DDD, the Natural Evolution of the IT Industry

Eric Evans published the original book about DDD, “Domain-Driven Design, Tackling Complexity in the Heart of Software, ” in 2004. It took more than 10 years to become a thing and even longer to not be considered “exotic” and “a theoretical but unnecessarily complicated paradigm.”

In 2024, DDD can be considered a commodity in the sense of the word defined in Wardley mapping (at least in Europe). There are conferences with thousands of attendees, new books every year, and tech start-ups looking for engineers with DDD experience or at least awareness. As usual in this young industry full of people packing old ideas in shiny new envelopes and selling them for the big bucks, one question returns: “Is DDD a hype?”.

The picture in the header of this post is from computerhistory.org (thank you). It shows the first Colossus operational at Bletchley Park in 1944. Computers and information technology, in general, have changed since that picture, going from punched cards to cloud computing and AI. The key booster was the Internet, paving the way to “Space, the final frontier… to boldly go where no man (and women and everything in-between) has gone before” (Star Trek: Enterprise).

When I became a software developer in 2003, the usual jobs were automating manual processes, connecting servers, and using the web to communicate with users instead of snail mail and fax. (Ok, in Germany, both are still heavily used 🙈.)

The main goal was to ease the sellers’ jobs and day-to-day lives. SaaS was just defined. Software was used to automate existing manual processes, hence slow processes. Understanding the business domain was not important because the innovation was done on the technical level. Engineers could lay back and let product managers and designers tell you everything they need from a computer to execute —ideally, as an ordered list, in very exact words 🤓.

Then, mobile phones became the rulers of our lives. They were more powerful than personal computers, not only because of their RAM and CPU but also because they were portable. They allowed us to take and share pictures and videos, ask for timetables, buy tickets, and look for weather changes while moving. 24 hours a day. The differentiators of a product changed from “how usable” to “how easy to use” and “how fast it evolves”. The colour of a button became irrelevant compared to the whole user experience and the user’s perception of a product. 

Today, anyone with a logical brain can learn and write software. Infrastructure is cheap and easily accessible without a substantial up-front investment. Being on-demand, companies can run short-term experiences without significant risks. Understanding tech is no longer a key differentiator. Understanding the User became the key to sustainable market shares.

After the phase of simply automating existing processes followed at work or to achieve a goal, the game has changed. Engineers must not only ensure that the software they create works and is maintainable (readable and extendable) with an acceptable effort, but they also must not ignore the “world outside of bits and bytes” anymore. Product development needs to be collaborative work. Adapting to new market needs, trying new ways, and getting fast feedback are more important than ever. These experiments are not about technology (the users don’t really care if we use MySQL or MongoDB) but about speeding up the users to get their jobs done

“Are you telling me I can’t build software that solves users’ needs without DDD?! ” That’s a valid remark; I am not. Developers have always written software to solve someone’s goals, even pet projects. 

The need for collaboration changes the rules of the game. It changes how we work, understand the underlying problem, and decide what to build (and what not). During collaborative discovery, the user leaves the desks of the product managers and designers and joins our commonly maintained miro boards. DDD enables us to represent the domain understanding in our software and organisation. The strategic design of DDD gives us options for the future without knowing what the future will look like. The tactical patterns give us strong weapons against continuously deteriorating software. DDD unveils how useless questions like “How small is a micro-service?” are. It eliminates the (again) useless answer “It depends”. The answer depends on the context. When asked in a digital context, the answer must always be put in the context of the user’s needs and the socio-technical organisation. It does not depend on the mood of the consultant.

Unlike the usual cases, when an old solution is hyped again in a refurbished version, DDD is not a paradigm invented, forgotten and resurrected after years. It is a paradigm for solving problems in a way that has always been valid, but until a few years ago, it has not been considered important enough. It has needed years of businesses wasting money, engineers feeling the pain while handling “big bulls of mud” and anger because “the requirements have changed” and the technical decisions of the past became a heavy blocker instead of an enabler.

Example for an event storming
Event storming with domain experts

Feedback-Based Development

Roman theatre in St. Albans, GB

Important things need to grow to last. The German says “gut ding will weile haben” – good things take time.

The Roman Theatre of Verulamium (St.Albans) built in about 140AD

I did it: almost exactly four years after Nick Tune suggested me a conference in London as the best place to start talking at conferences, I had my first in-person talk at the DDD Meetup in London. Given the timespan, you could say, “What is so special in this? Why should I continue reading?”. Well, you don’t need to 😀. For me, it feels like quite a wonder that by looking at where I was four years ago (I was completely unknown in the international community) and what happened in the meantime, I can put a ✅behind this bucket list item.

Writing about the last four years would transform this post into a small book – I won’t do that now. Instead, I will tell you a bit about the talk and how I applied the same ideas to prepare for it. The talk is about Feedback-driven Product Development. This post is about Feedback-driven Self-Development😉.

Shifting from Projects to Feedback-Based Product Development
slides on miro

With this talk, I wanted to show how broken our product development processes, long and short-term outcomes, hell, the whole industry is, and they don’t need to be! We have everything we need to improve our life as product developers to enjoy this most creative job, but instead, we feel frustrated, overwhelmed and not fulfilled. In the presentation, I talked about the three things organisations (or single persons) can use to change this.

Disclaimer: I don’t mean software developers here. I mean all the different roles and skills needed to create something good.

Now back to the story I want to tell you: how did I use these three ideas to develop the talk and myself at the same time?

