Essay by **Donn Felker** published on **September 14, 2026** on his Substack (~4,400 words, subtitle *"Your identity was built on a bottleneck"*). The author, AI platform lead at **Polygon** and formerly at **Tinder**, an Android specialist for over ten years, dates his shift to **July 2025** based on three facts: a SaaS built without writing a single line, a threading library migration at Tinder cut from **6-8 hours** to **10 minutes** by a **2,000-word** prompt, and non-technical people (a CFO, a gym manager) shipping complete products. **(A)** He draws from this a psychological framework — *occupational categorization*, *professional identity centrality* — to explain engineers' anxiety: *"It was never about coding, it's about the ability to execute"*. **(B)** He proposes an image of a **leverage pendulum** between product and engineering: AI shifts the initial leverage toward product, complexity and scale pull it back toward engineering, and each oscillation dampens as guardrails and architecture get codified. **(C)** He describes a hybrid role, the **agentic builder**, and a two-step path (codifying one's knowledge into skills, shifting from specialist thinking to systems thinking) with a stated horizon of **six months**. Extends the shift to *agentic engineering* described in [[karpathy-vibe-coding-agentic-engineering-software-3-0-2026-04-29]] and the collapse of boundaries between professions from [[sfeir-ia-frontieres-metiers-skill-based-organisation-2026-08-01]].
**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)
FinOps for AI agents centered on "cost per outcome": why traditional FinOps fails against runtime behavior, guardrails, behavioral observability, and a 4-phase lifecycle - Orq.ai