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Software engineering

I am an agile and pragmatic software engineer and technology consultant with a passion for driving innovation and excellence.

My role often transcends traditional boundaries, embodying the essence of an enabling team consultant, tech lead, architect, full stack developer, and QA.

Software engineering is a multifaceted discipline that has to integrate technology, social team dynamics, and business strategy. This makes software engineering a complex domain and many decisions are tradeoffs.

The only constant is change. Coding agents have moved the bottleneck from writing code to specifying intent and verifying results — and as review itself becomes automatable wherever the code is simple and well-tested, the constraint settles back onto intent. The work shifts from conductor to orchestrator: from pairing in dialogue to dispatching tasks that run autonomously for hours.

Technology

At the core of software engineering lies a robust set of technical practices encompassing programming, testing, debugging, and architectural design.

  • Clean code
  • Test-driven development (TDD)
  • Continuous integration and delivery (CI/CD)
  • Automated builds
  • Domain driven design (DDD)
  • Extreme programming (XP)
  • Shift security left with threat modeling
  • Object-functional programming
AI-assisted development

Working with coding agents does not remove the need for discipline — it relocates it. Rigor moves out of the code itself into the specifications, tests, and scaffolding that surround the agents. The mode shifts from conductor to orchestrator: from pairing in dialogue to dispatching tasks that run autonomously for hours — a double diamond (discover, define, develop, deliver) verified by AI agents, trustworthy only when the specs, the harness, and the QA gates are good enough.

  • Spec-driven development (SDD): the specification as the primary artifact, code as a derived one — intent is now the bottleneck
  • Engineer for reviewability: simple components and high branch coverage with BDD-style tests, so review can increasingly be automated
  • Context engineering: agent-readable conventions, steering files, and living documentation
  • AI as adversarial reviewer of requirements, designs, and code — not just as a generator
  • Keep humans in the loop where compliance, security, or business risk demands it
  • Vibe coding for prototypes and spikes, structured workflows for production
  • The durable craft is human: clear communication, abstract thinking, mental modelling

The longer treatment lives in two standalone sites: Software Development with AI, six essays on how the work moved from writing code to communicating intent and verifying output, and Lights On, Lights Off, a textbook on AI software factories — "lit" ones keep a human reading the diff, "dark" ones let machines verify machines.

Team collaboration

The success of software projects often hinges on the dynamics within development teams. Agile methodologies promote iterative cycles of planning, prioritization, and execution, fostering a collaborative environment where communication and fast feedback is key.

  • Pair programming
  • Team topologies
  • Four key metrics ("Accelerate"/DORA)
Operations

A strong DevOps culture, which blends development and operational activities, enhances the efficiency and reliability of software by fostering closer collaboration and integration between teams.

  • The three ways of the DevOps handbook: flow, feedback, continuous learning
Architecture

A decentralized approach to architectural decision-making is important, to empower teams to make choices based on their specific contexts and challenges.

  • Evolutionary architecture
Business alignment

The strategic aspect of software engineering involves aligning projects with the organization's broader goals and objectives. The overarching aim is to ensure that software engineering efforts support the organization's direction and add value.

  • Fast feedback, e.g. sprint reviews
  • Enterprise Architecture
  • Lean thinking

Standalone websites built with AI, one software engineering topic per site:

Software Development with AI — six essays on user stories, specs, and agentic practice

Software Development with AI

Software engineering

Six essays on what AI actually does to the practice of building software: writing code is no longer the bottleneck — the work moved to communicating intent upstream and verifying output downstream.

The Ten-Year Note — a 2026-2036 timeline for software development and consulting

The Ten-Year Note

Software engineering

A ten-year timeline (2026–2036) for software development and consulting, priced on one thesis: the artifact got cheap, the accountability didn’t. A claims audit and a nine-metric dashboard state in advance what would force a re-price.

Lights On, Lights Off — a tutorial on AI software factories, lit and dark

A textbook on AI software factories: “lit” ones keep a human reading the diff, “dark” ones let machines verify machines. Its advice is to earn the dark with evidence, one narrow loop at a time.

Ubiquitous — an eight-module introduction to Domain-Driven Design

Ubiquitous

Software engineering

An eight-module introduction to Domain-Driven Design — Ubiquitous Language, strategic design, tactical building blocks — taught through a single running order-fulfillment example.

Claude Code for Java Developers — a hands-on course for pairing with Claude Code on the JVM

A hands-on, eight-module course teaching Java and JVM developers to pair effectively with Claude Code — from first session to team-wide adoption, with Maven, Gradle, Spring, and JUnit examples throughout.

Open source on GitHub

A curated tour of my public repositories on github.com/jdinkla.

AI & agentic development tooling

  • claude-marketplace Plugin marketplace

    A personal Claude Code plugin marketplace — a catalog of plugins (skills, slash commands, agents, hooks) installable with one command.

  • software-craft Claude Code plugin

    Slash commands for high-level software engineering: architecture, Domain-Driven Design, Architecture Decision Records, and quality & maintenance work.

  • user-story-skills Claude Code plugin

    Skills and slash commands for user story refinement across the full lifecycle, from discovery through post-release — INVEST reviews, acceptance criteria, splitting, and more.

  • Turns a source essay into visual media — slide decks and single-page infographics — with multi-provider text and image generation.

