Why engineering managers are expected to be hands-on again and how AI tools are making it possible to stay technically sharp while still leading.
The Trap of Instant Heroism in the Era of AI
AI has expanded what engineering leaders can do.
Resetting on engineering expectations in the age of AI
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How to Do AI-Assisted Engineering
15 experienced engineers and engineering leaders share their real-world experiences with AI-assisted engineering.
Why AI hasn’t replaced software engineers, and won’t
Arvind Narayanan and Sayash Kappor take on the question of AI job losses through the lens of a profession that is uniquely suited to AI disruption - software engineering. In …
Why AI hasn’t replaced software engineers, and won’t
Coding agents as normal technology
AI makes weak engineers less harmful
Like other kinds of puzzle-solving, software engineering ability is strongly heavy-tailed. The strongest engineers produce way more useful output than the average, and the weakest engineers often are actively net-negative: instead of moving projects along, they create problems that their colleagues have to spend time solving. That’s why many tech companies try to build a small, ludicrously well-paid team instead of a large team of more average engineers, and why so far this seems to be a winning strategy.
AI is removing the middle class of software engineering
AI makes projects with weak engineering culture fail much faster.
Cory Doctorow: The people who tell you ‘AI is changing everything’ are lying
It has become impossible to tell managers mesmerised by artificial intelligence that the tools are not, in fact, helpful. So employees just play along with the fiction to keep their jobs, writes our tech columnist
The future belongs to those who can refute AI, not just generate with AI
Why verification, not prompting, could shape the next decade of engineering
Pure and impure software engineering
Why do solo game developers tend to get into fights with big tech engineers? Why do high-profile external hires to large companies often fizzle out? Why is AI-assisted development amazing for some engineers and completely useless for others?
The Engineering Leadership Report 2026
Our survey of 600 engineering leaders exploring how the role is evolving, where the challenges lie, and what the future holds for the job.
Why AI Makes Things Worse for Enterprise Teams, by Paul Ford
Why are so few engineering teams reaping the benefits of AI? On this week’s episode, Paul presents Rich with the findings from a recent report from CircleCI and
X : What are you interested in? Me : Wow, that varies constantly. Right now? There are a number of topics that I'm actively pursuing … a) When we talk about software engineering we typically think… | Simon Wardley
X : What are you interested in? Me : Wow, that varies constantly. Right now? There are a number of topics that I'm actively pursuing … a) When we talk about software engineering we typically think about the active part of creating code but software development is currently practised as a craft not an engineering discipline. The only engineering discipline in software engineering is testing. This creates a flaw in the comparison with using AI to code because development itself has never been optimised. If all we have to do is write code and we can automate that part then we can just replace those expensive typists with LLMs but development should be, and has the capability to become an engineering discipline. It's just not that for now. https://lnkd.in/eSRprhbf b) Most people talking digital sovereignty are doing so with good intentions but they literally have no idea what they are talking about. This is not because they are daft or foolish but because they cannot see the environment they are talking about. They are like generals talking about territorial sovereignty with no idea of what territory is or how you represent it. https://lnkd.in/eku2X_Ea c) Architectural decisions are made in code and not in the diagrams we create. Those architectural diagrams are more like prompts, wishes and beliefs of what a system should be but rarely reflect the actual system. This creates additional problems when the real architectural decisions are made by coders but coding itself is a craft not an engineering discipline. d) The current crop of LLMs / LMMs are driving us towards a new theocracy. We can counter this through diversity, critical thinking and open approaches but that does mean we have to get to the point of all symbolic instructions being open. That includes the training data. Copyright is a distraction from the real issue that we don't know what the systems are being trained on. Guardrails are a post event kludge. https://lnkd.in/exJVmNvD e) The medium we use in conversational programming environments such as cursor and lovable (or what we call vibe coding when not looking at the code or Software Engineering + AI when looking at the code) appear to be flawed. We are focused on text not images. The change of medium changes the conversation, the corollary is the conversation we have around the screen and the one we have around the whiteboard. Same problem, different medium, different discussion. https://lnkd.in/e_W6b6z3 f) "Value" in consulting land is mostly theatre rather than something meaningful. There are many forms of value but often we fail to identify this, quantify it or even measure it. https://lnkd.in/eeNbR_VY g) Rewilding Software Engineering. To change software development into an engineering practice, we need to introduce two wolves - one that software engineering is a decision making process and secondly that we need to build tools for problems we are facing - https://lnkd.in/epyUnqgh
The engineering manager's attention budget
Every Engineering Manager has 5 jobs - most distribute their 100 'attention points' across only 2-3 of them
‘AI fatigue’ is settling in as companies’ proofs of concept increasingly fail. Here’s how to prevent it | Fortune
Along with the excitement about the possibilities of generative AI is a great deal of pressure for leaders and employees participating in projects.
