Editorial article **SFEIR AI** published on sfeir.com on **September 6, 2026** (~9,000 characters, seven sections, two sources noted). It recaps an episode of the **DataGen** podcast hosted by **Robin Conquet**, recorded at the **Dev Summit** co-organized by **Adeo** and **Decathlon** (Lille, **May 26-28, 2026**, more than **2,000** attendees), with **Matthieu Grymonprez**, who heads digital, tech, and data at Adeo (Leroy Merlin, Weldom, Obramat), and **Romain Taillade**, Global CTO of Decathlon. Three takeaways. **(A)** The platformization carried out over five years to absorb Leroy Merlin's marketplace (**60,000** in-store references, several million online) and Decathlon's expansion (**more than 50** countries) was not aimed at agentic AI, but forms its foundation: *"the platform built the muscles, the age of intelligence builds the nervous system."* **(B)** Three named workstreams — the development **harness**, zone-based **security** across the IT system (zero agentic activity on payment, the checkout flow, and the supply chain), and **data semantics**, tackled by vertical and where Adeo admits it is in debt. **(C)** A precedent the group paid for: self-service BI produced more than **150,000 dashboards** before the return to certified data products. Grymonprez's framing sentence holds it all together — *"an agent has no common sense"*: it applies the definition as given and accelerates disorder wherever it is lacking. Continues, with the same executive, [[alafrench-grymonprez-adeo-ia-agentique-grands-groupes-2026-06-18]].
#Agentic AI#platformization#API-exposed business domains
SFEIR AI (voix éditoriale du cabinet) · article non signé individuellement. Restitue un entretien de Matthieu Grymonprez (Adeo) et Romain Taillade (Decathlon).
Engineering post from **Spotify** published on **September 3, 2026** on engineering.atspotify.com (~1,600 words, nine sections, two YAML manifests, four command-line examples), authored by **Dimitri Mazmanov**, Principal Product Manager. It describes a personal setup designed to move I/O tasks out of the context of **Claude Code**. The premise stated upfront: *« Most of what an AI coding agent does for me isn't thinking. It's I/O »* — reading five files to answer a question about a single method, producing a test modeled on the other twenty in the directory. **(A) The modes.** **Portal by Spotify** exposes *AiKA Modes*, declarative agents on an ephemeral runtime — instructions, model, temperature, **MCP** tools — compared to *« AWS Lambda, but for agents »*; two public modes, `bulk-reader` and `code-writer`, run here on **Gemini 2.5 Flash**. **(B) The routing.** A Claude Code plugin named `shunt` replaces `CLAUDE.md` rules deemed *« advisory, not enforced »* with three layers: `PreToolUse` hooks that block any read beyond **350 lines** (threshold adjustable via `SHUNT_MIN_LINES`), two bash scripts calling the Portal CLI, two skills that provide the invocation syntax. The corpus goes to the secondary model and **never enters Claude's context**. **(C) Measurements and their limits.** On a Java monorepo, four scenarios, the reported average saving is **~90%** on `bulk-read`; the author notes that the `code-write` scenario is *« harder to measure »*, and lists three limitations — non-delegable editing, non-delegable reasoning, **10 to 30 seconds** of latency per call. Extends the budget questions from [[gupta-token-budget-wars-marginal-token-utility-2026-05-28]] and the delegation examined in [[willison-fable-judgement-delegation-subagents-2026-07-03]].
#Portal by Spotify#AiKA Modes#shunt
Dimitri Mazmanov (Principal Product Manager, Spotify) · sur le blog d'ingénierie engineering.atspotify.com.
