New and next for architecture

If you do show jumping, you need to be both in the actual moment but also look up to steer where you going next. Otherwise, you fail and it hurts.

As an enterprise architect, you also need to look at now, new and next simultaneously.

To be a top rider, you need to master the fundamentals, regardless of the challenges you meet in the arena. Not being an expert on one type of fence.

To master Enterprise Architecture, you need to be really good at the fundamentals, not expert on a certain type of software or AI platform.

The new is using AI as an architect to improve productivity. For this you need experience to be able to guide AI to a suitable solution, based on the complex problem you face. Holistic view, experience from many areas and knowledge of best practices are key traits.

My qualified guess on what comes next is the demise of Enterprise IT architecture roles, e.g. Ivory tower architects. The effort to manage IT architecture on enterprise level will be much lower due to use pf AI-tools. Remaining part will be stakeholder management, both business and IT.

The role in the future will probably be more of support to assure seed to bread, from initial business idea, to major change to business and IT in operation. E.g. program architect or senior delivery architect.

The skills you need then is both business and information architecture, as well as traditional application and infrastructure.

Think renaissance person. Think of being able to step into a business role as well as developing code.

Finally, you are accountable, not AI.

I can handle it myself

Don't give advice to software developers if they don't ask for help. You will get an answer like  “I can handle it myself."

The crux is often that they don't see the full picture and underestimate the complexity & effort to solve the problem.

If you are a seasoned enterprise architect or program manager, you seen it before.

I'm humble when it cames to solve complex problem. If I try to do it all by myself, I know that I will miss something.

I'm also lazy. If I can reuse something that is applicable in the same context, then I try to do it. Not inventing the wheel again, and again.

When doing enterprise architecture, I'm always starting with IAF, as it covers business, information, application and infrastructure, plus security and governance. You allways need some parts.

For information architecture, basic IAF as structure. Alternatively "Verksamhetsarkitektur på IRMs sätt". More or less the same.

“I can handle it myself." don't work when it comes to architecture frameworks.

Another timesaver is to use process and information frameworks for the industry you are in.

If you say that your information model will better and done faster, I would be very doubtful. I was part of a team that begun this work in 2001, before modern TMF frameworks where in place. It took a long time.

Then we have those who refuse to use AI. I still remember some colleagues that said computers with mice where toys when I bought an SE/30 to the marketing department.

Without a carrot or stick, you can just wait until they fail, and then try to help.

Next and beyond

The new thing is, with generative AI, you can develop code from from scratch. However, both software developers and AI need guidance to write maintainable code and avoid technical debt.

What I'm doing right now privately, not with our clients, is to use generative AI (Copilot) to develop a domain architecture in EA style, a solution architecture aligned with the domain and a software development playbook. All of this will be input to Claude and the development of iPhone front-end and Azure backend.

This is now for me and new for many of our clients. What about next and beyond?

In the old days, you wrote code from scratch to support your core business. Then COTS solutions for common things like finance, supply-chain etc. The trend continued with SaaS in the cloud.

What if development cost becomes low, not free, in the future. What are the implications?

Today, we have the 80/20 rule. 80% of the IT budget goes to maintenance of everything that is in production, e.g. legacy. So if you want to lower your TCO, you need to address the question how to use AI to manage your existing applications cheaper.

Eventually, the possibility to write and maintain your own code, will put a price pressure on large COTS and SaaS vendors. I'm looking at you SAP, Oracle, Microsoft, Salesforce and others.

The other prediction is that if your business heavily relies on IT, then it will be much cheaper for competitors to challenge our market dominance. Finance and insurance is a typical sector that may be impacted. Same goes for typical on-line business selling services and social media platforms. The brand, and trust in you, is fare more important than your IT in the future.

If your in physical world, less of a challenge, at least for next.

Beyond next? I would take inspiration from sience fiction and continue to polish the crystal ball.

For film production, focus should be on creativity and storytelling, and try to do lean productions to lower the costs

Now, new and next

Frank Wammes shared a self-assessment about thought leadership than made me think of what I write on my blog Disruptive Architecture.

The tagline for the blog is "When you need to make huge changes to your organization" which is about going from now to new. But what about next in the increasingly uncertain future?

I've been experimenting with generative AI since two years ago, and watching the progress of some of the tools since then. From something barely usable to an indispensable tool today.

As a consultant, I work with many different companies, and generative AI is more of new than now.

The question for me as an Enterprise Architect are the longer implications of this.

I'm trying to build a rather complex software platform for film productions, and with AI, I can build something much faster to try out ideas. This was not possible two years ago when I begun dabbling with the concept.

For many of my clients, this is not now, maybe new and more towards next. Very far far away from the daily work in the agile teams.

If I look at software development mostly done with AI, as new, what is then next?

In a follow up article, I will try to look into a crystal ball, and write about next using the film site project as an example.

Rather obvious

It's rather obvious when you know, but from my viewpoint, very few architects understand the need for information modeling. Even fewer know how to do it the whole way, from seed to loaf.

Your transformation program will surely fail if you forget to design a proper information architecture.

The starting point is a business glossary for the relevant part of the business. Then a canonical information model and a logical interpretation of this. Finally API's and schemas.

Business model -> Information model --> Data model.

If you don't know the craft, then you are in uncharted territory and will get lost.