter before making an article-specific claim.
• Use cheatsheet.md for a fast risk, autonomy, context, or local-model decision; read its cited chapters before acting.
• Use patterns.md when designing a workflow or harness; use glossary.md when terminology is unclear.
• Treat each chapter's source URL, author, and date as its authoritative metadata. Say a claim is not covered when no chapter supports it.

Core Decision Rules

Signal	Default action	Escalate when	Read
Output is plausible but unverified	Add the fastest trustworthy feedback: compiler, test, linter, review, or observable artifact.	Feedback is slow, ambiguous, or unavailable.	ch06, ch08, ch12
Probability of error is high, impact is high, or detectability is low	Do not use unsupervised execution; reduce scope and require human review.	A public API, security boundary, data change, or production behavior is involved.	ch16, ch19, ch21, ch27
Context is stale, broad, or causing guesses	Refresh the smallest relevant reference, specification, and workspace evidence; remove stale noise.	The agent cannot reliably decide what context to load.	ch09, ch22, ch25
Repeated agent misstep has a growing impact radius	Encode the missing judgment or constraint in a reusable skill or harness control.	It reaches team iteration or codebase-lifetime impact.	ch13, ch24, ch26
Considering a local model	Test the actual harness in sequence: memory fit, speed, tool calling, correctness, context, task size, and review burden.	Any earlier stage fails.	ch28, ch29

Chapter Index

#	Article	Author
1	The toolchain	Birgitta Böckeler
2	Median - A tale in three functions	Birgitta Böckeler
3	In-line assistance - when is it more useful?	Birgitta Böckeler
4	In-line assistance - how can it get in the way?	Birgitta Böckeler
5	Coding assistants do not replace pair programming	Birgitta Böckeler
6	TDD with GitHub Copilot	Paul Sobocinski
7	How is GenAI different from other code generators?	Birgitta Böckeler
8	How to tackle unreliability of coding assistants	Birgitta Böckeler
9	Onboarding to a 'legacy' codebase with the help of AI	Birgitta Böckeler
10	Building an AI agent application to migrate a tech stack	Birgitta Böckeler
11	Expanding the solution size with multi-file editing	Birgitta Böckeler
12	What role does LLM reasoning play for software tasks?	Birgitta Böckeler
13	The role of developer skills in agentic coding	Birgitta Böckeler
14	Guiding an LLM for Robust Java ByteBuffer Code	Unmesh Joshi
15	Building TMT Mirror Visualization with LLM: A Step-by-Step Journey	Unmesh Joshi
16	Coding Assistants Threaten the Software Supply Chain	Jim Gumbley、Lilly Ryan
17	Building Custom Tooling with LLMs	Unmesh Joshi
18	Autonomous coding agents: A Codex example	Birgitta Böckeler
19	I still care about the code	Birgitta Böckeler
20	Partner with the AI, throw away the code	Matteo Vaccari
21	To vibe or not to vibe	Birgitta Böckeler
22	Anchoring AI to a reference application	Birgitta Böckeler
23	Understanding Spec-Driven-Development: Kiro, spec-kit, and Tessl	Birgitta Böckeler
24	Assessing internal quality while coding with an agent	Erik Doernenburg
25	Context Engineering for Coding Agents	Birgitta Böckeler
26	Harness Engineering - first thoughts	Birgitta Böckeler
27	Humans and Agents in Software Engineering Loops	Kief Morris
28	Viability of local models for coding	Birgitta Böckeler
29	Experiences with local models for coding	Birgitta Böckeler

Topic Index

• AI output may be wrong / unreliable: ch04, ch06, ch08, ch12
• agentic coding / harness engineering: ch13, ch18, ch24, ch26, ch27
• autonomy, oversight, or high-risk execution: ch16, ch18, ch19, ch21, ch27
• code quality and review complacency: ch04, ch05, ch19, ch24
• context drift / reference application / context loading: ch09, ch22, ch25
• local-model viability: ch28, ch29
• prototype versus production: ch20, ch21, ch24
• risk assessment / vibe coding: ch19, ch21
• security and supply chain: ch16
• spec-driven development: ch23
• TDD: ch06, ch14

Supporting Files

• glossary.md — precise terms and source chapters.
• patterns.md — workflow patterns; read before designing a harness or repeated agent process.
• cheatsheet.md — decision tables; read before choosing autonomy, handling context drift, or evaluating a local model.

Scope and Limits

This skill covers only the 29 official URLs listed in the chapter files. It does not treat the series as a single-author book: chapter attribution remains article-specific. Do not infer claims beyond the cited article.