The longevity dose for sleep is 6.4 - 7.8 hours.
23 biological aging clocks
multi-omics: 11 proteomic, 5 metabolomic, 7 MRI
500,000 people
Interesting findings:
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Brain proteins notice sleep loss before brain anatomy does. When you measure brain aging by plasma proteins, the brain looks biologically youngest at 7.82 hours of sleep in women and 7.70 hours in men. When you measure brain aging by MRI of brain anatomy, it looks youngest at 6.48 hours in women and 6.42 hours in men.
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The brain and the metabolic organs share the same U-shape but hit their optimum at different hours. Fat tissue and the pancreas both bottomed near 6 hours. The brain bottomed higher, between 6.4 and 7.8 hours depending on whether you measure by MRI or plasma proteins. Sleep less or more than the organ-specific optimum and aging accelerates.
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Short sleepers vs long sleepers DNA.
Short sleepers' DNA matched the DNA of people whose bodies are breaking down all over.
back pain 40%
depression 37%
substance use disorders 37%
anxiety 32%
heart failure 31%
lung disease 28%
type 2 diabetes 18%.
Looking at genes only, chronically too little sleep makes the body look like it's breaking down everywhere.
Long sleepers' DNA matched the DNA of people with brain conditions versus whole body breakdown.
major depression 29%
schizophrenia 28%
ADHD 28%,
migraine 28%
bipolar disorder 21%
Short sleep gets you through the body directly: the nervous system get's aggravated, the immune system gets confused and stress hormones flood the bloodstream.
Long sleep get's you through the brain, but it's the result and not the cause. By the time someone is sleeping too long, the damage is already happening inside their organs.
Summary:
Less than 6.4 hours is a stressor. Your body is wearing down because it never gets enough time to recover. The short sleep is what is causing the damage.
More than 7.8 hours is a warning sign, signaling that something is already going wrong in your brain or your metabolic organs.
For now I see two ways to use LLMs-that-do-my-work (as opposed to LLMs-that-search, LLMs-that-ask-me-questions or LLMs-that-build-tools-I-use for instance)
1️⃣ Generating generic things
Given LLMs approximate language, and language approximates intent, it can be argued that the highly over-marketed "artificial intelligence" aspect of LLMs (aka "do something for me that works plz") is most useful when we don't know precisely what we want, and become less valuable the more precise you get (applying semantic anchoring on too many items, typically)
2️⃣ Helping with producing precise things
This includes being technical, having a technical approach, and using the tool positively for the technical steps (for instance, Test Driven Development and Domain Driven Design)
✅ Pros:
- Feeling more productive [1]
- Maybe more productivity (all the studies [1] I've read seem to point it's not the case but this is still early and moving)
❌ Cons (some happen systematically, others conditionally) :
- Dependency on the tool (breaking changes, availability issues, pricing policy changes, data use, state of the relationship between your country and the seller's country, etc)
- Token saving management [2]
- Cognitive surrender [3]
- A LOT more bugs in production [23]
- Senior developer time mostly spent on reviewing code that should not have reached them in that state [23]
- Lack of friction causing drops in memory, learning, engagement, and motivation [4][27]
- Value given to Contributions rather than to Contributors : why should lead devs hire you instead of firing up their own LLM? [28]
- Addiction to Control and/or Validation and/or Slot machine loop ("Replay button") [5]
- Automation of what brought you Joy at work [6]
- More expectations/stress [22] while being paid the same
- Critical thinking presence needs to be maintained (through discipline for instance, which does not work) and/or delegated into automated tests (back to Control replacing Joy)
- Critical thinking quality needs to be maintained by regularly doing things manually despite the tool acting actively against it ("Claude would do it faster" is such a pernicious thought)
- Loss of diversity in collaborative conversations ("my Claude's arguments versus your Claude's arguments") [7]
- How do you mentor Juniors?
