What a CRO Builds with Claude AI Today
A year ago I was paying €1,000/month for a developer. Today I build the same thing myself — in one hour.
Tom Adebahr
The Unconventional Path
- Noch vor einem Jahr habe ich 1.000€/Monat für einen Entwickler bezahlt — heute baue ich das selbst in einer Stunde.
- KI demokratisiert Fähigkeiten: CROs brauchen keinen Code, um operative Tools zu bauen.
- Der Wettbewerbsvorteil entsteht JETZT — wer wartet, verliert 12-18 Monate.
- A year ago I was paying €1,000/month for a developer — today I build the same thing myself in one hour.
- AI democratizes capabilities: CROs don't need code to build operational tools.
- The competitive advantage is forming NOW — wait and you lose 12-18 months.
- Claude AI + HubSpot = the operational AI stack for revenue leaders.
The New Reality for Revenue Leaders
Two years ago I wanted to build a simple app: a dashboard that shows my revenue data from HubSpot the way I need it. Not the way HubSpot prescribes. Cost: €1,000/month for a freelance developer. Result: three weeks of waiting, endless feedback loops, and in the end a tool that almost looked like what I had imagined.
Today I open Claude, describe what I need, and have it in one hour. No developer. No budget approval. No dependency. This isn't a small improvement — it's a paradigm shift.
The software market is moving faster than ever. Tools that were state-of-the-art 12 months ago are being replaced by AI-powered alternatives — often built by the users themselves. As a CRO, you're no longer the one buying software. You're the one building it.
5 Things I Build as a CRO with Claude
These aren't future visions. This is my daily workflow — today, every day, operationally.
The Operational AI Stack
No theoretical framework. This is the stack I use every day — and that allows me as a CRO to do things that previously required a whole team.
"The best tech stack is the one you can operate yourself."
Tom AdebahrWhy Most CROs Still Use AI Wrong
I talk to revenue leaders every week who "use AI". Most of them make three fundamental mistakes:
1. AI as a Toy Instead of an Operational Tool
Using ChatGPT for a few emails isn't AI adoption. That's playing around. Operational AI use means: automating processes that used to take hours. Building dashboards that previously required a BI team. Creating workflows that previously needed a developer.
2. No Clean Data Foundation
AI is only as good as the data it gets. If your CRM is a data dump, Claude will just deliver beautifully worded garbage. First build RevOps, then layer AI on top. The sequence matters.
3. Too Many Tools, Too Little Integration
Testing a new AI tool every week isn't a strategy. It's distraction. Five well-integrated tools beat fifty isolated ones. Your stack needs to work together — data must flow, automations must trigger, insights must be actionable. That's exactly why a thoughtful revenue architecture approach matters.
The Competitive Advantage Is Forming Now
In 18 months every CRO will use AI. That's not a prediction, it's inevitable. The question isn't whether, but when you start.
The advantage doesn't belong to those with the biggest budget or the best tech team. It belongs to those who start NOW and learn operationally. Those who build their first automation today, send their first AI-powered outreach, create their first dashboard with Claude — they'll have a lead in 18 months that's impossible to catch up.
It's not about perfection. It's about velocity. Your first automation flow won't be perfect. Your first Claude dashboard will have bugs. But you learn with every build. And every build makes you faster, more effective and more independent.
Do you want to be the CRO who has used AI operationally from the start in 18 months? Or the one who's just beginning to learn? The tools are here. The costs are minimal. The only resource you need is the willingness to start.