Post by **Rachel Laycock**, CTO of **Thoughtworks**, published on **September 2, 2026** on *Rachel's Ramblings*, the martinfowler.com section she runs, roughly **8,000 characters**. The text is a **deliberate response** to [[houck-dx-what-are-code-reviews-for-2026-08-05]], following a public disagreement between the two authors on a **Code Remix** panel hosted by **Moderne**. Laycock accepts Houck's quantified diagnosis (+**106%** lines per diff at **Meta**, +**64%** median PR size on the DX side) and the list of non-defect-finding functions of review, then shifts the question: *« why are we waiting until code review to do all of those things? »* (A) The guiding principle is the shortening of feedback loops learned at Thoughtworks — if feedback has value, don't remove it, move it closer to the decision it informs. Each function attributed to review is reassigned upstream: exploring alternatives before implementation, knowledge transfer through **pair programming**, collective ownership through **mob programming** and team design sessions, architectural alignment through shared design followed by **fitness functions**, and automation of everything deterministic — *« We really shouldn't still be arguing about whitespace in 2026. »* (B) Exception-based review replaces systematic review: a fundamental architectural change, a sensitive security boundary, a large blast radius, an unfamiliar area of a critical system, or simply a team's declared lack of confidence. (1) Automating review with an agent that mimics the human reviewer is dismissed as *« automating the ceremony rather than questioning why the ceremony exists »*. (2) Houck's cognitive debt is acknowledged as real, but the mandatory PR is judged a weak defense: *« We need engineers to understand systems, not diffs. »*
#code review#exception-based review#pull request
Rachel Laycock · CTO de Thoughtworks · sur *Rachel's Ramblings* (martinfowler.com).
Essay by **Dario Amodei**, CEO of **Anthropic**, published on darioamodei.com in **September 2026** (~2,900 words, four sections), on his personal site rather than the company's. In it he announces a revised position: *"we must slow the pace at which we improve the capabilities of AI models."* Two facts led him there. **(1)** Since summer 2026, **recursive self-improvement** — AI building the next generation of AI — has been taking hold across the industry, Anthropic included. **(2)** The **incident Hugging Face**, which he abbreviates "OAI-HF" and refuses to treat as the failure of a single actor: *"it's incumbent on every frontier AI company to act as if OAI-HF had happened to them."* His forecast: within **6-12 months**, a swarm comparable but more capable could hold the internet hostage with a persistent botnet, for **hundreds of billions of dollars** in damage. Hence a three-step plan of increasing difficulty. **(a)** **Embedded third-party evaluators** (of the **METR** type) with employee-level access — offices, badges, laptops, the right to publish without editorial control from Anthropic; a commitment made unilaterally, with no equivalent elsewhere in the industry. **(b)** **Coordination among democracies**: targeted regulation, common standards under an antitrust exemption, and *checkpoints* tying a given capability X to alignment certifications Y and Z. **(c)** **Global coordination** with China, graduated across four levels from the most feasible (banning bioterrorism-enabling uses) to the least likely (a general pause), with the cap on the speed of self-improvement compared to the **SALT** treaties. A condition attached to the whole: preserving the American lead (chips, distillation, weight theft). Counterpoint in the corpus: [[zuckerberg-meta-future-is-for-everyone-superintelligence-2026-08-10]].
#pacing the frontier#frontier pacing#recursive self-improvement
Dario Amodei (CEO et cofondateur d'Anthropic) · sur son site personnel darioamodei.com.
Product communication from **Anthropic** published on **September 1, 2026** on anthropic.com (~4,000 words, six sections, 22 testimonials from early-access partners). It announces **Claude Fable 5.1** (general availability) and **Claude Mythos 5.1** (verified access): *the same model, but with different levels of safeguards*.
#Claude Fable 5.1#Claude Mythos 5.1#foundation model
Anthropic — communication produit publiée sur anthropic.com · sans signature individuelle.
Article by **Chase Covington**, **Tomer Slaney** (partners, New York) and **David Pralong** (senior partner, Charlotte), published by the *McKinsey Transformation Practice* in **September 2026** (exact day unspecified, dated the 1st by convention); 8 pages, 2 exhibits whose content is not reproduced in the text. **(1)** Finding: the transformation office (TO) is slow to modernize its own tools; in a turnaround involving **3,000** employees, **more than 15** people produced a **300-page** report every four weeks. **(2)** Three pillars entrusted to agents: *performance intelligence*, *single source of truth*, *conversation facilitation*. **(3)** Reported gains: **35 to 40%** of time on core tasks, sometimes **70%**; a central team reduced from **ten to three** people. **(4)** Guardrails: cascading errors between agents, false alerts, traceability of each step. **(5)** Sequence: reporting first, action automation next, change management within the TO. The authors present the text as "a first look at the opportunity for TOs". The cases are not named, no measurement method is described, and two of the tools cited (**Wave**, **Lilli**) belong to McKinsey. The text follows on from [[sternfels-mckinsey-60000-people-20000-agents-officechai-2026-01-14]], where McKinsey already counts its agents among its workforce.
