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Transformation & Adoption Auto-verified translation

Steps of AI Adoption (tableau/artifact + post LinkedIn « I talk to engineers at other companies every day… »)

**Boris Cherny** (Creator & Head of Claude Code @Anthropic) publishes a framework table on LinkedIn, **« Steps of AI Adoption »**, mapping an engineering team's adoption of agentic AI across **5 stages (0→4)**, each characterized by an **order of magnitude of agents driven** and a **transformation of the engineer's role**: **0 Gated** (0 agents, locked-down access), **1 Assisted** (~1 agent — "you + one agent", supervised pair programming), **2 Parallel** (~10 agents — **orchestrator**), **3 Supervised autonomy** (~100 agents — **manager of managers**, an org tree), **4 AI-native** (~1,000+ agents — **VP steering by intent**). The table crosses five columns: number of agents, *what it looks like*, *the bottleneck*, *the products that help*, *the guardrails*. **Central thesis**: consuming more tokens does not move you up a level — advancing to the next stage requires **identifying and breaking the next bottleneck** AND **building the next set of guardrails**. Concretely: giving Claude a trustworthy **self-verification loop** (tests + build + lint + e2e on a real environment), enabling **Auto mode** (avoiding blocking permission prompts), making **code review and security review the default**, adopting multi-agent interfaces (Agent view CLI, Desktop, iOS/Android apps, Tag), then `/loop`, `/batch`, `/goal`, **dynamic workflows** and **worktree isolation** for subagents. On steering: usage (dashboard) measures **activity, not return**; the right question is *"would we have spent engineering effort on this anyway? if so, how many manual engineer-hours would it have cost?"* — that's the ROI. The real payoff arrives when **fixing and maintaining happens in the background** and teams focus on *building*. Anthropic sits at **stage 3, heading toward 4**; Boris Cherny states he has personally reached **level 4**.

#Boris Cherny#Claude Code#Anthropic

Boris Cherny (Creator & Head of Claude Code @Anthropic)

AI Coding Agents & Skills Auto-verified translation

Loop Engineering: The Guide for AI Agents

In-depth technical guide (Lushbinary agency blog) on **Loop Engineering**: designing the systems that drive coding agents in a loop, rather than prompting them manually. Covers the lineage prompt → context → loop engineering, the Ralph technique (Geoffrey Huntley), the **five building blocks + memory** of a loop, their implementation in Claude Code and OpenAI Codex, writing verifiable stop conditions, an adoption maturity scale, and the risks that worsen as loops grow more sophisticated. Domain: agentic software engineering, coding agents, harness/orchestration.

#Loop engineering#coding agents#harness engineering

Lushbinary Team