X post by **Andrew Ng** from **August 14, 2026** (16:29 UTC), reprising the "Dear friends" letter from ***The Batch* #366** (DeepLearning.AI, same date), ~900 words. Ng presents **The AI Engineering Skills Map** and publishes **four skills** held to be the most important. **(1) Building and deploying AI applications** — the specificity is named: *« The key difference between AI and non-AI applications is that the former has unpredictable outputs »*, hence the emphasis on *evals* and error-analysis loops. **(2) Software engineering fundamentals**, because *« Understanding software fundamentals allows you to recognize what tradeoffs even exist »* — the inexperienced developer fails *« because they don't know what context to give their coding agent »*, hence the goal of *« steering coding agents using the precise language of software engineering »*. **(3) Using coding agents**, in an operational formulation: *« help the agent autonomously close loops by providing verifiers or evals »*, and *« knowing how much to intervene and how much to leave them alone »*. **(4) *Shaping the build***: *« Given a clear spec, coding agents are rapidly improving at delivering to it. Thus, our work as engineers is shifting toward deciding what should be in the spec »*, paired with *« Engineers should no longer expect to be given a pixel-perfect design and asked only to implement it. »* A **terminology note** carries most of the framing: Ng talks about **skills** in AI engineering and **not the role** "AI Engineer", with an explicit analogy — *« All developers today should know how to work with the cloud, and only a smaller number have a "Cloud engineer" title. »* The whole is backed by *« an analysis of more than 10,000 job postings, dozens of structured interviews with experts, hiring managers, and recruiters, surveys, and other online data »*, of which **no numeric results are published**: Ng describes his process as *« informally… akin to running clustering »* and announces a detailed map in future posts. He states the interest in the second-to-last sentence: *« DeepLearning.AI's principal focus is to help developers gain these AI engineering skills. »*
#AI Engineering Skills Map#skills map#Andrew Ng
**Andrew Ng** — fondateur de **DeepLearning.AI** · general partner d'**AI Fund** · cofondateur de **Coursera** et de **Google Brain** · ancien chief scientist de Baidu. Texte signé · à la première personne · écrit *« with my team »* sans qu'aucun collaborateur soit nommé. Publié le **14 août 2026** sur X et dans ***The Batch* n°366** — même texte aux deux endroits ; préférer *The Batch* pour toute citation durable. Quatrième fiche Ng du corpus · après les lettres n°350 (24 avril) · n°352 (8 mai) et n°359 (26 juin).
Doctrinal manifesto published on **meta.com** on **August 10, 2026**, signed with only a first name (*"– Mark"*) by **Mark Zuckerberg**, under the title *"The Future is for Everyone: The Path to a Positive AI Future"*, ~6,500 words. Three principles are announced from the outset: individual empowerment as a source of prosperity, invention as the primary purpose of superintelligence, balance of power as the foundation of safety. **(A) The central argument is a political argument**, stated as a short chain: *"Humanity is not a monoculture"* — people's values encode opposing trade-offs, no technical solution can align simultaneously with conflicting interests, so any singular superintelligence would have to prioritize certain values over others and would thereby be incapable of being benevolent toward everyone. Hence the formula: *"There is no such thing as a singular benevolent superintelligence."* Safety is reframed as a problem of power distribution, illustrated by a thought experiment repeated three times (a single superintelligent lawyer versus everyone having one; the same for cybersecurity, then for business). **(B) A redefinition of alignment**: *"Solving alignment is necessary for billions of people to adopt personal superintelligence agents. But it also implies that if we reach a state where billions of people are using and scrutinizing personal superintelligence agents, then we will have solved alignment with their interests."* The corollary targets the rest of the industry without naming it: *"the most dangerous scenario would be leading labs training powerful models and keeping them for themselves."* **(C) Datable commitments**: a **fully private** mode where *"even Meta"* cannot see or grant access (a WhatsApp analogy); **free** versions for billions of people paired with a **dynamic bidding mechanism** for paid compute; the announced **resumption** of open source releases — *"we will soon resume releasing some open source models"*; and a structure giving the **independent board** the power to approve release safety criteria and verify each release's compliance, with the author acknowledging that Meta is a founder-controlled company. **(D) Two public-policy proposals**, repeated three times: that labs share **intermediate training checkpoints** and engineers with the government rather than an end-of-cycle review, and that the **physical production** of dangerous materials be regulated rather than the spread of knowledge. The text's sourcing is nearly nonexistent.
#Mark Zuckerberg#Meta#Meta Superintelligence Labs
**Mark Zuckerberg** — fondateur et PDG de **Meta**. Texte signé du seul prénom (*« – Mark »*) · publié le **10 août 2026** sur un domaine dédié de meta.com. La signature n'est pas « Meta » · et l'alternance des pronoms est régulière : **« we » pour les engagements de l'entreprise** (*« we will offer free versions »*, *« Meta is implementing a governance structure »*) · **« I » pour les affirmations normatives ou contestables** (*« I think this view of alignment is fundamentally flawed »*, *« I propose that companies developing frontier AI should… »*, *« My honest guess, and it is a guess »*). Les engagements produits et de gouvernance sont au « nous » · les propositions de politique publique au « je ».