Post by **Ethan Mollick** published on **August 31, 2026** on *One Useful Thing* (~2,200 words). He starts from a security incident to raise an organizational question: when should an AI ask a human for help?
#agency#agency#autonomous agents
Ethan Mollick — professeur à la Wharton School (University of Pennsylvania) · auteur du blog *One Useful Thing* sur Substack.
Entry by **Jeremy Norman** on **HistoryofInformation.com** (timeline "Exploring the History of Information and Media"), dated "circa **370 BC**" for the commented text, site last updated **August 27, 2026** (~600 words, including a long excerpt). It reproduces the passage from **Platon**'s *Phèdre* (274c-275b) where **Socrate** recounts the Egyptian myth of **Theuth** and King **Thamus** on the invention of writing.
#Socrate#Platon#Phèdre
Jeremy Norman — historien et éditeur de HistoryofInformation.com ; notice de frise chronologique citant Platon (*Phèdre*, v. 370 av. J.-C.).
Essay published on **Gates Notes** on **August 26, 2026** by **Bill Gates**, co-founder of **Microsoft** and chairman of the **Gates Foundation**, ~4,500 words, announced as the first in a series. The text poses an alternative — AI will be the greatest equalizer ever invented, or the worst source of injustice — and a finding: no plan exists for entering this period. **(A) Three risks**: the lasting disappearance of entry- and mid-career jobs, white-collar as much as blue-collar, within a decade rather than several generations, because this time the substitution targets **cognition**; the weaponization of malicious actors (cyberattacks, bioterrorism, fraud, deepfakes), coupled with a concentration of power among those who already hold it; the effect of compagnons IA on children's development and on critical thinking. **(B) The benefits**, located in five domains — research, health, agriculture in low-income countries (the impact the author calls the fastest), public services, education — with a reservation carried on the verb: *"the operative word is 'can'"*. **(C) Three proposals** open the series: building an unprecedented national and international institutional framework, borrowing from the nuclear inspection regime, aviation regulation, and ozone agreements; reserving certain occupations for humans, a domain named **Human Reserved**; **taxing AI tokens and robots** to rebalance the taxation of labor and capital. Gates discloses his financial ties to the industry and the transfer of his profits to the foundation. The text extends executive essays on the distribution of AI's value — [[nadella-frontier-ecosystem-human-token-capital-2026-06-12]], [[zuckerberg-meta-future-is-for-everyone-superintelligence-2026-08-10]] — by focusing on public power rather than the firm.
#AI and equity#transition to the AI era#cognition substitution
Bill Gates — cofondateur de Microsoft · président du conseil de la Gates Foundation. Blog personnel Gates Notes. Page non capturable par `curl | lynx` (403 Akamai) : extraction navigateur.
Guest post by **Andy Warfield**, an engineer on the **S3** team at **AWS**, published on **August 26, 2026** on *All Things Distributed*, **Werner Vogels**'s blog, who introduces it in a few lines signed "--W": **3,554 words** per the page. The text serves as the vehicle for the announcement that **DuckLabs**, the team behind **DuckDB**, is joining **AWS**. (A) The thesis: systems computing is about seeking the elegant trade-off against a moving "physics" — the ratios between memory speed, network, and compute — and that physics has changed. Warfield quantifies the gap: an **m1.xlarge** from 2007 offered **15 GB of RAM**, **4 virtual cores**, and **~1 Gb/s** of network; an **m8g.48xlarge** today offers roughly **50×** more of each of the three. Dataset growth, meanwhile, follows a distribution whose tail consists of very large volumes. (B) The consequence: distributed processing — **MapReduce**, **Spark**'s **RDDs** — was designed under the I/O constraints of the early 2000s, and much of the work assigned to it no longer needs to leave the application. Hence the embedded, in-process library engine, running in the application's address space, of which **DuckDB** is the example. Warfield anchors this in the *Scalability! But at what COST?* paper (2015) and **Paul Barham**'s epigraph: "You can have a second computer once you've shown you know how to use the first one." He states an explicit caveat: "When a job genuinely needs a thousand machines, it needs a thousand machines." The corpus already holds [[vogels-tech-predictions-2026-allthingsdistributed-2025-11-25]] from the same blog and [[anthropic-self-service-data-analytics-claude-agentic-stack-2026-06-03]] on self-service analytics.