  • pixbridge Python · PyPI

    Multi-provider AI image generation library with a unified client API across Gemini, OpenAI, and xAI. Published on PyPI.

Static analysis: the arclens family

Structural analysis tools that extract a codebase's architecture, compute coupling metrics, detect cycles, and render reports and diagrams — one tool per ecosystem.

  • arclens-kt Kotlin

    Static analysis for Kotlin codebases: dependency structure, coupling metrics, and architectural visualizations.

  • arclens-java Kotlin

    The same analysis for Java programs, implemented in Kotlin.

  • arclens-ts TypeScript

    Structural analysis for TypeScript and React codebases — afferent and efferent coupling, circular-dependency detection via Tarjan's SCC, Mermaid diagrams, and a self-contained HTML report.

Games & simulations

Browser-based, built with AI coding agents.

  • space-v-simulator TypeScript

    A management simulation that teaches the verification paradox: higher AI adoption generates more code while review capacity stays fixed — without investing in verification, delivery slows down.

  • vibe-crossword-tile-game TypeScript · React

    A Scrabble-like single-page game against an AI opponent with three difficulty levels — full rules, cross-word validation, bingo bonus.

  • city-guessing-game TypeScript · React

    Guess-the-city quiz: a red dot on a continent map, multiple-choice answers. Built with React and Leaflet.

  • flag-learning-game TypeScript

    A vibe-coded game for learning the flags of the world's countries.

  • Maze generation and solving algorithms from Jamis Buck's "Mazes for Programmers", with a solver arena where pathfinding algorithms race through generated mazes.

Ray tracing & algorithms

  • A Rust port of Jamis Buck's "The Ray Tracer Challenge", verified by the book's own Cucumber/Gherkin specs — 313 scenarios.

  • The same book implemented in Kotlin.

  • A ray tracer inspired by Kevin Suffern's "Ray Tracing from the Ground Up".

  • Nearest-neighbour search with k-d trees on Apache Spark.

  • GeomAlgLib Haskell

    A library of geometric algorithms and data structures for Haskell — convex hulls, triangulations, Voronoi diagrams — written in 1998 for my diploma thesis, and still building on a current GHC.

AI experiments

  • ai-playground Python

    Examples for the OpenAI API and LangChain.

  • ai-text2image Python

    Round-trip experiment: GPT describes an image, then an image model regenerates it from that description.

  • gemini-cli-news JavaScript

    A small RSS reader for InfoQ news, built to try out Google's gemini-cli.

Article & talk code

  • Example code for my JavaSpektrum article on Structured Concurrency — the JDK 24, 25, and 26 preview APIs kept side by side so the differences are easy to see.

  • Documents and code from the "Coding da Vinci Nord" 2016 culture hackathon, analyzing a family-names dataset.

The archive

Older talk and article code, kept read-only: Kotlin coroutines (parallel 2019) · structured concurrency warm-up (KKON 2021) · KKON 2022 talk · cuDNN example from iX Developer 2018 · GPU computing (parallel 2017) · parallel 2015 · parallel 2014 · parallel 2012 · email analysis with Spring Boot & Elasticsearch · disk-usage pie charts in Groovy · Eclipse Modeling Framework with Groovy · Common Warehouse Metamodel in EMF · family-name graphs via Levenshtein distance · Markov chains for Ruby Quiz 74 (2006).

Articles about Software Engineering

The seven wastes of software development
Jan 13, 2026 software-engineering

The seven wastes of software development

Lean Thinking is more than just a set of management tools; it is a philosophy centered on maximizing customer value while relentlessly eliminating waste. At its core, it challenges us...

#agile #project-management #quality-assurance
Read more
Nov 11, 2025 software-engineering

AI Crosses from Exploration into Engineering

The Thoughtworks Technology Radar has always been more than a list of tools. It captures what happens when technology moves from experimentation to everyday practice. In its 33rd edition, one...

#ai #gen-ai #thoughtworks
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Nov 01, 2025 software-engineering

Announcing NKP 0.1: Static Analysis for Kotlin Projects

I’m excited to share the first MVP release of NKP (aNalysis of Kotlin Programs), a command-line tool for analyzing Kotlin codebases and uncovering architectural insights.

#jvm #architecture #kotlin #object-functional #quality-assurance
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Java in the Technology Radar
Sep 03, 2025 software-engineering

Java in the Technology Radar (JavaSpektrum)

I’ve written a new article for JavaSpektrum: “Java im Technology Radar – Totgesagte leben länger”. The piece looks back at Java’s journey through the eyes of the Thoughtworks Technology Radar...

#java #article #jvm #thoughtworks
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Structured Concurrency in Java 24
Mar 31, 2025 software-engineering

Structured Concurrency in Java 24 (JavaSpektrum)

I’ve written an article for JavaSpektrum 2/2025 about Structured Concurrency in Java 24. The article covers JEP 499, Java’s fourth preview of Structured Concurrency, which aims to make concurrent programming...

#java #concurrency #article #jvm #parallelism
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Coroutines in Kotlin at KKon 2021 Warmup
Apr 23, 2021 software-engineering

Coroutines in Kotlin at KKon 2021 Warmup

In my talk “Nebenläufigkeit mit Koroutinen strukturieren” at the KKon 2021 Warmup I explained how to structure and organize concurrent programs with coroutines in Kotlin.

#kotlin #parallelism #concurrency #talk #slides
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