The single thing I need my task systems to do, from a simple shopping list to complex project management software, is to answer the question "What should I be doing RIGHT NOW?"
In this video I'll evolve 10 years of optimisation in 10 minutes.
Article and links here https://www.namtao.com
À l’ère des agents, notre avantage ne viendra peut-être plus de notre capacité à produire plus vite ce que nous savons déjà, mais de notre capacité à apprendre plus vite ce que nous devons réellement construire.
Nous explorerons progressivement cette tension afin de proposer une démarche permettant de concilier la richesse de la modélisation métier avec la vitesse et les capacités du développement agentique.
L'IA à l'école : bonne ou mauvaise idée ?
📖 CHAPITRES
- 00:00 Intro
- 00:57 1 : L'IA remplace les profs
- 03:21 2 : Réviser avec ChatGPT : mauvaise idée ?
- 06:57 3 : La meilleure méthode pour apprendre
- 09:47 4 : Est-ce que l'IA nous rend plus bêtes ?
- 14:11 5 : Interdire l'IA à l'école ?
- 17:15 Conclusion
🚰 SOURCES ET ATTRIBUTIONS
🔵 Intro
-
Alpha School, reportage CBS « Inside the $40,000 a year school » :
• Inside the $40,000 a year school where AI ... -
France 24, la classe de CE1 avec IA :
• Dans cette école, l’IA révolutionne l’appr... -
Citation de Jonathan Haidt, « The Anxious Generation » (2024)
🔵 Chapitre 1
- Australie, réseaux sociaux interdits aux moins de 16 ans :
https://www.esafety.gov.au/about-us/i...
- France, interdiction votée pour les moins de 15 ans :
https://www.touteleurope.eu/societe/l...
- ChatGPT, 100 millions d'utilisateurs en 2 mois (analyse UBS) :
https://www.reuters.com/technology/ch...
🔵 Chapitre 2
- L'étude en Turquie, Bastani et al., « Generative AI Can Harm Learning » (Wharton/UPenn) :
https://papers.ssrn.com/sol3/papers.c...
-
Animation reprise de l'excellente chaîne Science Petr, « AI Is Frying Your Brain » :
• AI is frying your brain. -
Son guide pour transformer une IA en tuteur :
- L'étude d'Harvard, Kestin et al. (Scientific Reports, 2025) :
https://www.nature.com/articles/s4159...
- Démo Khanmigo, de Sal Khan : • How AI Could Save (Not Destroy) Education ...
🔵 Chapitre 3
- Daniel Kahneman, « Système 1 / Système 2 : Les deux vitesses de la pensée » (2011)
- Veritasium, conférence « What Everyone Gets Wrong About AI and Learning » : • Veritasium: What Everyone Gets Wrong About...
🔵 Chapitre 4
- L'étude du MIT, Kosmyna et al., « Your Brain on ChatGPT » :
https://arxiv.org/abs/2506.08872
- L'effet Google, Sparrow, Liu & Wegner (Science, 2011) :
https://www.science.org/doi/10.1126/s...
- Jonathan Haidt, « Into the Machine » : • Is AI making you stupid? w/Jonathan Haidt
🔵 Chapitre 5
- Chine, IA gelées pendant le gaokao (juin 2025) :
https://fortune.com/asia/2025/06/09/a...
- Décret présidentiel américain du 23 avril 2025 (Executive Order 14277) :
https://www.presidency.ucsb.edu/docum...
- Belgique, concours de médecine (La Libre) :
https://www.lalibre.be/belgique/ensei...
- Le mode étude de ChatGPT :
https://openai.com/index/chatgpt-stud...
- Le mode apprentissage de Claude :
https://www.anthropic.com/news/introd...
- L'apprentissage guidé de Gemini :
https://blog.google/products-and-plat... Miniature inspirée des excellentes chaînes Fern et AQuatre
The fleet can build anything and remembers nothing. Someone has to carry what the machines cannot.
Watch a good Fleet Lead work for an hour. Six agents in flight at once. Two are drafting against different halves of the spec, one is writing harness checks from the criteria, one is grinding through a migration, and two are parked, waiting on a judgment call their operator will make between other judgment calls. Work merges, checks run, something lands. A refactor that would have been a two-week argument goes in quietly before lunch. It looks less like programming than like conducting, and the throughput coming off one desk is, frankly, a little absurd. The six is a soft count, too. Agents spawn agents when the work splits, the pattern production orchestrator systems already run [1], and the formation swells and thins by the hour. In the work we run, the spikes reach scores of agents under one orchestrator when the day calls for it.
Présentation par : Cyrille MARTRAIRE (Arolla)
📕 Résumé :
Je lis des publications scientifiques tout le temps, pour n'importe quel sujet que je veux apprendre sérieusement. Pourquoi perdre son temps à lire des opinions et des résumés superficiels quand vous pouvez trouver des réponses fiables et précises directement dans des publications scientifiques ? Mais on ne va pas se mentir, la littérature académique peut paraître intimidante si vous ne savez pas comment l'aborder. Et même avec l'IA, la lecture d'articles reste un ingrédient clé.
Si vous n'êtes pas familier avec l'univers des publications scientifiques, rejoignez-moi pour découvrir comment explorer ces contenus austères mais fascinants propulsera votre apprentissage, quel que soit le sujet. Nous illustrerons cela à la fois pour modéliser un domaine métier (à la DDD) et pour comprendre le groove en musique (pour le fun).
Enregistré en avril 2026 à Paris, Palais des Congrès, Porte Maillot.