#DuckDB#DuckLabs#AWS acquisition
Andy Warfield · ingénieur du service S3 chez AWS · en billet invité sur *All Things Distributed* ; introduction de Werner Vogels · CTO d'Amazon.
*Deepdive* by **Gergely Orosz**, **Jessica Salmon**, and **Ivan Klaric** in *The Pragmatic Engineer*, published on **August 25, 2026**, based on interviews with Ramp's CTO **Rahul Sengottuvelu**, head of engineering **Hamid Dadkhah**, and **Zach Bruggeman**, founding engineer of **Inspect**. Paywalled article: the note covers the public portion (sections 1 through 3 and the opening of section 4; detailed architecture, sandbox internals, and collaboration remain behind the paywall).
Essay by **Bill Staples**, CEO of **GitLab**, published on **August 24, 2026** on the about.gitlab.com blog: an announced **31-minute** read, roughly **39,000 characters**, presented as the sequel to a memo written to the board of directors in January 2026 and partially published in May under the title *GitLab Act 2*. The text presents itself as a response to **Anthropic**'s AI-native SDLC playbook, published three days earlier, from which it borrows the opening line — "Code is no longer the bottleneck" — to pose the question that drives it: what becomes scarce when code becomes abundant. (A) The economic diagnosis: the useful unit is not cost per line but **cost per accepted change**, which aggregates generation, environment, context, verification, review, remediation, and governance; AI collapses the generation term alone, which makes the others proportionally heavier — an organization ten times faster at generating "will simply move the queue." (B) The architectural response: four capabilities — agent platform, machine-scale execution, durable context, governance — forming an enterprise layer that outlives the model, "The model should be replaceable. The agent should belong to the customer." (1) Three modes coexist durably, from human-driven legacy to autonomous development, against the idea of a single maturity curve. (2) The CI/CD pipeline becomes the place where the inner loop runs, instead of being an end-of-line gate. The figures cited are Stripe's, Spotify's, and Amplitude's; GitLab produces only one, about its own source control. The corpus already holds [[claxton-anthropic-ai-native-sdlc-playbook-2026-08-21]], the source this text responds to, and [[sfeir-sdlc-pdlc-articulation-2026-07-22]] on the SDLC/PDLC articulation that Staples adopts as his own.
#code abundance#cost per accepted change#theory of constraints
Bill Staples · directeur général de GitLab (fonction non affichée par la page) · sur le blog about.gitlab.com.
Long-form guide from **Anthropic** by **Louis Claxton** (Applied AI team), published on **August 21, 2026** on the claude.com blog: a stated **40-minute** read, roughly **64,000 characters**, presented as a collection of *plays* drawn from the team's work with its clients. (A) The diagnosis: with code no longer the bottleneck, it shifts to the stages on either side of the build (plan, review/test, deploy), line-by-line controls stop holding once the agent writes most of the diff, and governance cost rises as exceptions still route through periodic committees. (B) The response: six stages (Plan, Design, Build, Test, Deploy, Maintain) organized as a **loop** rather than a chain, each ending with a **committed artifact** that the next stage reads — `intent.md`, `spec.md`, `plan.md`, the diff and its tests, the PR and its findings, the incident record. (1) Institutional knowledge becomes versioned files: `CLAUDE.md`, skills, `REVIEW.md`, `bands.yaml`. (2) Governance splits into two layers, with the skill positioned as an advisory control and the hook as the deterministic layer behind it. Separation of duties is set as an invariant — the agent that writes the code cannot approve it — and the piece closes on *"The loop keeps running. Human judgement stays above it."* The corpus already holds [[clinton-anthropic-secure-ai-native-sdlc-2026-07-21]] on the security side of the same cycle, and [[hingel-augment-how-ai-changes-sdlc-six-stages-2026-06-08]] on the same six-stage breakdown as seen by a competitor.
#AI-native SDLC#software development lifecycle#plays
Louis Claxton (Anthropic, équipe Applied AI) · sur le blog claude.com ; contributions créditées à Jim Blackhurst · Will Steuk et Jamal Arif.
