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Yield Estimator cover
Yield Estimator — Studio Edition cover

Yield Estimator

Stop guessing the ROI of your AI agent deployment. This interactive HTML tool allows teams to estimate the 'Net Yield'…

Who this is for: teams shipping AI agents to production — founders, platform engineers, and anyone whose agents touch money, data, or external systems.

  • Complete, zero-placeholder document
  • Ready to adopt as-is
  • Grounded in production agent-governance practice

$49 Prices in USD

One-time · Instant PDF download via Gumroad · All sales final — no refunds.

Updated October 2026

Get it now — $49

Secure checkout via Gumroad · Sold by ghostcorpnet · buyer protection · Single-user license · Instant delivery

Lifetime access — yours forever in your Gumroad library

License TL;DR · full terms

  • Use it in your own products and client work
  • Single-user license — one buyer, unlimited personal use
  • No reselling or redistribution as-is

Not ready? Get the free MIT playbook first.

MD · 11 KB

$49 one-time, USD Instant download via Gumroad 3 sections inside

What it does

Stop guessing the ROI of your AI agent deployment. This interactive HTML tool allows teams to estimate the 'Net Yield' of AI agents by subtracting the essential costs of governance—policy gates, audit trails, human-in-the-loop oversight, and incident response—from projected productivity gains. Move from raw LLM output to a governed, production-ready forecast.

What's inside

  • Complete, zero-placeholder document
  • Ready to adopt as-is
  • Grounded in production agent-governance practice

How it works

How do I receive it?

Checkout is handled by Gumroad. The PDF is available for instant download the moment you pay — no account setup on our side, no waiting.

Is it really ready to use?

Yes. Every ghostcorpnet product is written with zero placeholders — adopt it as-is, no "insert your policy here" gaps.

Who is it for?

Teams shipping AI agents to production — founders, platform engineers, and anyone whose agents touch money, data, or external systems.

Pairs well with

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