platform-org-design-advisor

Designs platform engineering team structures, staffing plans, and operating models using industry benchmarks.

Updated Jul 16, 2026
One-click install
npx skills add https://github.com/Cloud-Byte-Consulting/plugins --skill platform-org-design-advisor-cloud-byte-consulting
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: platform-org-design-advisor
Source: https://github.com/Cloud-Byte-Consulting/plugins/tree/main/platform-assessment/skills/platform-org-design-advisor
Command: npx skills add https://github.com/Cloud-Byte-Consulting/plugins --skill platform-org-design-advisor-cloud-byte-consulting

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Engineering leaders lack grounded guidance when deciding how to structure, size, staff, fund, and govern platform engineering teams — especially as AI agents change who the platform serves. This Skill provides benchmark-grounded org design advice covering reporting lines, budgets, role coverage, and AI-era operating models. ## Core Features & Use Cases - Benchmark-grounded org scans: Compares your reporting line, budget band, team size, adoption model, and AI ownership against 2025 industry survey distributions. - Seven-role staffing model: Maps the canonical platform roles (HOPE, PPM, IPE, DPE, SPE, OPE, AI platform engineer) to concrete triggers for when each becomes a dedicated hire. - Autonomy-level progression design: Aligns team shape with agent autonomy levels L0–L4, including review structures, dispatch ownership, and an evidence-based trust ladder for agents. - Use Case: A VP of Engineering with 200 developers asks whether to create a dedicated platform team and who it should report to; the Skill runs an org scan, cross-checks maturity, and delivers a target org sketch with two costed alternatives. ## Quick Start Use the platform-org-design-advisor skill to assess our platform team structure and recommend a target org design with staffing sequence.

Frequently Asked Questions about platform-org-design-advisor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I decide when to create a dedicated platform engineering team?

The practitioner inflection point is roughly 100–150 developers, earlier for weak engineering cultures. Below ~50 developers, lay foundations without a standing team; use 10–20% of engineering capacity as the sizing heuristic once past the threshold.

Who should the platform engineering team report to?

A dedicated Head of Platform Engineering is the most common pattern at 32.9% of orgs, followed by VP Engineering at 21.1% and CTO at 14.6%. Reporting into Infra/Ops correlates with ticket-ops relapse, and any line more than two hops from a technology executive is a flag.

Should AI platform ownership sit in the platform team or a dedicated AI team?

Default to platform-team ownership with named interfaces to data science, matching the 36.7% industry pattern. Escalate to a dedicated AI-platform team only at scale, such as multiple GPU-backed products, to avoid recreating the DevOps-silo mistake.

How does team structure change as AI agent autonomy increases?

Human roles progress from Executor to Validator to Orchestrator to Constraint-setter across levels L0–L4. Each shift moves functions from doing to verifying to designing verification, requiring staffed review capacity at L2, dispatch ownership and eval engineering at L3, and governance-as-product at L4.

What are the limitations of the benchmark figures used for org design?

Benchmarks derive from 2025 industry surveys of roughly 500 and 240 respondents and are directional priors, not targets. Findings based on partial connector visibility or self-reported maturity are marked low-confidence rather than presented as certain.