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This is exactly how real developers use AI. Small steps, testing, and constant refining.

AI industry uses the Jio model of dependency. Give products at very cheap rates make them dependent and charge higher and higher.

The question also extends to how the control is done, how much of AI are we implementing in our lives? Who controls that? Healthcare is a field that benefits the most from AI, and we need more people there but does it make more money....

Brilliant Pascal. Whether or universal basic income is a great way to motivate someone, and whether it leads to fulfilling lives is not really the question. Can we extract the wealth from the West Coast is actually the question, and Warren Buffett seems to have an idea for that too. Probably not under the current administration though.

Pascal BORNET part of this awareness that we champion, is understanding that AI is not just a resource. It is a new environment for human cognition. And the implications of a small group controlling a cognitive environment are unknown, at best.

This is the correction phase of the AI hype cycle that many experienced engineers expected. AI absolutely boosts productivity, but “replace engineers” was always a flawed framing. Engineering is not just code generation — it’s architecture, trade-offs, debugging ambiguous failures, domain understanding, operational ownership, and long-term maintainability. What many companies underestimated:• Token economics at enterprise scale• Context-window inefficiencies on large codebases• Human review overhead• Hallucination-driven rework• The cost of bad architectural decisions generated confidently at high speed The real winning model is likely to be:Small, highly skilled engineering teams + AI augmentation — not AI replacing teams entirely. The companies getting the best ROI from AI today are usually the ones using it as a force multiplier for senior engineers, not as a wholesale substitute for engineering judgment.

The people getting amazing AI results usually have strong systems behind them.

Clara, I’m curious how you think institutions can practically preserve that kind of humane reflection as AI systems scale so quickly, while geopolitical tensions, sometimes shaped by misinterpreted religions and religious influence, continue to rise.

I also come to the world of AI in education via Theology, and also value the time to read closely. I'm not at all surprised by the number of philosophy, theology and ethics folks doing this work in education.

A desperate attempt maybe to stay relevant in topics they know nothing about. AI use and consequences are ethical topics, not religious ones.

Yes, lots of rethinking to do. At the school of collective intelligence in Rabat they are doing a wonderful seminar on AI and learning that I sadly cannot attend and they have been sharing interesting articles on learning in the teams chat I follow while I grade the 30 essays from my class: ·       AI-induced never-skilling in medical education: https://www.nature.com/articles/s41591-026-04438-y ·       On the opposite side of the debate, the historical development of ‘cognitive offloading’ in education systems https://stefanbauschard.substack.com/p/institutionalized-education-as-cognitive ·       On what we mean by learning: Deescalating the AI Learning Debate - by Nick Potkalitsky https://nickpotkalitsky.substack.com/p/deescalating-the-ai-learning-debate

The best builders know prompting is only one small part of the process.

No AI worries here!

Great analogy. Nobody builds something solid without checking the weak spots.

the prompt is just the start the craft is everything that comes after it!!

Data centres could provide solar for every building in the area to offset their energy consumption, and could provide rainwater recovery either on their own buildings or for locals, to accommodate their water needs. Grownups do this kind of thing.

Yes, Gary Kucher - there's a growing body of evidence that points to similar harm, which is especially concerning re' developing brains. The brain doesn't care what it's exposed to, it simply changes accordingly, and whether the changes serve it long-term isn't its concern ...

This feels very real compared to all the hype around AI coding lately.

This is a thoughtful overview, especially because it includes the caution that often gets missed in conversations about fasting. One nuance I think matters is that fasting is not only a question of the fasting window. The response depends on the whole biological and lifestyle context around it: metabolic health, medication use, stress, sleep, protein intake, micronutrient adequacy, and the quality of what someone eats when the fast ends. That is where the discussion becomes more practical. Some mechanisms linked to fasting are promising, but in real life, the value comes from whether the approach is safe, sustainable, and nutritionally complete for that individual. Fasting can be a useful tool for some people, but it should not be treated as a universal shortcut. The pattern around the fast matters just as much as the fast itself.

Thanks. I read a really good comment by swedish academic Virginia Dignum in Umeå University: https://reflectingwide.blogspot.com/2026/05/magnifica-humanitas-what-encyclical.html