Optimise For the Time to Learn

As I said, I have never written a talk with slides and all. I have even switched from Windows to Linux to never land in a situation where I needed to write a PowerPoint presentation. But the talk itself is only the output, it is not my goal. My goal is to learn if I can do this, if I am good at it. If I enjoy it? I started to speak in international circles on Virtual DDD, and the pandemic made it very easy to meet great people. After three years of interactions, it felt natural to me. We became online friends. Last year I proposed my first workshop at the biggest DDD conference in Europe because I wanted to meet them and knew that I wouldn’t be able to support the trip financially otherwise. It worked, and now I am part of this very special community. It stopped becoming a challenge; I needed something new: a talk presented on a podium, completely out of my comfort zone.

You need to know that I am not a consultant (and I still don’t want to become one), so there are not too many reasons for all the effort needed to travel abroad to conferences and give a high-quality workshop or talk. One (and still the main reason) is to meet and exchange with other nerds. The other is my personal development: can I do this? Where are my boundaries?

So that in January, Nick convinced me to dare the next step. We agreed on a date and on a (vague) topic and set the first milestone with this: learn. Learn about the fun, the (lack) of skills in presenting my thoughts, and the reaction of others. If they are interested at all in what I want to say. My slides (the output) needed to be good enough (on my own quality scale) so that I could achieve these goals.

Measure the Outcome

The outcome was great! Even if it was a complicated plan, everything worked out, and I was ready to go. This meetup, in a city where almost no one knew me (so that they were unbiased), with a topic which could have been everything or nothing, the splendid location at Mastercard providing the conference feeling – all this was on purpose to get the most honest feedback. After seeing several people nicking during the talk, making multiple connections on LinkedIn and mastodon directly after the session, and getting several “Thank you for addressing this” comments, I could tick one important question: people want to know what I am speaking about ✅

The question about joy, about having fun, was answered too: yes, I had fun. I had great conversations with myself while I was writing the talk, and I had better conversations with the people in the room ✅.

Embrace the Change

The best outcome I learned by giving this talk was that it is not good enough yet. Imagine the other situation: having it perfect for the first time. Where am I going from here? What a boring (hence scary) thought! After this first practice, I now know (and not guess) that I will need to rework everything, but my first “walking skeleton” is the right one; the first step was exactly in the right direction. The next iterations can come.

The next milestone is at the beginning of October at KanDDDinsky. The steps towards it will be small and several based on feedback from Nick, Andrea, or anyone up to it. My journey to find my boundaries can continue.

(Data) Ownership, Boundaries, Contexts – what do these words mean?

In the last months, we started to use these terms more and more at my company without discussing the concepts behind them. One day I was asked, “What do you mean by data ownership?” 🤔 The question made me realise that I don’t know how much of these concepts are understood.

These terms refer to sociotechnical concepts (some originating from Domain-driven design). They refer to one possible answer to the question: how can a product be improved and maintained in the long term? How can we avoid hunting for weeks for bugs, understanding what the code does, finding out what it should do, and hoping that fixing one issue does not lead to a new problem? How can we continue having fun instead of becoming more and more frustrated?

Real digital products address needs which were fulfilled earlier manually. Companies which survived the first years of testing the product are often innovators in their market. They have chances to stay ahead of the others, but they have the burden of solving all questions themselves. I don’t mean the technical questions; nowadays, we have a considerable toolbox we can use. But all the competitors have that toolbox too. The questions to answer are how to organise in teams and how to organise the software to reach a steady pace without creating an over-complicated, over-engineered or over-simplified solution.

How to get a grip on the increasing complexity built up in those years when the only KPI that mattered was TTM (Time-to-Market)?

Years ago, the companies creating software to help automate work answered this question with silos around the architecture: frontend, backend, processing, etc. In the meantime, it became clear that this was not good enough.

Engineers are not hired to type code but to advise and help to solve problems. 

This means they should not belong to an engineering department anymore but be part of teams around different topics to handle: marketing, search, checkout, you name it. These are sub-domains or bounded contexts (depending on the importance of the subject, more than one bounded context can build the solution for the same sub-domain). These contexts and their boundaries are not fixed forever because the context changes, the market around the company changes, and the needs change. The people involved change and, finally, the effort needed changes. The best way also to define them is to take a look at how the business is organised (sales, marketing, finance, platform, developer experience, etc.) and how the companies using the product are organised (client setup, client onboarding, employee onboarding, payroll period, connected services, etc.). By aligning the software and – to get the most significant benefit – the teams to these sub-domains, you can ensure that the cognitive load for each team is smaller than the sum of all.

What are the benefits?

  • The domain experts and the engineers speak the same language, the ubiquitous language of their bounded context, to use the DDD terms.
  • The teams can become experts in their sub-domain to make innovation and progress easier as the problems are uncovered one after another. They can and will become responsible and accountable about their domain because they are the only ones enabled to do so.
  • Each team knows who to contact and with whom to collaborate because the ownership and the boundaries are clear. (No long-running meetings and RFCs anymore by hoping to have reached everyone involved).

What does data ownership mean in this case? Data ownership is not only about which team is the only one controlling how data is created and changed but also the one controlling which data is shared and which remains implementation detail. This way, they stay empowered and autonomous: they can decide about their experiments, reworks, and changes inside their boundaries.

Data ownership also means process ownership. 

It means the team which owns the data around “expenses”, for example, owns the features around this topic, what is implemented and when so that they are involved in each improvement or change regarding expenses from the beginning. This is the only way to respect the boundaries, take responsibility, and be accountable for all decisions around the software the engineers create.

Applying these concepts can’t be done overnight, mainly because it is not only about finding the (currently) good boundaries but also shifting the mindset from “let me build something” towards “I feel responsible for this part of my product”. It needs knowledge about the product and a lot of coaching and care. But finding the boundaries to start with should be doable in case of a product already established on the market and with a clear strategy. The alternatives are silos, continuously increasing cognitive load or the loss of an overview and local optimisations.