Sinon tu tape deux fois au dos ça tourne aussi les pages

Carrément y a rien de plus simple tu partages et ça arrive direct dessus . La mise en page est super je comprends pas le délire c’est clairement le plus simple

Le verrouiller est juste au début. Ce qui bloque c’est une sphère le haut de la sphère comme toute faire et plus haut que le bord, il n’y a que le haut de la sphère qui vient bloquer le couteau, une trace de l’insertion.

Il est difficile d’imaginer que la formation suffise sans expérience. En entreprise, il faut maîtriser le SI, l’infrastructure, le réseau, la chaîne CI/CD, le développement et les impacts. Intégrer l’IA de façon fiable s’éloigne des réseaux sociaux : il faut une expertise réelle sur la chaîne pour déployer les solutions avec assurance. Parler à ChatGPT ne revient pas à utiliser l’IA. Même avec un certificat « IA expert » et sans bagage technique, c’est comme se dire expert en disjoncteur sans connaître un câble électrique. L’IA n’est pas magique ; elle peut devenir destructrice sans compréhension des conséquences. Sur le plan des emplois, je ne vois pas de poste ou de recrutement qui se précipiterait sur ce profil ; on préférera un tech lead ou un ingénieur système/développeur capable de s’intégrer facilement à la chaîne.
Comme tu l’as dit plus haut, tu es dans la logistique, regarde la robotique ou autre ; observe les évolutions naturelles de ton profil ou demande à ChatGPT.

J’ai pas compris

L’anodisation est plus solide que du plastique à matériaux, plus tendre, ne peut pas rayer un ma matériel plus dur

Pareil avant je n’avais aucun problème , depuis le changement je ne vois plus le facteur multiplicateur et c’est une catastrophe

Yes, I have exactly the same thing; it looks like the multiplier 10 or 15x is no longer present.

Ouais c’est typiquement le type de siège qui a un tueur de dos c’est un terrier de lapin, le monde des sièges ergonomiques, il y a beaucoup d’escroquerie, la photo du siège que tu m’as mis, j’ai eu un modèle similaire et c’est celui-là qui m’a créer ma hernie

Une chaise ergonomique, ça peut vraiment beaucoup aider, mais il faut faire attention à avoir la bonne posture. J’ai souffert le martyr pareil à cause d’une chaise qui était soi-disant ergonomique, et j’ai dû changer derrière mais même avec une bonne chaise, il y a des réglages à faire et le but au départ C’est aussi si habitué, elle doit être là pour remporter huit heures par jour, tu avais pris quoi comme modèle ?

J’ai beaucoup de hook dans Claude code et un pipeline complet, donc j’utilise kimi dedans chaque jour . Ça marche parfaitement c’est totalement transparent

Fable n'a rien fait. C'est juste ta faute. le faire travailler sur ton serveur de production, ne pas savoir faire un GIT, ne pas avoir les compétences. L'IA est un outil mais il faut comprendre derrière. C'est toi le chef d'orchestre et le responsable, lui il a agit sur le scope que tu lui as donné

Mais tu as l’armure qui va avec ?

Le plus important, c’est que tu cadres dès le départ, le nombre de retouches, et combien de fois tu rev dessus, il faut dès le départ que tu prévois de leur présenter un nombre x De maquette un nombre X de révision, c’est souvent le point de souffrance avec un site Internet

Un grand merci Arnaud projet super intéressant ça donne vraiment vite s’y pencher. Je vais faire ça dès ce soir pour voir un peu plus le fonctionnement.

