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iSAQB Software Architecture Gathering

Thought Provoker
Published on November 11, 2026

Through the AI Looking-Glass: Kevlin Henney on Technology, Human Behavior, and Hype

 

To conclude our SAG 2026 speaker interview series, Kevlin Henney joins us for the 20th and final interview, sharing his perspective on AI, our relationship with technology, and what past technological developments can teach us about today’s AI-driven world. Ahead of his session “AI Through the Looking-Glass” and full-day workshop “Keeping It Simple: Reducing Complexity in Architecture and Development,” he explores the importance of looking beyond the hype, questioning our assumptions about technology, and understanding how simplicity can help us build better, more maintainable software systems.

1. Your session suggests that AI tells us at least as much about ourselves as it does about technology. Looking at previous technological shifts, what aspect of human behavior do you think changes the least, no matter how much the technology evolves?

The first behaviour that comes to mind is optimism, although it is more properly classified as an attitude than a behaviour. I believe humans have the capacity to be ingenious and generous. Every technological shift offers us an opportunity to address the problems of the world, whether they are of our own making or thrown at us by nature, whether at the scale of the individual and the day or of generations and the world. We can turn many of our dreams and imaginings into reality. I think many technologists view new technologies through a similar lens.

 

Optimism — the belief that good things will happen — can, however, obscure the conditional nature of the future: while good things can happen, there is no guarantee or necessity in human nature that they must happen. It requires work and deliberate choices. Optimism can blind us to the nuanced nature of technology. It can also make us credulous, so that we believe in a positive outcome  because that is what we want to believe rather than grounding ourselves in reality. Magical thinking, therefore, is an associated behaviour we want to be aware of.


Perhaps the darkest behaviour that accompanies any technology is greed, whether that is for power, possessions or money. Greed accompanies every opportunity and, therefore, every technology. It boosts hype curves, normalises exploitative and extractive practices, reframes the power narrative and kicks ethics, idealism and individuals to the curb. Often misattributed to the economist John Maynard Keynes, the observation that “capitalism is the extraordinary belief that the nastiest of men for the nastiest of motives will somehow work for the benefit of all” captures the intersection of greed and magical thinking that we need to guard against.

2. Every major technology seems to arrive with both bold promises and equally bold fears. Looking back at previous waves of innovation, what do you think we consistently overestimate, and what do we consistently underestimate?

I think we overestimate both the good that will happen and the bad that will happen. What ends up being good is often not what people thought would be good and, similarly, what ends up being bad is often not what people thought would be bad. We typically underestimate what actually becomes the benefits and liabilities of an innovation.

 

The pre-LLM history of AI was filled with plenty of optimism about how AI could help us as a competent and impartial assistant, that it would free us up to make better use of our time and engage in creativity, society and family. It was also filled with fear — fear fuelled by our collective failure to appreciate consciousness as something separate from intelligence, a fear that AI would achieve sentience and become a direct enemy of humanity. Woven together, these views form a significant part of the fabric of science fiction. We now know these fictional futures are not the ones that lie before us. When people now talk about the prospect of AI devastating humanity, it won’t be because of malicious intent, dark design or sinister forces; it will be an embarrassingly banal side-effect of something that could have been prevented with a better prompt or setting a particular config flag or installing a particular patch.

 

All technologies bring with them liabilities, with many of these being more about us and how we behave than necessarily being intrinsic to the technologies themselves. This is not to say that we should consider technology neutral — a common claim, but one that deserves to be challenged as, well, life is not that simple. The set of possible relationships we have with a technology is part of the technological proposition, not separate from it. To say otherwise seems naïve or intellectually dishonest.

 

The long-term benefits of technologies can be imagined, but are sometimes difficult to discern because any popular tech changes the world it’s in and, therefore, what becomes simple and possible and even inevitable in terms of exaptation and other technologies. The twentieth-century dream of the videophone happened in the twenty-first century, but it did not come from traditional telecommunications companies trying to invent the videophone, a goal they pursued for half a century. Videophones emerged from the haphazard growth and convergence of many separate technologies — the web, broadband, webcams, laptops, mobile phones, WiFi, 4G, etc. — until they arrived without fanfare or even the label ‘videophone’.

3. Your talk encourages a more balanced perspective on AI instead of simply embracing or rejecting it. What question do you wish more software professionals would ask themselves before forming an opinion about AI?

I don’t know that I can boil it down to a single question. People arrive at opinions from many perspectives and for many reasons, some of which are apparent to them but many of which are not, some of which can be considered objective and some of which are highly personal.

4. Your workshop explores what "keeping it simple" really means. Looking back at the systems you've worked on, what's the most common reason simplicity gets lost along the way?

Ultimately, it’s that we as humans have a poor relationship with time. We make poor intertemporal choices: we make the system an underthought mess because we’re in a hurry; we make the system an overthought mess because we’re trying to future-proof.

5. Teams often try to design systems that will still meet tomorrow's requirements. At what point does preparing for the future become an unnecessary source of complexity?

At the point that people start committing and accumulating speculation in their codebase. The ability to use our imagination to conceive of possibilities outside of our immediate present is an amazing tool. It lets us explore ideas, have conversations, learn about what we’re building and who we’re building things for. But speculation is not prediction or commitment. Unless something changes in our understanding of physics, we can’t predict the future. Padding our architectures with speculation is not the best use of this tool. Used with more care, speculation can be used to simplify and refine what we build and how we build it.

6. Looking ahead, how do you think advances like AI will change our relationship with complexity in software architecture over the next decade?

What is possible versus what we will actually do with AI in this respect are two quite different things. We have the potential to reclaim the effort lost to legacy systems. In theory, legacy need not be a money pit or the principal source of resistance in new development. Technical debt is something that we can repay rapidly and in regular instalments without ever running up a large debt. Exploration of technical options in an architecture should become simpler, with set-based engineering becoming the norm. We should have more time to spend in discussion with colleagues and customers. We should be able to spend less time wasting time. These are all possibilities. Will they happen? Over to you.

 

Many thanks to Kevlin for the great interview!