Software engineering, metrics, functional safety ...
Alternatively: do not trust the big tech on how good the AI is humans are still needed to point it to the right direction Image by Michael Kauer from Pixabay My summer is getting dangerously close to its finish line, despite my strong protests. I ve spent the summer working on non-software-engineering tasks, but before I went on Continue reading "Software Engineering with Agents there is a need…
Image by Manueldesign20 from Pixabay It s hard to believe that 2026 is already halfway and the summer is upon us. When I look back at what happens now, I still think that the best time to be a software engineer is now. We get so many cool tools to work with that we do not Continue reading "Summer 2026 where are we going now?"
Image generated by Gemini based on this blow post https://www.mdpi.com/2076-3417/16/10/4788 The practical meaning of automated code generation is shifting rapidly. What was recently categorized as simple autocomplete has expanded into complex workflows involving multi-file modifications, test execution, and repository navigation. However, as Zhenhan Chen et al. argue in a recently published…
Image taken directly from the paper https://arxiv.org/pdf/2605.24138 The Software Engineering (SE) landscape is shifting from LLM-assisted workflows, like copilots, toward Autonomous SE, where multiple specialized AI agents cooperate without a human in the loop. The premise is exciting: a Designer agent creates the plan, and a Programmer agent implements it. Yet, simply letting agents talk…
Experiment design from the paper Large Language Models (LLMs) are revolutionary for programming productivity, producing functional code snippets in seconds. However, as software engineers, my co-authors and I know that functional is not the same as well-designed. LLMs are generally bottom-up thinkers; they excel at local syntax but struggle to adhere to higher-level architectural Continue reading…
Image generated by Gemini based on the content of this post https://arxiv.org/pdf/2605.19102 Getting Large Language Models (LLMs) to write functional code often feels like casting spells; a slight misphrasing in your prompt can result in a buggy output. This is even more important now that we have agents which work for days on our tasks. Continue reading "My prompt is better than your prompt how…
Image source: Gemini, based on the summary of this blog post. When I write this post, I m sitting at a reporting workshop of Software Center, at Axis Communications in Lund. Jan has reminded us that we ve been going on for 15 years. That s most of my academic career and a lot of my life. Although Continue reading "15 years of Software Center A Look in the Mirror and over the Front Windshield"
Image generated by Gemini based on the blog post content https://arxiv.org/pdf/2604.23340 We have all seen Large Language Models (LLMs) write impressive snippets of code or debug a tricky function. AI coding editors like GitHub Copilot are increasingly adopted, with studies suggesting that up to 88% of developers report increased productivity. But accelerations in development come Continue reading…
https://miroslawstaron.github.io/hallucinations.html#/5 The shift from manual coding to AI-augmented orchestration is no longer a future it is a reality. Software engineers adopt AI increasingly often and increasingly deep. However, as organizations pour investment into Generative AI tools, a critical question remains: How do we measure the true return on investment? I asked Gemini to analyze…
Link to the book I m often asked what invention I think is the biggest in human history. I do not have one that is the biggest, but I have a short list: 1) Writing once we learned how to codify knowledge, our progress accelerated tremendously 2) Computing once we learned how to make Continue reading "From Gutenberg to Google and on to AI"