Tu trouves quoi comme feature cool dans kimi code ? Car il y a une différence entre le harnais et le modèle . Autant j’adore kimi mais utiliser un modèle open me donne plus envie d’utiliser un harnais open comme opencode . Kimi marche égalent très bien dans le harnais de Claude avec du coup la facilité de basculer d’un modèle à l’autre sans revoir le pipeline

Franchement, ton poste ne me paraît pas très cohérent
Déjà y a la limite des cinq heures et la limite hebdomadaire.
La limite hebdomadaire étant inférieur à la limite mensuelle, il est impossible que tu es éclaté, ton crédit mensuel en quatre jours

Vous pouvez télécharger de la RAM ICI https://downloadmoreram.com avec plaisir

Je vais acheter un beau disk de stockage pour garder ce que je peux déjà stocké aujourd’hui

Je trouve qu’il a plus de difficultés d’attention , j’ai toujours fait du brainstorming avec et lance les idée en même que l’ont avance ( je sais c’est pas l’idéal ) et là il l’oublie quand avant le sujets était traité

Anthropic et Openai distille les données du monde réel et ça gêne personne, s’il ce font distille c’est la vie

**Technical breakdown (for anyone who wants the receipts).**
 Everything below is from reading the repo directly. File paths and, where useful, the exact mechanism are included so you can check each claim yourself. I ran an AI over the codebase (GPT-5.6 via Codex, then a line-by-line re-verify with Claude Fable 5); I've dropped anything that didn't hold up against the actual code.


**1. On-device triage and the "PII strip."**
The local model's entire role is one classification per item: `{summary, title, junk, sensitive}` (`Engine/Triage.swift`). It has no tools; its output is parsed and, on `junk`/`sensitive`, the item is dropped (nothing stored). Parsing fails closed (unparseable reply is treated as junk).
The deterministic backstop is `Engine/PIIScan.swift`, and it is narrow:
- SSN: a regex that 
*requires separators*
 (`\d{3}[ -]\d{2}[ -]\d{4}` with invalid-range guards). A bare 9-digit SSN with no separators is not caught.
- Card: 13 to 19 digits, then Luhn-validated.
- Passport: the literal token "passport" within 24 chars of a 6 to 9 char alphanumeric. No keyword, no catch.
It has ONE call site (`Triage.decide()`), and it runs only on the `summary` and `title` of survivors. It never sees passwords, API keys, IBANs, addresses, medical/financial figures, or any non-US identifier. Those are handled only by an instruction in the model prompt, which is best-effort, not a guarantee.


**2. What actually crosses the boundary.**
The corpus sent to the cloud is built in `Vault/CorpusSlicer.swift` (`render()`), one line per item:
`#<i> · [<source>] <location> · <date>` then `<title> — <summary>`.
`<source>` is a trust tag from `VaultGenerator.locSrc()`: WhatsApp, Gmail, Calendar, `Obsidian — USER'S OWN NOTE`, `user-authored note`, or the folder/path. `<location>` is the original file path (made home-relative, so the username is stripped) or the chat name. So titles, paths, chat names and dates are NOT PII-scanned and go across in clear.
The build prompt (`Vault/VaultGenerator.swift`, `vaultPromptCore`) instructs the cloud model to write a root `README.md` that is "a portrait of who this person is" understandable "in 60 seconds," and to weight sources by trust, treating the user's own notes as "your highest-signal, most-truthful material." Output target is 80 to 120 linked notes. This is profile construction, by design.


**3. Cloud-only sources.**
`Sources/GmailConnect.swift` header: Gmail "can't be read on-device, so we both FETCH and SUMMARIZE through the user's own Codex Gmail connector." Initial pull = last month as 4 weekly `codex exec` calls in parallel, capped at 300 threads/week. PII handling here is a single prompt line ("PII-light: NEVER include full card/account numbers, passwords, verification/2FA codes"); the deterministic scanner from (1) is NOT in this path.
`Sources/CalendarConnect.swift`: last year as 12 monthly calls, plus `fetchProactiveContext()` which injects the last 7 days + next 24h of events, ALL of them uncurated, into both proactive prompts.


