Long-form article published on **X** on **August 11, 2026** by **Jesse Zhang**, CEO of **Decagon** (customer-service AI agents), under a dilemma-shaped title — *« To FDE, or not to FDE? »* — devoted to the **Forward Deployed Engineer**, which has become *« the answer to almost every hard question in AI go-to-market »*. Starting observation: Anthropic and OpenAI have built enterprise deployment arms explicitly modeled on Palantir, *« every seed-stage company »* advertises an FDE offering, and job postings for the title are said to be up several hundred percent in a year. **(A) The Palantir genealogy** supplies the framework: **Shyam Sankar**'s (CTO) formula, *« FDEs eat pain and excrete product »*, and **Joe Lonsdale**'s reminder that Palantir spent nearly two decades being called a *« glorified consultancy »* on the basis of an accurate observation. **Gotham**'s bespoke deployments (CIA, NSA, military intelligence) were encoded into platform primitives — ontology, object models, permissions, workflow engines, provenance tracing — which became **Foundry**, then Apollo and AIP; standardization pushed gross margin into the 80% range and Palantir moved from an FDE motion to account-based selling, with many FDEs migrating into core engineering. *« The pain was the input to the product, not a cost of sale. »* **(B) The criterion proposed** is not to give up on FDEs but to know when to stop: go early, then ask whether one is still **discovering** — *« The trap is not starting. It's not stopping. »* **(C) A distinction few make: FDE ≠ implementation.** *« Building that integration into their ticketing system »* is real work, but it is execution against a known spec, not discovery of an unknown one; conflating the two *« is how a company convinces itself that a growing services org is a product investment »*. Closing line: *« If your FDEs are eating pain and excreting more pain, you don't have an FDE team. You have a services business. »* Two figures are put forward about Decagon — *« two-thirds of deployment work is now done autonomously via Duet »* and *« a few days on average to launch the first AOP, even for large banks, airlines, telcos »* — without the "deployment work" denominator being defined or the AOP acronym spelled out.
#Forward Deployed Engineer#FDE#engineer embedded with the client
**Jesse Zhang** — cofondateur et **CEO de Decagon** (agents IA de service client, San Francisco) · 85 000 abonnés sur X · site personnel `jessezhang.org`. Il cite son cofondateur **Ashwin Sreenivas** · **ex-Palantir** · d'où la profondeur du récit Palantir. Publié le **11 août 2026**.
Polemical essay-thread by Ahmad Osman (@TheAhmadOsman) on X, *"Anthropic's War on Opensource AI"* (1.7M views). Core thesis: Anthropic systematically converts "safety" into a **control mechanism** (permission regime, regulatory capture, anti-competitive access restrictions, behavioral opacity) to keep builders, startups, and open source communities **downstream** of a handful of frontier labs. Central anchor point: the **Fable incident** (silent degradation of competing AI dev requests). Advocacy for open source / local AI as the only viable "political economy of intelligence." Domain: AI policy, open source vs. closed labs, sovereignty, governance.
Op-ed by **Olivier Rafal** (Consulting Director Strategy at **WeNvision**) published on **February 23, 2024** on **CIO-Online** (*Tribune* section), advancing a thesis still counter-intuitive at the time: **generative AI is more a matter of technology product than an AI/data science project**. **Argument 1 — data science is not the core issue**: building a *foundation model* from scratch requires *« several months, millions of euros, and access to enormous quantities of data »* — reserved for players with specific, monetizable datasets (e.g. **Bloomberg** and its **BloombergGPT** for finance). For nearly all companies, the right reflex is therefore not to hire data scientists. **Argument 2 — skills mismatch**: what is mainly needed is **development and integration engineers** (back/front), **strong cloud skills**, and **DevOps**. Client quote: *« You don't necessarily need to be a data scientist, but you need to understand the basic concepts, have back-office development skills, and strong cloud skills. »* **Argument 3 — platform architecture (orchestrators + APIs)**: building an enterprise **plateforme d'IA générative** via orchestrators and APIs makes it *« possible to work with the best LLMs on the market and switch between them as their respective capabilities evolve, without reworking the applications »* (anti vendor lock-in). **Argument 4 — from project to product**: *« The platform […] must be regarded as a product in its own right »*; instead of a one-off investment, plan for a **monthly funding stream** (continuous iteration, ongoing innovation). **Argument 5 — governance & shadow AI**: the unprecedented democratization of GenAI generates *« as much shadow AI as strong expectations toward the CIO office »* → governance to capture business needs, **prioritize products by value**, and oversee proper operation. **Paradigm shift** announced: *« the shift is from classic algorithmic programming to agents Langchain that handle part of the decisions »*. **Relevance to the watch**: a **founding text (2 years ahead)** of WeNvision's doctrine (product > project, platform/API, flow-based funding, governance, shadow AI), later extended by [[wenvision-ai-agents-enterprise-deployment-2025-10-01]], [[habert-ia-agentique-production-2025-10-29]], and rafal-wenvision-tokenomics-foundation-finops-ia-2026-06-04 (FinOps/token, flow-based funding → financial governance). It also foreshadows the *harness/platform around the model* (Dropbox/Okumura: *systems around the model*) and **model independence** achieved through an orchestration layer.
#generative AI#technology product#product vs project
**Olivier Rafal** · *Consulting Director Strategy* chez **WeNvision** (cabinet de conseil FR). Tribune publiée dans la rubrique *Tribune* de **CIO-Online**. Auteur déjà présent dans la veille (cf. fiches WeNvision/Atlas/Tokenomics). Publié le **23 février 2024**.