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On the 2025 to-do list: figure out AI agents
David Knott David Knott

On the 2025 to-do list: figure out AI agents

Recent years have seen waves of AI innovation breaking faster than we can figure out good practice. Organisations around the world are working hard, not only to find ways to put AI to work, but to do so safely and responsibly. The AI to-do list often seems to be growing longer faster than we can strike items off it - but the only route to good practice is practice.

The advent of AI agents promises to add more items to the to-do list. The AI agent wave started cresting in 2024, and will break in 2025. Several major technology vendors and platforms already offer their customers the ability to build, configure and operate AI agents in an enterprise context, and the ability for consumers to build agents or to subscribe to existing agents, cannot be far behind (indeed, it is likely that, by the time this article is published, it will already be happening).

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Generative AI: time to learn a whole new vocabulary
learning about GenAI David Knott learning about GenAI David Knott

Generative AI: time to learn a whole new vocabulary

I have no idea how to talk about sport. This was a disadvantage when growing up as a teenager at an all boy’s school. I felt as if I’d missed an important lesson, or failed to read the manual that the other boys had been issued at an early age. How else did everybody else have a vocabulary, a set of concepts, a whole language, that was opaque to me?

I initially felt the same way when attempting to learn in public about generative AI, the set of solutions such as ChatGPT and DALL-E which are receiving a lot of attention right now.

This was the week when I was supposed to read a few more detailed papers, to find a couple of books, and to go deep enough to get to grips with the main concepts. However, I found that, unlike my similar experiment with quantum computing, it was hard to find accessible entry points. Perhaps this is because, despite rapid developments in recent years, the ideas behind quantum computing have been around for a long while - long enough for experts to write introductions for curious laypeople like me. By contrast, most of the material describing generative AI technologies was quite new, and either so high level that it told me little I didn’t already know (and much that I had reason to be sceptical of), or dived so deep that I was as baffled as if listening to the dissection of a football match. No-one has had time to write the accessible introduction yet.

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When talking to AI, be careful what you ask for
learning about GenAI David Knott learning about GenAI David Knott

When talking to AI, be careful what you ask for

You’ve got to ask the right questions.

According to Herodotus, when Croesus went to the Oracle at Delphi to ask whether he should go to war, the Oracle replied that, ‘If you make war on the Persians, you shall destroy a great empire’. Encouraged, Croesus launched his war, only to find that he was defeated, and it was his empire that was destroyed.

This lesson seemed particularly important when I was attempting my second week of learning in public about generative AI. As with my exploration of quantum computing, I began this second week by opening my browser, entering some search terms and reading the top few news articles that were returned.

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Can we generate intelligence about generative artificial intelligence?
learning about GenAI David Knott learning about GenAI David Knott

Can we generate intelligence about generative artificial intelligence?

Where’s my talking robot?

Robots and computers capable of holding conversations with human beings have been a staple of science fiction and visions of the future for many decades. Yet, until recently, they have seemed as elusive as flying cars.

And, while we’re asking, when’s the automated programmer arriving?

Since my first ever professionally programming job, the technology industry has threatened to do away with the job of programming - whether through 4GLs, low-code / no-code solutions, or other ways of avoiding the job of building code line by line. However, these approaches have seemed to do no more than push the need for programming somewhere else.

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Do you have werewolves in your technology architecture?
David Knott David Knott

Do you have werewolves in your technology architecture?

What was that eerie, babbling, howling sound? It sounded like a group of people yelling or fighting, but without any words that we could make out.

My wife and I were visiting a wildlife park in the Pyrenees. We were standing in front of the large enclosure that held a pack of wolves. At first, they were hidden amongst the rocks and trees of the mountainside. Then we saw one furry head and a pair of sharp ears, then another, then another. Then the whole pack emerged, about a dozen of them. And they all started howling at once.

But it wasn’t the ‘how-oo-oo-oo’ sound we associate with wolves in films and TV programmes. It was a discordant babble that sounded like overlapping voices. It was strange and disconcerting, even though we knew that we were safe, and could see where the noise was coming from. Later, I learnt that Iberian wolves make this sounds to disorient their prey.

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The Line: the simplest cloud architecture diagram you will ever use
David Knott David Knott

The Line: the simplest cloud architecture diagram you will ever use

There are a lot of diagrams which attempt to explain cloud, ranging from the classic ‘staircase’ depiction of the shared responsibility model to many, many elaborate diagrams covered in the logos of cloud services. I’d like to add to that stock of diagrams by introducing one more, which I hope will be helpful. I call it ‘the line’:

No, the graphics in this article have not glitched: that really is a single, horizontal line.

A diagram this sparse needs a few words of explanation. Your cloud provider lives below the line. You live above the line. The line is made of APIs.