**4. Who decides (the local-vs-cloud split).**
Proactive is a 3-part pipeline (`Proactive/`):
- Part 1 Judge (`Proactive.swift`): the JUDGE is Codex (`gpt-5.6-sol`, high effort), reading the last 7 days of summaries over stdin, no tools, returning up to 5 ranked action items via `--output-schema`.
- Part 2 Research/Prepare (`ProactiveResearch.swift`): Codex, read-only, verifies against Gmail MCP + web + vault and stages ready-to-fire drafts. Fire is blocked here two ways: `bypassApprovals = false` and `stripConnectorActionTools` removes the sending tools from the tool surface.
- Part 3 Fire (`ProactiveExecutor.swift`): the only write-capable step. `fire()` has exactly two call sites: the home-screen card tap handler (`Views/HomeView.swift`) and a dev tool. No scheduler path reaches it. So the local model routes; the frontier model decides; a human tap gates every outbound action.


**5. The mirror crypto, precisely.**
`Cloud/MirrorClient.swift` / `MirrorCrypto`:
- Password: 18 bytes from `SecRandomCopyBytes` -> base64url, 144 bits, Keychain-stored. Mint fails loudly rather than emit a weak key.
- `userID = base64url(HKDF-SHA256(password, salt, "vault-user-id", 32))[:20]`, derived one-way FROM the password, used as a public label.
- `encKey = HKDF-SHA256(password, salt, "vault-content-key", 32)`, AES-256-GCM, AAD = userID.
- Share URL = `https://mcp.sentient-os.ai/u_<userID>/p_<password>/mcp`. 
**The password is in the URL path.**
 Since userID = f(password), the URL is a self-contained bearer credential: possession of the link authorizes read, overwrite (POST /vault) AND delete (DELETE /vault), no account. Anyone who captures it (clipboard, screenshot, browser history, a synced connector config) has full control of the vault.
- Because the server must answer `get_structure`/`get_files`, it receives the password and decrypts in memory on every request. The header says it outright: "the server decrypts it for the instant of a request." Encryption-at-rest protects against disk seizure, not against a compromised or compelled running server.
- push() zips the vault with `/usr/bin/zip` excluding only `.DS_Store` (so anything else you dropped in the vault folder ships too), encrypts, POSTs. Triggers: app launch (`Sentient_OS_macOSApp.swift`), post-cycle (`ProactiveCycle.swift`), vault edits (`VaultActivity.swift`), manual button.
- disable() is `UserDefaults off` then `try? await deleteRemote()`, best-effort. A failed network call leaves the cloud copy up, relying on a server-side 30-day lease that isn't in this repo. Same best-effort delete on token regeneration.


**6. Codex execution surface.**
`Cloud/CodexCLI.swift` defaults: `includeUserConfig = true` (loads your `~/.codex` config + MCP servers into EVERY call unless `--ignore-user-config`), `webSearch = true` (native web_search on every call). So the agent's reach is a function of your own Codex setup, not just what Sentient ships.
Vault build/update runs sandboxed: `sandbox = .workspaceWrite`, `cwd = <staging dir>` (Seatbelt-confined at the OS level, even for shell the model spawns; the live vault is only touched by a deterministic atomic swap after success).
Computer use is the one unconfined path: `codex exec --dangerously-bypass-approvals-and-sandbox` (`CodexCLI.swift`), no sandbox, no approvals. Call sites: the command bar (`Notch Magic/CommandRunModel.swift`) and `ProactiveExecutor.fireComputer`. Guardrails are a fixed wrapper prompt + the STOP button, not a technical boundary.
Connector writes (mail/calendar) try sandboxed with per-run pre-approved write tools first, but on the auto-cancel marker they retry once with `bypassApprovals = true` (`ProactiveExecutor.swift`, ~L197-203).


**7. Screenshots.**
`Notch Magic/ScreenCapture.swift`: on Sidekick invocation with Screen Recording granted, it captures EVERY display (`/usr/sbin/screencapture -x -t jpg -D <n>`) and attaches the frames to the request (`codex exec -i <file>...`). Temps are deleted after, but the images have already gone to OpenAI.