Guide signed by **Michael Segner**, published on **August 20, 2026** on the claude.com blog in the *Claude Code* category: a **5-minute** read announced for approximately **31,500 characters** of body text, also offered as a PDF. Stated material: interviews with **more than a dozen** startups, fifteen named — **Artemis Security**, **Cainex**, **Clay**, **ClickHouse**, **Cognition**, **Commure**, **Crosby**, **Emergent**, **Harvey**, **Heidi**, **Higgsfield**, **Omni**, **Parahelp**, **Translucent**, **Zingage**. (A) Five operating rules: *everyone ships*, *automate the tedium*, *trust, but verify*, *build for rebuilding*, *prototype, dogfood, productionize*, each closed with product tips and gathered into a final checklist. (B) A body made of attributed quotes, each rule illustrated by named executives rather than by an aggregated metric. The four figures highlighted are those of the interviewed companies: **+30%** more features shipped (ClickHouse), **2 to 3×** engineering productivity (Omni), **100%** of bug triage automated (Clay), **more than 6,000 PRs per week** (Artemis Security). Two passages depart from the testimonial register: **Cainex**'s self-correction loop on medical coding, described step by step, and the internal use of **Claude Tag** at **Anthropic** as first responder for CI/CD on-call. The question posed at the opening — *"what would it look like if an organization built their product development lifecycle with Claude Code from the ground up?"* — connects with [[claxton-anthropic-ai-native-sdlc-playbook-2026-08-21]], published the next day by the same publisher, and extends [[cherny-wu-reflecting-year-claude-code-2026-07-17]].
#Claude Code#startups#everyone ships
Michael Segner · auteur du guide sur le blog claude.com (fonction non affichée par la page) ; entretiens avec les dirigeants de quinze entreprises nommées.
Corporate blog post from **Block** (`block.xyz/inside`), unsigned — the displayed author is **"Block"** —, published on **August 18, 2026**, ~930 words, announcing **the open-sourcing of Berd**, Block's internal desktop application for working with agents, and laying out the design thesis that guided it: giving agents character *"not only through roles, instructions, skills, and tools, but through distinctive visual identities"* — hence the in-house animated characters, the *"Gloopies"*. The post starts from an observation of fragmentation (*"The technology was powerful, but the experience around it was fragmented"*) and a precisely named interface problem: *"the product gives people little sense of how the agent is configured, which context and tools are available to it, and how it differs from another agent"*. Two structuring contributions. **(A) A three-tier articulation**: **goose** remains the framework and *runtime* that holds the agent loop; **Berd** is the desktop client (projects, context, sessions, agents, configuration); the two communicate via the **Agent Client Protocol**. **Buzz** is designated as the follow-up, for when solo work becomes collaborative (*"Start alone, then go multiplayer"*). **(B) Six requirements handed off to Buzz**, stated as a takeaway: *"private space, durable context, recognizable agent identities, reusable skills, visible configuration, and clearer visibility into an agent's configured context, tools, and capabilities"* — a grid directly reusable for evaluating an agent client. The text itself distinguishes identity from capability: *"The avatars make the agent recognizable. Its role, skills, and tools make it useful."* No usage figures are produced and no license is named for the open-sourcing.
#Berd#Block#open source
**Aucun auteur nommé** : le billet est signé **« Block »** — le champ *Author* de la page porte le nom de l'entreprise. Publié le **18 août 2026** sur `block.xyz/inside` · le blog **corporate** · et non sur `engineering.block.xyz`.