1️⃣ Pieces of data gathered about the impact of LLMs on productivity
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_ai-for-developer-productivity-what-now-activity-7452020616016195584-EX1V?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
2️⃣ Multilingual prompting saves 20-40% tokens
https://arxiv.org/pdf/2507.00246
3️⃣ Study from January 2026 about cognitive surrender
https://www.linkedin.com/posts/mehdi-moussaid-160ba916a_labandon-cognitif-cest-le-nom-donn%C3%A9-par-activity-7447901614989934592-HF6l?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
4️⃣ Friction : it matters (memory, learning, engagement, motivation)
https://youtu.be/rf642RFALDU?is=wl04yfCcEyU7A2d0
6️⃣ A study from March 2026 about LLMs automating the joy out of work
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_are-we-automating-the-joy-out-of-work-designing-activity-7451939177014841344-qmGA?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
7️⃣ LLM use reduces the number of fields explored by Research
https://www.linkedin.com/posts/mehdi-moussaid-160ba916a_encore-un-article-incroyable-publi%C3%A9-la-semaine-activity-7422549300930310144-Qv6v?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
8️⃣ study from April 2026 about LLMs corrupting your documents when you delegate, via sparse but severe errors
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_llms-corrupt-your-documents-when-you-delegate-activity-7453400644373303296-TyT4?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
9️⃣ A study from June 2025 about cognitive debt when using chatgpt as an assistant for essay writing
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_your-brain-on-chatgpt-accumulation-of-cognitive-activity-7451938489916506112-mfOD?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
🔟 LLMs induce slavery
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_les-travailleurses-du-clic-activity-7450846472041975810-9ma6?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
1️⃣1️⃣ Lack of intelligence
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_vous-voulez-gagner-2-millions-de-dollars-activity-7450472933619253248-xMpe?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
1️⃣2️⃣ Deleted volume
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_claude-code-deleted-my-entire-archive-activity-7447698537464819712-UFoG?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
https://arxiv.org/abs/2306.08189 (An analysis of language models on negation benchmarks)
1️⃣3️⃣ A study from March 2026 about LLMs doing human work
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_crashing-waves-vs-rising-tides-preliminary-activity-7447605340403191808-ZsaI?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
1️⃣4️⃣ A study from March 2026 about LLMs answering correctly to visual questions, despite not being given any visual input
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_ia-santaez-hallucinations-activity-7446491905867247616-Q5uH?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
1️⃣5️⃣ A study from February 2026 on ai psychosis (aka delusional spiraling) caused by chatbots
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_ai-ai-activity-7445881612736712704-7NFv?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
1️⃣7️⃣ A study from March 2026 about LLM writing assistants shifting users' attitudes on societal issues through their bias
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_when-people-use-ai-for-writing-assistance-activity-7448643257019809792-_ccP?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
1️⃣8️⃣ Generated nudes from victims of Crans-Montana fire
https://www.lebigdata.fr/a-vomir-ils-utilisent-lia-grok-pour-denuder-les-victimes-de-crans-montana
1️⃣9️⃣ The Chinese government floods X search results with porn whenever there is political unrest
https://x.com/nikitabier/status/2017134769113542752
2️⃣0️⃣ Hallucination is feature, not a bug (in probabilistic tools)
https://www.linkedin.com/posts/matsanchez_on-na-jamais-%C3%A9t%C3%A9-aussi-pr%C3%A8s-de-lia-g%C3%A9n%C3%A9rale-activity-7455161889161949184-IcQ2?utm_source=share&utm_medium=member_desktop&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
2️⃣2️⃣ Compressed Cognition : Agentic coding is mentally expensive
https://www.linkedin.com/posts/adam-tornhill-71759b48_i-have-to-admit-that-i-havent-had-this-much-share-7458044119022616577-q6K4?utm_source=share&utm_medium=member_android&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
2️⃣3️⃣ The acceleration whiplash
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_the-ai-engineering-report-2026-the-ai-acceleration-activity-7459198398634733569-XTzE?utm_source=share&utm_medium=member_android&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
2️⃣4️⃣ LLMs return Trendslop for Strategic advice
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_researchers-asked-llms-for-strategic-advice-activity-7460645767389818880-FXaN?utm_source=share&utm_medium=member_android&rcm=ACoAABIeznoBdvfOCQc-Pz317B5HZYqHGwcBOgU
2️⃣5️⃣ PR with (+10k, -4million) lines of code
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_from-the-claudecode-community-on-reddit-share-7461460781025488896-7RMV
2️⃣6️⃣ Example of anthropomorphizing (work conditions of the agent)
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_une-%C3%A9tude-r%C3%A9cente-de-stanford-r%C3%A9v%C3%A8le-que-activity-7462070011168288768-v4Cp
2️⃣7️⃣ Software developers who abandoned LLMs to go back to traditional
https://youtu.be/iXG_b1K8GK8?is=OGvvC-40wdZiku_s
https://youtu.be/pzkwn3hu1Cc?is=kzL6Dw9v0YW2q4uh
2️⃣8️⃣ Software project with strict anti-LLM policy and the reasons why
https://www.linkedin.com/posts/minh-t%C3%A2m-tran_the-zig-projects-rationale-for-their-firm-activity-7462098611229638656-64xk
2️⃣9️⃣ Bun's migration from Zig to Rust : (+1million, -4k) lines of code in 11 days
https://www.linkedin.com/posts/fabricebernhard_1009257-lines-of-code-migrated-in-11-days-share-7460996434058805248-key-
L'IA ne va pas nous remplacer : elle va nous rendre idiots.
Les chatbots soignent la dépression, mais attention !
L’IA se révèle étonnamment efficace pour traiter l’anxiété et la dépression. Des études sérieuses montrent des résultats concrets.
Mais il y a un revers à la médaille : atteintes à la vie privée, dépendance et risque de remplacer le contact humain par du code.
Cet épisode analyse les points forts et les risques de la thérapie par IA, et explique pourquoi des millions de personnes y ont recours malgré tout.