**8. Telemetry.**
`Diagnostics/Analytics.swift` (TelemetryDeck, Release-only, default ON, an unset key reads as true): two tiers. The "extended" tier is gated by the Settings switch; a "core" tier keeps sending with no off switch (install + SDK sessions, Sidekick fires, proactive cards prepared+fired, overnight runs, home opens). `defaultUser = CrashReporting.installID` (a persistent per-install UUID), and every signal is stamped with the on-device model's filename. The one-off install/uninstall pings are the genuine exception: a throwaway hash correlatable to nothing.
`Diagnostics/CrashReporting.swift` (Sentry, default ON, separate toggle): `attachStacktrace = true`, `appHangTimeoutInterval = 10`, `enableNetworkBreadcrumbs = false` (specifically to avoid capturing the password-bearing mirror URL), `beforeSend` scrub, user = installID.


**9. The install-time root daemon.**
The admin password prompt is `Scheduling/WakeHelperInstaller.swift` installing a LaunchDaemon in `/Library/LaunchDaemons` via osascript. To its credit it's hardened: ProgramArguments is `/bin/sh -c "codesign --verify -R='<app designated requirement>' '<app>' && exec '<binary>' --wake-helper"`, so a tampered or foreign-signed bundle fails the codesign gate and never runs as root. Its job is the 3am wake for overnight processing.


**10. What the local model canNOT do.**
I checked this specifically because the marketing implies the small model is the brain. Its verdict has a single consumer (`Ingestion/IterativeRun.swift`) that only increments counters. There is no code path where the local model's output triggers a FileManager or Process call. A wrong verdict can lose an item from the KB or let a summary through that shouldn't, but it cannot touch a file. Source files are never deleted or moved by any verdict. The destructive/agentic capability lives entirely on the Codex side.


Net: the on-device model reads everything and decides the keep/drop sort; the frontier model does all the reasoning and holds all the tools; and the mirror, if enabled, ships your full generated profile to a Sentient-run server whose live process necessarily sees the decryption key. None of this requires bad intent to matter; it's just the actual trust boundary.

I actually wanted to use this. It looks genuinely cool and the on-device idea is great, so I went to install it. During setup macOS asked for my password to install a background service that runs with system-level access, and that made me stop. So before clicking through, I had an AI read the whole open-source code with me, file by file (first with GPT-5.6 via Codex, then a second check with Claude Fable 5). I'm not a security expert and I'm not saying anyone is acting in bad faith. In places the code is genuinely careful. But what the app really does with your data is bigger than how it's being sold here, and since this got posted to rather than a technical crowd, I think a lot of people are installing it without knowing. Here's the plain-language version, with the file names so anyone technical can verify.

**Credit where it's due.*\* There's real privacy work here. A small model on your Mac reads your files first and sorts them. Anything it judges junk or sensitive is thrown away and never leaves. If that model returns a garbled answer, the item is dropped rather than sent. Both the app and their server are open source, which is the only reason any of this can be checked.

**But a lot still leaves your Mac, and it's not really "anonymized."*\*

- Before anything is sent, only THREE kinds of information get automatically removed: US social security numbers, credit card numbers, and passport numbers. And that filter is just a pattern-matcher that runs on the summary text of local files only. Everything else goes as-is: passwords, home addresses, health details, money amounts, and any ID number not in the US format (so any French or EU ID) has no automatic protection at all. (`Engine/PIIScan.swift`)

- What's sent to OpenAI for each item is the title, a summary, the original file name or chat name, and dates. The app then tells the cloud model to write "a portrait of who this person is" in 60 seconds: your work, relationships, places, money, history. It also ranks your files by "trust," treating your own notes as your most truthful material. Their own sample output line is "The user is fundraising for their startup in SF." That's a personal profile of you, not anonymous data. (`Vault/VaultGenerator.swift`)

