Adelaida Diaz-Roa
Every meeting, decision, and note feeds into one brain that compounds. Nothing gets lost, nothing gets repeated, nothing stays trapped in your head.
I built this because I was drowning in my own company. Two countries, scattered docs, decisions I couldn't find three months later. Now the system remembers so I don't have to.
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Three ways to work together
Every engagement starts with the same 2-hour deep dive. If we don't find at least 10 hours a month to give you back, you walk.
02 · Sprint
$10,000 · founding rate · post-founding $15,000
A 2-4 week sprint to find and build your highest-ROI AI workflows.
Full operations audit: where your time goes, what's manual, what's broken. I identify the top 3-5 automation points and build each one end-to-end. Working systems, not a recommendation deck. Includes the Brain Setup if you don't have it yet. Handoff documentation so your team can maintain everything. Two weeks of post-sprint support.
If after the deep-dive you don't see 10+ hours a month coming back to you, you pay nothing.
3 founding-rate spots remaining.
01 · Setup
$3,500 · founding rate
Your personal AI operating system, installed and customized in one week.
2-hour deep-dive interview mapping your workflows, decisions, and knowledge architecture. Full system build: Claude Code + Obsidian vault with custom skills, knowledge graphs, MCP integrations. One week of hands-on training.
Same guarantee. 10+ hours back, or nothing.
Post-founding: $5,000
03 · Ongoing
$4,000/month · founding rate
Ongoing AI strategy, optimization, and team training. 4-8 hours a month.
Continuous optimization of your AI brain. New tool evaluation as the landscape shifts. Monthly team trainings. Slack and async access. Monthly ROI report: what we built, what it saved.
3-month minimum, month-to-month after.
Post-founding: $5,000/mo · 3 retainer spots at this price
I'm taking 5 founding clients at these rates while I build public case studies. Once those spots fill, prices go up. No extensions.
The system is real
I didn't write a thesis about AI workflows. I ran two companies through them for eight months, then shipped the core on GitHub for anyone to use.
My own before and after
Before this system, I was running two companies across two countries with sticky notes, scattered docs, and the hope I'd remember the important thing from Tuesday's call. Meeting notes disappeared. March decisions contradicted January ones because I couldn't find them. I was the bottleneck in my own company and didn't realize it.
After six months, every meeting auto-processes into my knowledge graph. My AI advisory panel pulls context from 9,000 nodes before I make a decision. Pattern recognition flags when I'm repeating a mistake. Journal entries from three months ago surface when they're relevant to today's problem. I went from reactive to compounding.
The next five will be yours.
Zero risk
Two hours. I map your entire workflow and show you exactly where the system gives you time back. If you don't see at least 10 hours a month coming back to you, you pay nothing. I keep the notes, you keep the clarity, and we part as friends.