Reference page published on **eventuallycoding.com** on **July 28, 2026** by **Hugo Lassiège** (Lyon, developer turned entrepreneur, author of Bloggrify, Hakanai, and Writizzy). The author announces it as such: *"This will be more of a reference page than an article,"* intended for his own resources page. **Subject**: an exhaustive, tooled description of a **solo software factory** where *"the code produced is now nearly 100% generated,"* across several polyglot monorepos (Nuxt, Kotlin, JS — Hakanai, Writizzy, Bloggrify) in **continuous deployment to production**. **Distinction stated upfront**: this is not **vibe coding** in Karpathy's sense (experimentation, letting oneself be carried along) but **context engineering** — *"giving all the necessary context, at the right time, so that the software matches an intention and is systematically controlled,"* with the sentence that grounds the responsibility: *"Even if I don't write the code, I am responsible for it and must keep control over it."* **The entire toolset answers three questions**, and this is the text's most reusable reading grid: *"What does the agent know?"* (context, memory, code graph) — *"What does it know how to do deterministically, without improvising?"* (skills, procedures) — *"What stops it when it gets it wrong?"* (hooks, architecture tests, quality gates). **Six layers detailed**: (1) **context** — root `CLAUDE.md` + topical `.claude/rules/*.md` conditionally loaded via `paths:` + `.agents/*.md` for non-technical matters (personas, positioning, tone); (2) **skills** — about thirty, existence criterion *"if I explain the same thing a third time"*; (3) **tools** — JetBrains IDE MCP, **GitNexus** (code graph: `impact(symbol)`, `detect_changes()`), Claude-mem, RTK filtering wrapper, Sentry, read-only database; (4) **executable guardrails** — harness hooks, **architecture tests**, pattern linting (**ast-grep** for architecture decisions, not just ESLint); (5) **factory** — blocking quality gate with `needs:` on the quality job, five test stages; (6) **product process** — numbered specs with a drafting skill **and a closure skill**, design in Claude Design, staged delivery behind feature flags, distinction between **feature flipping** (Unleash) and **gating** (customer contract). **The rule that sums it all up**: *"What matters must be executable. An instruction is followed 'most of the time'… A hook or a test is followed all the time."* **A rarity for the genre**: a "To improve" section that exposes four lived limitations — the **impossibility of measuring a rule's obsolescence** (*"I have no way of knowing whether an old rule has become obsolete"*), the **rabbit hole** created by a boyscout rule, the **lack of packaging** for skills across projects, and above all the admission of tension: *"I am becoming less and less useful during implementation phases,"* *"torn between the satisfaction of having an increasingly efficient factory and the risk of losing knowledge."*
#software factory#context engineering#vibe coding
**Hugo Lassiège** — développeur devenu entrepreneur · basé à **Lyon** · écrit du code depuis 2001 et tient **eventuallycoding.com** (le blog a porté le nom `hakanai.free.fr` avant de devenir *Eventuallycoding* en 2013). *Eventuallycoding* est le nom-parapluie qui regroupe ses projets · sa chaîne YouTube et ses blogs.
Guide from the media outlet **Every** (every.to/guides) published on **June 2, 2026**, co-signed by **Mike Taylor, Laura Entis and Claude**, proposing an **8-level maturity scale for AI adoption**. **Pivot thesis**: AI adoption **is not a race toward maximum sophistication** — ***« a higher level isn't necessarily better »*** ; one must identify the level that **matches one's own workflow and level of trust**, then regularly reassess whether moving up a notch adds **real value**. ***« The best way to find value in AI is to use it in a way that fits your work. »*** **Structuring axis**: at each level, *« you delegate more of your work to—and place more trust in—the AI »* (increasing delegation + trust). **The 8 levels**: **(1) Chatbot** — conversational interface with no embedded context (ChatGPT, Claude, Gemini); **(2) Copilot** — AI embedded in the workspace with access to the current file (Cursor, Claude in Excel, Gemini in Docs); **(3) Agent** — reactive system that executes step-by-step while requesting approval (Cowork, Codex); **(4) Autopilot** — one describes the **outcome** and the agent executes autonomously, review of the **final result** only (Lovable, Codex, Claude Code; tied to *vibe coding*); **(5) Workflows** — engineers building **harnesses** around agents (planning, review, confidence checks, guardrails; Compound engineering, Claude Workflows, Copilot AI Studio; shift from one-shot vibe coding → **agentic engineering**); **(6) Assistant** — **proactive, always-on** agents that monitor a domain and surface information without being prompted (OpenClaw, Hermes Agent, Claude Managed Agents; e.g. `heartbeat.md` every 30 minutes); **(7) Multi-agent** — simultaneous management of **several long-running agents** with distinct roles (Claude Managed Agents, OpenClaw, Codex Goals; *« firmly in senior engineering territory »*); **(8) Orchestrator** — an **agent manager** directs a team of sub-agents (planning, delegation, monitoring, consolidation; Gas Town, Paperclip, Symphony/OpenAI; *« highly experimental »* — even frontier engineers themselves hold this role). **Sweet spots by role**: **knowledge workers** typically operate between levels **1-4**, **engineers** between **5-8**. **Canonical parallel of intern onboarding**: *« Expect to put in a similar amount of effort with your agents before you can trust them… at the next level of autonomy »* ; and the marker phrase ***« You wouldn't brag that you had eight interns working overnight on a key project, and you hadn't checked their output. »*** The right level depends on **4 criteria**: output quality, cost, reliability (trustworthiness), stakes of failure; and **model capability** progressively shifts the "safe" level of autonomy. A framework directly usable to structure an **adoption doctrine** on the consulting side. Convergence with *systems around the model* (Dropbox/Okumura), *harness engineering* (Böckeler, Lattice, Wescale), Karpathy (vibe coding → agentic engineering), Cherny (/loop + Routines), and the *agent manager* doctrine (BFM/Girard).
#AI adoption#maturity scale#eight levels
**Mike Taylor** · **Laura Entis** et **Claude** (co-auteurs déclarés) · pour **Every** (every.to) · rubrique *Guides*. Mike Taylor est un auteur connu sur les sujets prompt/AI (co-auteur de *Prompt Engineering for Generative AI*) ; Laura Entis est journaliste/éditrice. La co-signature explicite de **Claude** comme auteur fait partie du positionnement éditorial d'Every (entreprise AI-native). Publié le **2 juin 2026**.