Une liste de papiers sélectionnés par Cyrille dans le domaine de l'informatique pour commencer https://gist.github.com/cyriux/ee0d382bda9853e3fe86189f4f95658f
Publications scientifiques utilisées :
Kardas, M., & O'Brien, E. (2018). Easier Seen Than Done: Merely Watching Others Perform Can Foster an Illusion of Skill Acquisition.
More people are learning to code than ever, but most learning opportunities do not explicitly teach the problem solving skills necessary to succeed at open-ended programming problems.
In this paper, we present a new approach to impart these skills, consisting of:
1) explicit instruction on programming problem solving, which frames coding as a process of translating mental representations of problems and solutions into source code,
2) a method of visualizing and monitoring progression through six problem solving stages,
3) explicit, on-demand prompts for learners to reflect on their strategies when seeking help from instructors, and
4) context-sensitive help embedded in a code editor that reinforces the problem solving instruction.
We experimentally evaluated the effects of our intervention across two 2-week web development summer camps with 48 high school students, finding that the intervention increased productivity, independence, programming self-efficacy, metacognitive awareness, and growth mindset.
We discuss the implications of these results on learning technologies and classroom instruction
James Prather, Brent Reeves, Juho Leinonen, Stephen MacNeil, Arisoa S. Randrianasolo, Brett Becker, Bailey Kimmel, Jared Wright, Ben Briggs
Novice programmers often struggle through programming problem solving due to a lack of metacognitive awareness and strategies. Previous research has shown that novices can encounter multiple metacognitive difficulties while programming. Novices are typically unaware of how these difficulties are hindering their progress.
Meanwhile, many novices are now programming with generative AI (GenAI), which can provide complete solutions to most introductory programming problems, code suggestions, hints for next steps when stuck, and explain cryptic error messages. Its impact on novice metacognition has only started to be explored.
Here we replicate a previous study that examined novice programming problem solving behavior and extend it by incorporating GenAI tools. Through 21 lab sessions consisting of participant observation, interview, and eye tracking, we explore how novices are coding with GenAI tools.
Although 20 of 21 students completed the assigned programming problem, our findings show an unfortunate divide in the use of GenAI tools between students who accelerated and students who struggled.
Students who accelerated were able to use GenAI to create code they already intended to make and were able to ignore unhelpful or incorrect inline code suggestions.
But for students who struggled, our findings indicate that previously known metacognitive difficulties persist, and that GenAI unfortunately can compound them and even introduce new metacognitive difficulties.
Furthermore, struggling students often expressed cognitive dissonance about their problem solving ability, thought they performed better than they did, and finished with an illusion of competence. Based on our observations from both groups, we propose ways to scaffold the novice GenAI experience and make suggestions for future work.
Clara explores the concept of metacognitive awareness, the role it plays in learning, common traps in your thinking, and how using LLMs affects it in surprising ways.
Papiers de recherche :
Florence Boulenger Journaliste : tech, futur du travail, économie, entrepreneuriat.
L’IA va vous faire gagner du temps. L’IA va améliorer votre productivité.
C’est vrai, ça ?
Pour obtenir une réponse un peu plus construite qu’un « ça dépend* », nous sommes allés voir Arthur Vinson, co-CEO de Mailoop et Suzy Canivenc, docteure en sciences de l'information et de la communication.
Déjà associés dans le cadre de l'Observatoire de l'Infobésité et de la Collaboration Numérique (OICN) fondé en 2023, ils viennent de publier une étude réalisée à partir d’une cinquantaines de sources disponibles sur le sujet.
« ChatGPT ne date que de novembre 2022. Il nous a fallu attendre quelques années pour mener un travail de recherche à partir d’un corpus suffisamment solide. »
« Où sont passés les gains de productivité de l’IA ? En partie dans le travail masqué de vérification de ce qu’elle génère. Mais aussi dans le fait qu’aucune IA ne peut régler les pertes d’efficience socio-organisationnelles... »
« Les fameuses tâches “à faible valeur ajoutée” ont une valeur : ça s’appelle l’apprentissage ! »
I’m convinced that a large % of programmers don’t actually like computers.
As a side effect, are also perfectly happy to throw away their reasoning to a model as soon as they can.
I don’t get it, at ALL. Don’t you LIKE understanding the magic of the machine?
You do realize hand-programming (I hate that I even have to specify hand now) is fun…right?
Clara explores whether learning to code is still worthwhile, offering crucial insights into the learning process and the future of programming.
Clara explains how to use AI effectively when learning to code or improving your programming skills, discusses the potential drawbacks of the concept “AI as a tutor” and its impact on the learning experience, both practically and emotionally. 📃 Read the research this video is based on about the "widening gap" here: https://dl.acm.org/doi/10.1145/363262...
- 0:00 what’s up with AI and learning?
- 0:32 the experiment
- 0:58 pssst... check out our student pack
- 1:13 student A (struggling)
- 2:11 unawareness of unawareness
- 2:26 student B (non-struggling)
- 3:36 the widening gap
- 4:23 a rule of thumb 👍
- 4:39 doing things slowly is better for learning
- 4:48 imposter syndrome
- 4:56 meh.
- 5:43 🤑getting things done
- 6:09 the good old days
- 6:36 how to use LLMs in learning
- 6:54 what have we learned?
- 7:13 the psychology of learning to code
- 7:20 please… please... the student pack
- 7:32 begging and conclusion
- make it wrong
- make it short
- make it again
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