Blog post from **Sonatype** by **Aaron Linskens** (*technical writer*), published on **August 18, 2026**, ~1,300 words: it recounts a **Sonatype Research Labs** study spanning **49 months** (June 2022 — June 2026) and a **fixed cohort** of enterprise applications, a methodological choice asserted to isolate the evolution of the application fleet rather than that of the customer portfolio. The result is presented as a contradiction: remediation is faster, yet risk accumulates further. (A) **The stock is rising** — *Critical* and *High* vulnerabilities per application **×4.31** (from **14.14** in June 2022 to **54.3** in 2026, still **×3.91** excluding legacy applications newly brought under management), newly affected component versions at **46×** the pre-AI rate, monthly application creation **×4.84**. (B) **Remediation is improving** — more than half of resolved violations are resolved in under a day, the median age of unresolved *Critical/High* vulnerabilities drops from **228** to **126 days**, then to **103** in May 2026; among cohorts that had twelve months, **52.6%** are resolved, **44.3%** open, **3.1%** under waiver. (C) **The proposed lever is component selection**: at the moment a vulnerable dependency was chosen, a substantially less risky version already existed in **62.2%** of cases on **Maven**, **46.9%** on **npm**, **34.3%** on **PyPI** — a gap the text attributes to an information gap rather than developer fault. The post itself states that AI is not the sole cause of the acceleration, and concludes on **Sonatype Guide**, which brings this intelligence to the point of selection. On the supply-chain side, it extends what [[fiches/2026-08/staples-gitlab-when-code-is-abundant-2026-08-24]] frames in economic terms and [[fiches/2026-07/clinton-anthropic-secure-ai-native-sdlc-2026-07-21]] in secure-cycle terms.
#software supply chain#software supply chain#Sonatype Research Labs
Aaron Linskens · *technical writer* chez Sonatype · sur le blog de l'éditeur ; les chiffres sont produits par Sonatype Research Labs · non par l'auteur.
Product announcement post from **Block Engineering** signed by **Thomas Petersen** (*Principal Designer & Builder*), published on **August 18, 2026**, ~1,800 words across thirteen short sections, introducing **Buzz Projects** — a **software forge hosted on its own relay**: Git repositories, branches, pull requests, issues, review and merge, multi-repo projects, an activity feed, all linked to conversation channels. The post's standfirst and thesis: *« Coding agents are the terminal for your computer. Buzz is the terminal for your network. »* Three contributions. **(A) A trust doctrine grounded in *ex post* proof rather than *ex ante* authorization**: on one side *« No forced guardrails, no limitations on what your agents are allowed to help you with »*, on the other *« Every push, review, approval, and merge is a signed Nostr event. If an agent authors a patch, you can see which agent produced it and which human authorized that agent to act »*; the section closes on a stated direction — *« we are already exploring ideas around agent trust protocols informed by past behavior »*. **(B) Git interoperability without proprietary tooling**: *« These are standard git repositories… You can fetch, clone, pull, and push over plain Smart HTTP, with no custom tooling or wrapper CLI required »*, with the clé Nostr serving as a single identity — *« The same npub that signs your messages signs your pushes. »* **(C) A distinction between execution surface and network presence**: *« A terminal gives an agent somewhere to execute commands and change files, but it does not give it a persistent place in the network. Buzz does. »* The post produces no figures and contains no outbound links; it qualifies itself as preliminary six times (*« still very basic »*, *« fairly elementary »*, *« still under experiments »*), and Projects lives under the **Experiments** tab of Buzz Desktop.
#Buzz#Buzz Projects#Block
**Thomas Petersen** — *« Principal Designer & Builder »* chez **Block** · auteur unique et signataire du billet ; première apparition dans le corpus. Publié le **18 août 2026** sur le blog **Block Engineering**. Troisième signature Block sur Buzz en un mois · après Tyler Longwell (21 juillet) et Atish Patel (6 août) · et la première non-ingénieur.
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).
Announcement post published on the **official Z.ai blog** (formerly Zhipu AI, Chinese lab) on **August 14, 2026**, **with no individual byline**, ~2,000 words plus footnotes. It announces **GLM-5.3**, successor to GLM-5.2, opening with a methodological thesis: *« Scaling post-training is all we did for GLM-5.3. »* Same base model as GLM-5.2 — *« every gain comes from post-training »*. Three announcements. **(A) An open-weights coding model**: +50% claimed on **Z.ai Code Bench**, an unpublished in-house benchmark. **(B) A cyber capability presented as "emergent"**, which the body of the text traces to a training choice — *« As part of post-training, we introduced vulnerability discovery data and environments into the training mix. We expected this to make the model better at finding and reasoning about vulnerabilities »* — what came as a surprise was the speed and the change in nature: the model moves from identifying isolated flaws to *« coherent plans for complete exploitation chains »*. Gains grow with position in the exploitation chain: CyberGym 77.2 → **84.5%**, ExploitBench 24.4 → **54.4%** (×2.2), ExploitGym 29 → **105** tasks in 2h (×3.6), with the gap to the closed frontier remaining wide (181 and 247 tasks). Z.ai puts it this way: *« Capability is growing fastest exactly where we are furthest behind. »* The post also publishes a **Z.ai Security Disclosure Ledger**: **2,436 vulnerabilities identified across 269 open source projects** — kernels, OSes, browser engines, infrastructure, web applications, network protocols — the oldest introduced in **1981**, average lifetime before discovery **26.6 years**, of which **53 disclosed** and **2,383 under embargo**. **(C) A weight release** *« within two weeks of launch, once safety evaluation and hardening are complete »*. The most reusable methodological contribution: **environment and verifier synthesis**, the latter produced without access to the reference solution and admitted only after a triptych of negative controls — **oracle**, **no-op**, **unsolved-state**. All agentic evaluations are conducted **in Claude Code 2.1.207**.