A diagram this simple also needs a few words of justification. We all know that adopting a public cloud platform involves a separation of concerns: that there is work that you do and work that your cloud provider does. Do we really need another reminder of that?

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Build your way out of the ivory tower
David Knott David Knott

Build your way out of the ivory tower

How do you escape the ivory tower?

No technology architect wants to be accused of living in an ivory tower. Such an accusation means that there is at least one person who thinks that you are detached from practical reality, that you add no value, and that you do nothing but slow people down. It is never good to be characterised as an irrelevance.

Yet it is possible as a technology architect to find yourself living in an ivory tower without realising it. This is much less likely if you are a solution architect, working as part of a team, solving problems and making decisions every day. It is even less likely if you are a hands-on technologist, actively contributing to the solution that you work with.

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Conway’s law: power, money, capability and the duty to explain
David Knott David Knott

Conway’s law: power, money, capability and the duty to explain

Conway’s law is one of those, ‘Of course!’ concepts: a concept where, the first time you hear it, you say, ‘Of course!’ It reveals something which you always suspected about the world, but couldn’t quite put into words.

Conway’s law answers the question, ‘why are so many computer systems so strangely organised?’, with the idea that the structure of systems follows the structure of the teams that build them. Melvin Conway didn’t quite put it like that in 1967: he said, ‘Any organisation that designs a system (defined broadly) will produce a design whose structure is a copy of the organisation’s communication structure.’ (If you haven’t heard of Conway’s law before, but have encountered many strangely designed computer systems, you may be experiencing your own, ‘Of course!’ moment.)

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Time travel back to the days of quantum ignorance
quantum computing David Knott quantum computing David Knott

Time travel back to the days of quantum ignorance

Let’s attempt some time travel. A few weeks back, I embarked on an experiment of learning about quantum computing in public. I started with a set of questions. Let’s see whether my slightly less ignorant current self can answer some of the questions of my completely ignorant past self.

How do quantum computers actually work? How do you do computation with qubits? How do you program a quantum computer?

I attempted to answer these questions in my deliberately boring article about quantum computing, but my one sentence version is: quantum computers execute algorithms using logic gates which operate on information encoded in the properties of entities at the quantum scale. I have also learnt that it’s very hard to write a meaningful one sentence version of quantum computing: better go read that article (or, even better, one of the resources linked at the end of this article).

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A state of excitation about quantum computing
quantum computing David Knott quantum computing David Knott

A state of excitation about quantum computing

Let’s get excited!

I started this series of articles about quantum computing because of the extravagant claims being made about the field. Those claims made me feel that I should be excited, but didn’t give me enough understanding to know why.

Last week I felt that I had made enough progress to give a dull but, I hope, useful account of quantum computing. So let’s revisit some of those extravagant claims and see how I feel about them now.

I won’t repeat my boring account of quantum computing here, but will give my one sentence version (as usual, if this is wrong, please correct me in the comments): quantum computing is the use of entities which exhibit the quantum properties of superposition and entanglement to represent mathematical properties and perform calculations.

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Schrodinger’s yawn: a deliberately boring account of quantum computing
quantum computing David Knott quantum computing David Knott

Schrodinger’s yawn: a deliberately boring account of quantum computing

Let’s be boring for a little while.

I’ve been trying to learn about quantum computing for the last few weeks and, while I am still only just getting started, I think that I have gained (with lots of help) a sufficient high level understanding to have a go at explaining some of the basics - at least in simple terms that I am capable of understanding.

One of the things I have found in investigating this field is that it very easy to fall prey to mystification. The behaviour of the world on a quantum scale is strange and counter-intuitive, and it is natural for our brains to keep screaming, ‘But what’s really happening?!’ However, I think that the best way for laypeople like me to get a basic understanding of quantum computing is to resist the temptation to over-visualise, to avoid mystical or mystifying language, and to keep analogies minimal and simple. In short, to follow Richard Feynman’s exhortation to ‘Shut up and calculate!’

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A quantum of understanding - with a little help from some friends
quantum computing David Knott quantum computing David Knott

A quantum of understanding - with a little help from some friends

Last week I shared that I was hitting a wall (made of maths) in my attempts to understand quantum computing, but that learning new things about the wonder and weirdness of the quantum world was keeping me going. This week I have to admit that I was rapidly running out of wonder, with a lot of wall still to climb.

Fortunately, some people came to my rescue! I have to thank Daniela Mordetzki for introducing me to her brother, Ariel Mordetzki, a researcher in quantum computing, to Ariel for taking the time to talk to me, and to my old colleague Michel Allair for taking the time to write and share notes on his own exploration of this field. Together, they helped me get a grip on concepts and explanations which had been eluding me. They also helped me to understand why all the books I am trying to read about quantum mechanics dive into the mathematics so early: at this stage in the maturity of quantum computing, the maths is what it’s all about.

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