This post was originally published on LinkedIn.

I still think most people are missing the point with AI.

Fancy Claude Code setups, "agents" (but not really), doing things the most complicated way when Claude Chat would have worked fine.

Too much talk of the repo architecture, the prompting, the download my 125 skill .md files, the "I have the mega complicated OpenClaw setup that sends me an email every morning with the news" (could have easily just been a scheduled task in Claude chat).

Not enough practical use cases and GTM capabilities and how they should evolve with the AI tools we have now.

And not enough on how to get from Level 1 (thought partner) to Level 3 (production-ready AI automation) or Level 4 (Autonomous AI Agents). Where the real business value is unlocked.

And I think that is because most operators and companies are stuck at L1 and L2.

L1/2 is great and can save a lot of time but L3/4 is where the promise of AI lives.

But it's way harder to get there vs. what you may hear on Linkedin.

This is why we keep on iterating on our maturity framework and how each GTM capability can move from L1 to 3/4. It helps demystify what each level means and gives us a roadmap to get unstuck from L1/2.

We just added a break down of the levels by:

• autonomy
• tool access
• objective
• context layer
• human role

Check it out and let me know what you think.

I'll also share a link to an example of one of the capabilities in the comments. Will keep sharing more as we build them out.