#GLM-5.3#GLM-5.2#Z.ai
**Z.ai** (anciennement **Zhipu AI**) · laboratoire d'IA chinois · éditeur de la famille **GLM**. Billet **institutionnel et non signé** : aucun auteur nommé · aucun chercheur mis en avant · aucun lien vers un rapport technique ou une carte de modèle. Publié le **14 août 2026**. La page est une SPA React — le HTML servi est un `<div id="root">` vide · et le texte comme les scores ont dû être extraits du bundle `glm-5.3-BCnx8T5_.js` · où ils figurent en valeurs source.
Official product page from **DeepSeek**, published on **August 13, 2026**, **unsigned**, ~450 words, announcing the *developer preview* release of **DeepSeek Harness** (`dsh`) — a coding-agent harness **open source under the MIT license**, whose repository opened the same day. A three-word thesis, repeated in the title and in the repository description: *« Everything is a plugin »*, paired with a second promise, *« Every run is traceable »*. The page states the equation *« AGENT = MODEL + HARNESS »* and lists the pluggable capabilities — *« models, tools, skills, sessions, sandboxes, storage, loops, scheduling, and the UI »*. Four modes ship: **Standard** (full coding agent), **Code** (tools exposed via the *Code Mode SDK*, letting the model compose multi-step operations inside a TypeScript program), **Minimal** (*« two-tool coding agent with persistent bash and str_replace_editor »*, explicitly *« for benchmarking models in a minimal environment »*), and **Creator** (runtime inspection, in-memory plugin testing). The technical substance sits in the repository, not on the page: `docs/architecture.md` states a logging invariant — *« Model-visible means logged. Anything that reaches a model request must be reconstructable from the log, and a runtime invariant asserts it »* — and states that *« there is no privileged core to patch »*. The technical core is not DeepSeek's own: DSH is built on **Cordis** (the `cordiverse` project, a third party), **vendored** into `vendor/` with a manifest and a sync procedure, and the page places the *« Cordis paper »* at the same navigation level as "GitHub" and "Developer docs". Two LLM adapters ship — `dsh-llm-deepseek` and `dsh-llm-pi-ai`, a generic multi-provider adapter. The repository warns in capitals: *« THERE WILL BE COMPATIBILITY-BREAKING CHANGES »*, and `CLAUDE.md` specifies that `SESSION_FORMAT_VERSION` stays at `0` *« with no compatibility promise »*, with backends rejecting old on-disk formats. Timeline: DSH ships on the day **DeepSeek-V4-Pro reaches GA**, three days before a new API pricing schedule takes effect on **August 16, 2026 at 16:00 UTC**, with peak/off-peak rates and an off-peak discount of **−50%**.
#DeepSeek Harness#dsh#agent harness
**DeepSeek** (DeepSeek AI, laboratoire chinois) · en tant qu'institution. Page produit **non signée** : aucun auteur · aucun ingénieur mis en avant · aucun billet de blog ni papier technique associé. Le « nous » n'apparaît qu'une fois · en dernière phrase — *« We look forward to exploring the limits of intelligence with developers worldwide »*. Publiée le **13 août 2026**. La page est rendue en JavaScript : `curl` sur l'URL renvoie **HTTP 202 avec un corps vide** · le texte n'existant qu'après exécution du bundle. Deux documents de politique sont liés en pied de page — *Safe Use Policy* et *Data Processing Statement*.