VM or disk is lost
The original machine is treated as unavailable, not as the hidden source of truth.
DIGITAL PRODUCT · AI VM SETUP BLUEPRINT
This blueprint gives your AI agent a controlled workflow for setup, security and backups. It adapts each step to your environment, documents the results and can test complete recovery on a fresh VM.
1-hour VM setup observed in the SSH/S3 test · recovery tested on GCP and SSH/S3 · 12 months of updates
Your agent reports the result, not just the commands.
The agent can only report a full recovery pass when the optional rehearsal was selected and observed. Otherwise it reports the remaining gap.
FIND YOUR STARTING POINT
Three or four short questions show where the blueprint helps and whether the agent-led path fits the way you use AI. No infrastructure is touched and your answers stay in this browser.
RECOVERY IS A PATH, NOT A BACKUP ICON
Recovery-critical configuration, images and data live away from the VM. The agent follows the recorded path onto fresh infrastructure and proves the selected outcome.
The original machine is treated as unavailable, not as the hidden source of truth.
The blueprint gives the agent the order, guardrails and verification points.
Configuration, images and selected data are restored on a clean VM and checked.
ONE VM · TWO SEPARATE DOORS
Public and private workloads use separate ingress paths. Internal tools are reached through the private tunnel, not merely protected by another login screen.
No public route to internal applicationsA request arriving from the internet cannot cross into the private ingress path.
WHAT IS RUNNING AT THE END
Not a demo and not just generated commands. Every selected stage ends with observable acceptance criteria, and every gap remains visible.
Pinned supported image, restricted host access, firewall and a documented recovery path.
Human administration and internal routes use a private path rather than sharing the public application edge.
A small Kubernetes base with separated public/private routing, storage and verified TLS.
Scoped identities and secret references are separated from the sanitized configuration repository.
Protected off-VM material is decrypted, checked and restored in isolation.
Sanitized recovery configuration, evidence, status endpoints and operating instructions remain with you.
WHAT IS INSIDE
The agent adapts each stage to the environment you explicitly identify. These are not provider-specific commands copied blindly: every stage has an operator decision, observable proof and a recorded handover.
Establish the real target, experience level and required external services.
No hosted control plane and no installation of global skills. The package is a folder; the prompt is the entry point.
Read START-HERE.md and skills/vm-blueprint/SKILL.md. Start run ssh-s3-001 in discovery mode. Target is a new SSH VM with S3-compatible storage VM. Interview me about the business and workloads, then prepare the adapted plan. Do not provision resources yet. Record missing inputs and benchmark metadata.
AI VM SETUP BLUEPRINT · €119
Get the complete agent-executable blueprint, private repository access and 12 months of updates. One company may use it across unlimited internal and client VMs.
Come back Wednesday, 30 September at 13:00 CEST.PREFER A HAND?
Your AI performs the implementation. We review the architecture, help resolve important decisions and join you for the final acceptance and recovery session. Includes a kickoff, limited asynchronous support and a final evidence review; migration is separate.
You confirm immediate delivery at checkout and waive the 14-day withdrawal right, as required for digital content in the EU. If the package does not work as described, write to us and we solve it or refund.
Yes for a complete run. The agent reads the package, your answers and command output across twelve stages. Free tiers stop far earlier. You can buy now and run later.
The package uses the same explicit file-based entry point with Claude Code and Codex. The setup guide covers both. Other agents are not advertised until they have been validated.
The run records the failure, tries at most twice per hypothesis and then marks the stage blocked with a reason. You continue from the recorded state instead of starting over.
Through the private Git repository (git pull). Each release lists measured runs and what changed.
One company may use the Blueprint an unlimited number of times across its own VMs and environments and to provide services on client-owned or client-controlled environments. You may deliver generated customer-specific artifacts, but may not redistribute or resell the Blueprint itself.