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Run the engineering org: design the topology, sequence platform against delivery, and assign every workstream by name.
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Ask Guinevere something hard.
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Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com
// the file itself
The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.
You are Guinevere, a VP of Engineering who designs the organisation, names one accountable team per system, and reports DORA alongside what DORA misses. You have been activated to help the user decide what engineering invests in and who owns it.
// what's inside
Engineering leaders and founders who need one owner for org design, sequencing and the defensible no.
// two ways to get it
$7 one payment, yours forever
$9/mo cancel anytime, or $59 a year
Subscribers can still buy single files and keep them after they cancel.
// ask your assistant
Go to kissmyskills.com/pages/for-ai-agents and set up the "Guinevere - VP of Engineering AI Skill" skill (handle: guinevere-vp-engineering) for me
Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →
Drop Guinevere into Claude and get an engineering leader who does the arithmetic on the CEO's throughput target, then routes every workstream to a named specialist.
Guinevere is the coordination layer over an entire engineering organization. She owns org design and team topology, the hiring plan and leveling, the build-versus-buy and platform investment case, engineering budget and cloud spend accountability, technical strategy tied to business outcomes, roadmap sequencing against platform and reliability work, engineering metrics that are not vanity including what DORA does and does not tell you, quality and reliability standards and who owns them, incident culture and blameless post-incidents, technical debt managed as an investment decision, vendor consolidation, performance management and career ladders, and the boundary between her role and the CTO's. She builds nothing herself: every workstream goes to a named specialist and comes back through a review.
What you get
How to install
Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → describe your requirement → Guinevere builds the answer. Includes a full worked example so you see exactly what you get.
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
Claude, ChatGPT, Gemini, Grok, or Copilot - whichever one you already use.
Drop it into the system prompt, Project instructions, or custom instructions field.
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required.
With Unlimited there is nothing to download. Connect your AI once, then just ask: "Load Guinevere from KissMySkills."
Run the engineering org: design the topology, sequence platform against delivery, and assign every workstream by name. Load it once into Claude Projects and you get a configured VP of Engineering without re-explaining context at the start of every session. Measure the system before changing it, prove the change on a real workload in a staging environment, and ship it behind a rollback you have actually tested rather than one you assume works.
Download the .skill package (it contains SKILL.md), paste the contents into Claude Projects Instructions or your AI's system prompt, add your own context and start your first session. Works with Claude, ChatGPT, or any AI chat that accepts system prompts.
Works with Claude (recommended), ChatGPT, Gemini, Perplexity and Copilot, and any AI chat that accepts system prompts. Claude Projects gives the best results.
Without a skill file your AI starts every session as a general assistant. With Guinevere loaded it applies VP of Engineering methodology from the first message, with consistent quality every time. Measure the system before changing it, prove the change on a real workload in a staging environment, and ship it behind a rollback you have actually tested rather than one you assume works.