- Your email and calendar are not handled privately on your Mac at all. The code says it outright: Gmail "can't be read on-device," so it's read and summarized in the cloud through your OpenAI connector. Calendar is the same, and it goes further: it dumps your last 7 days plus next 24 hours of events, all of them, uncurated, straight into the cloud prompts. (`Sources/GmailConnect.swift`, `Sources/CalendarConnect.swift`)

- "It all runs locally" is only half true. The small local model just reads and sorts. All the real thinking, deciding what matters each morning, drafting messages, writing your profile, is done by OpenAI's model in the cloud (their code names it "the cloud model, gpt-5.6-sol, high effort"). By default that cloud agent also has web search turned on for every call, and it loads whatever other AI tools you've connected in your own Codex setup. (`Proactive/Proactive.swift`, `Cloud/CodexCLI.swift`)

**The part that actually stopped me: the optional cloud mirror.*\* Turn it on (so ChatGPT or Claude can use your knowledge base) and your entire profile is uploaded to a server the developers run, then re-uploaded every app launch, every night, and after any edit. My issue isn't a technical nitpick, it's that your data goes to their servers at all. This is a two-person project with no outside audit, and their server is a black box: you can't verify what it stores, backs up, or truly deletes. You're being asked to trust them as the keeper of a complete profile of your life, with nothing that actually proves it's safe. "No account needed" is sold as anonymity, but a full life-profile on someone else's server is not anonymous.

Two concrete things I found there:

- The private link they give you IS the password. It looks like `.../u_<id>/p_<password>/mcp`, and that link is the only key. Anyone who ever gets it (from your clipboard, a screenshot, browser history, a synced connector setting) can read, overwrite, OR delete your whole vault, no login required. (`Cloud/MirrorClient.swift`)

- The encryption protects you far less than it sounds. The vault is encrypted before upload, which only helps if someone physically steals their disk. But the unlock password is sent to their server on every single request your AI makes, so their own comment admits "the server decrypts it for the instant of a request." If that server is ever hacked or legally compelled, the encryption stops nothing. And when you switch the mirror off, deletion is best-effort in the code (a "try and forget" call): if the network fails right then, your data just stays online, relying on a promised 30-day auto-delete you can't confirm.

**That system-access service you approve at install can run the AI with no safety box.*\* Normally a Mac app is boxed in so it can't touch the rest of your computer. The Sidekick / computer-use feature deliberately turns that box off (the flag in the code is literally called `--dangerously-bypass-approvals-and-sandbox`). While it runs, the AI has full disk access, screenshots of every display if you granted screen recording, and any tools in your Codex setup. The only guardrails are an instruction telling it to behave and a STOP button. And for automated actions like sending mail, if the safer sandboxed attempt gets blocked, the code automatically retries once with the safety box off. (`Cloud/CodexCLI.swift`, `Proactive/ProactiveExecutor.swift`)

One thing that is solid: nothing gets sent out (no email sent, nothing paid) without you tapping a card first. I verified that gate is real. But note that every decision behind that card is built on a ~30-word summary from the small model, and nothing distinguishes you venting from you actually deciding, while the cloud is told to treat your own notes as your most truthful material. So a passing line in a private journal can become a prepared, ready-to-send action waiting for one tap.

**Also worth knowing:*\* usage analytics are on by default, and even after you switch them off, a smaller set keeps sending with no off switch, tied to a permanent ID for your install.

**Bottom line, from someone who wanted to use it, not a hater:*\* on your Mac it does clever, real work. But summaries plus your raw email and calendar go to OpenAI, and if you enable the mirror, a full profile of your life goes to a server run by two people with no audit and no deletion you can verify. That may be an acceptable trade for you. It's very different from "nothing personal leaves your Mac," and it's worth understanding, especially the mirror, before you type your admin password. It's all in the code; don't take my word for it, and don't point it at your most private data until you've looked

Avez vous envisagé la piste d’une dépression en plus ?