Posts

Shift your build left!

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I can't quite believe I am writing this in 2026. I originally wrote  a version of this article back in 2016 , 10 years ago! But I am seeing an increasing number of teams overusing their build pipeline again.  I get it. Modern build pipelines now have a huge amount of functionality. They are now far more than simple script runners waiting for a trigger - just look at GitHub Actions, or what you can script these days in GitLab. So it is becoming far more tempting to let critical functionality drift right, and into your pipeline. Builds, publishing scripts, testing etc can all drift right. But don't let it happen! As with all late actions in software, by the time it is in the pipeline it is too late. Pipelines are shared resources, so can be delayed in running. Often the runners are slow, and take time to spin up. And perhaps most importantly,   the pipeline scripting languages are designed to tie you in to a specific vendor . What happens when your pipeline vendor goes out...
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AI use on this blog

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  Just a quick note in case there is any doubt whatsoever. I do not use AI - or more correctly LLMs (Large Language Models, aka stochastic parrots ) - of any kind on this blog.  All articles, both past and future, are written entirely by my own fair hand and input manually with my somewhat dodgy typing. They are a direct link from my Human Intelligence to the written word, sharing 30+ years of real world software engineering experience.  So all the errors are my own. 
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The bitter pill

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As AI adoption continues apace, one good thing coming out of this second mass experiment of the decade (the first being Work From Home, caused by Covid) is  data . As more and more companies adopt AI in the software development workflow, they are generating huge amounts of information about its effectiveness. The folks at CircleCI are in a unique position to collect the data across millions (28 million to be precise) of delivery pipelines they host. They have published a summary of their findings  here . So what do 28 million data points tell us about using AI in software delivery? It's..."interesting". TL;DR - AI's effect on branches is noticeable. It increases throughput of branches for median teams significantly (15%), but this increase never makes it to production; they are never released. The production release branch throughput degrades by ~7% for the average team - AI adoption slows down teams by quite a lot. As expected, the AI-induced pressure of generating m...
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Location: Guildford, UK
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A new Law of AI is emerging - Gell-Mann Amnesia!

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 I noticed this throwaway comment recently: " Whenever I use AI to probe a topic I know something about, it seems to make a number of errors; by contrast, whenever I use it to explore topics I know little about, it knows so much more! " I must admit I have noticed something similar. When I am asking about something I know about, such as software, AI generated responses tend to be at best flawed, at worst plain wrong. Yet when I ask about something I genuinely know nothing about the results are compelling and I have to rein myself in. It turns out this is a named effect, observed by Michael Crichton (yes, that  Michael Crichton !). " Gell-Mann Amnesia ". He noticed that experts reading articles in their field of expertise will tend to find them full of errors, whereas reading other articles, even in the same publication, on topics outside their expertise  are believed to be credible. That is exactly what is happening with AI. When the results are critiqued by an exp...
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What makes a high performing team tick?

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What makes a high performing team tick? What is it that takes a team from being medium or low performing into elite performance as defined by DORA? On demand deployments, single figure bug counts, next to no downtime. Having worked in high performing teams, as well as having built a few myself over the years, I feel that I have a unique perspective on what it is that allows a team to work effectively together. The "Secret Sauce". So what's the recipe?  It's...." complicated ". But it looks a bit like this: At the top, unsurprisingly there is Technical Excellence . Team members need to be fully aware of and skilled in the various accepted best-of-breed tools and techniques that are out there. These currently include TDD, BDD, incremental design & architecture, refactoring, pairing/mobbing and so on. No excuses, these are all proven techniques that improve both quality and delivery, and should not be dropped unless there is a provable reason to. Even then ...
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The Four Demands of Software Development

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Do you know where your team's time goes? What are the competing priorities? Understanding this can be the first step to making sense of how a team is working together at a given time, and gives fairly heavy hints how to improve things for the better. A team's investment (time, money etc) can be broadly split into four 'pots': External Demand . User-facing features, new functionality. Internal Demand . Improvement. Kaizen. Failure Demand . This is the surprises. Often nasty, time consuming surprises. Business As Usual (BAU) . Keeping lights on. Those essential maintenance tasks that keep things ticking over. Any team that understands this, and knows how interdependent they are will generally thrive. Wait... interdependent?   Yes indeed. This is a zero sum game, and any team needs to make a conscious decision of how much of their finite budget (people, time, money) to invest in each at any given time. To make things even more interesting, a team only has direct control o...
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Location: Guildford, UK
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"Use AI" is answering the wrong question

 We are certainly living in interesting times right now. Specifically here I am talking about the rise of "Artificial Intelligence" (or, more correctly, 'Large Language Models", AKA 'LLMs') in software development. Whether you believe these tools are useful, or will lead to the demise of the human race¹, there is no doubt they are surrounded by the biggest hype cycle that anyone has seen before. There is an unprecedented (many are now saying unsustainable) amount of investment happening in this area. But any investment requires a return which means marketing and sales are working overtime to bring in new paying customers. Unfortunately as a result of these intensive sales campaigns there are companies - many of whom should know better - becoming ensnared in the unfulfilled promises being made by unscrupulous companies, and are " drinking the Kool Aid ". However, once the contracts are agreed by senior management, and the (not insignificant) bills be...
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