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Why APE·X?
In the Planet of the Apes reboot, the breakthrough is a serum. The apes don’t invent it — a lab does. One dose, and they rise.
AI is that serum today.
It’s sitting there, waiting. Any business can take it, including the ones you compete with.
Every workflow in this gallery is a dose: prepared, tested, and pointed at one business problem.
Your business does the rising — your business + AI, stronger together.
Apex — the top — is where the first movers end up.
About Me
One person runs this shop. Here’s how — and why that’s the point.
I took the dose in late 2022 — soon after ChatGPT launched — and I’ve worked with AI daily ever since. Ape-X is currently a one-person studio, and it runs on what it sells: I design the workflows, AI does the heavy lifting, and automated checks sit on every number before anything ships. Every demo in this gallery was built exactly that way.
That’s the pitch in miniature — this is what a business gets done when AI is pointed at it properly. Yours next.
Where the craft comes from
The demos show what I can build. These show the training behind it — tap any certificate to open it.
Applied Gen AI Cohort
100xEngineers · six-month build cohort · completed Sep 2025
AI for Business Leaders
Allie K. Miller, ex-Amazon & IBM AI leader · Maven · Jun 2024
Advanced ChatGPT for Finance
Nicolas Boucher & Christian Martinez · Maven · May 2024
Prompting for AI Operations
Certification · The AI Exchange · 2023
How I keep the AI honest
AI can ship remarkably fast. What makes it safe to rely on is the checking — standing rules from my build book, in plain English:
The AI never does the math. AI models are excellent writers but unreliable calculators. So in these workflows, ordinary computer code does every calculation, the AI is handed the finished figures with instructions to copy them exactly, and a second automated check verifies every figure against the source data before anything ships. If a check fails, nothing goes out.
Every fact must cite its source line. When the AI reads an email or a filing and pulls out a fact, it must also hand over the exact phrase it found the fact in — and code checks that the phrase really appears in the original, word for word. A fact that fails the check is thrown out and flagged for a human instead.
When the AI is unsure, it says so — and a human decides. “I’m not sure” is a valid, expected answer. Anything uncertain is never scored or silently filed: it lands in its own “needs a human look” section, with the reason stated, for a person to decide.
Want this pointed at your business?
Tell me what eats your team’s hours. I’ll tell you straight — whether a workflow fixes it, and how long it takes to build.
Chat on WhatsApp Or start free: take the Skeptical Reader playbook and run it yourself today.