Insights

Practical writing on AI operations for digital businesses.

For the operators running them and the buyers acquiring them. No fluff, no invented case studies, written by Troy Johnston from operating his own software company on 130+ AI systems and evaluating ~50 companies as an M&A advisor.

For Acquirers

Teardown: a $70K ARR SaaS asking $15,000, and what I would verify before LOI

Public Listing Teardowns #1: a real Flippa listing read with public information only. What checks out, the $40K gap the arithmetic exposes, and why a 0.1x multiple is the loudest data point on the page.

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For Operators

The new Amazon reimbursement math, explained

Manufacturing-cost payouts and 60-day windows changed the recovery game. Why 25%-commission services are running the old playbook, and what a documentation-speed system looks like.

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For Operators

Auditing your automation against Amazon's AI agent policy

SP-API only, agent self-identification, human-in-the-loop. What 2024-25 duct-tape automation fails, and a five-step self-audit to run before Amazon runs it for you.

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For Operators

Why almost nobody knows their per-SKU profit (and how to fix it)

40+ fee types, late-arriving adjustments, and spreadsheets that die in a quarter. The five parts of a profit system that updates itself.

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For Acquirers

A pre-LOI red-flag checklist for digital business deals

18 checks across revenue plausibility, traffic authenticity, platform risk, owner dependence, and add-backs. Most bad deals fail one of these in the first week.

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For Acquirers

What $5,900 of digital deal diligence actually covers

Full scope transparency: source-system verification, MRR and churn reconstruction, traffic and code review, the AI Ops Underwrite, and the honest answer on when you need a $20-40K CPA QoE instead.

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