ππ₯π’π ππ’π§ ππ¦ ππ ππππ‘π!!!! ... ok not really... What happens when y
By Ken Β· November 4, 2026 Β· Curated by George's Blog
ππ₯π’π ππ’π§ ππ¦ ππ ππππ‘π!!!!
... ok not really...
What happens when your CEO tries a new AI tool for a week and it catches things your team missed?
You get humbled. Then you get curious.
Last week Steven Pope installed Grok Bot as a founder-operator.
It was highly effective:
β It flagged things the team walked right past
β It surfaced business logic I hadn't built into our own automations
β It added QA checklist items I hadn't thought of
β It pulled data, made decisions and ranked priorities without much hand-holding
For a founder-operator, that's exactly the job.
Then I tried scaling it to a team of 400.
That's where things got complicated.
Here's what we ran into with shared bots:
β Fragmented knowledge. Chats are private. What one employee teaches their bot doesn't reliably become organizational knowledge. Team memory is hit or miss.
β Workflow ownership. Routines belong to their creators. Despite testing different configurations, we couldn't reliably get teammates to access or execute shared routines.
β Limited collaboration. Bots couldn't pass files directly between each other, and shared bots behaved more like individual copies than a truly collaborative system.
Great personal assistant. Not quite enterprise infrastructure.
And that's exactly why I approached our AI ecosystem at My Amazon Guy differently.
I didn't start with prompts. I started with our SOPs.
β 3,000+ pages of SOPs indexed in a vector database, accessible to agents through MCP
β Persistent memory so agents don't start from scratch
β Task-specific sub-agents that can be deployed as needed
β Validation and QA checkpoints before outputs are trusted
β Feedback loops that turn new learnings into shared organizational knowledge
The goal isn't to create 400 smart assistants working independently.
It's to create an infrastructure where 400 assistants can operate from the same institutional knowledge.
I'm now experimenting with a similar approach inside Grok Bot: a shared resource agent connected to our enterprise data sources.
Instead of every employee connecting, configuring, and maintaining their own integrations, their personal agents would call on a common resource.
Everybody can build their own workflows. But everybody works from the same source of truth.
That's the distinction.
Grok Bot is impressive for solopreneurs, founders, and smaller teams. But based on what we've tested, its collaboration model still has a long way to go before I'd consider it scalable for an organization our size.
The assistants can stay personal.
The knowledge shouldn't.
Oh, and whatever happened to Clawdbot? π