Dharmesh Shah

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I’ve been thinking a lot about the "Gap of Implementation."

It’s that awkward space between when a new AI tool is released and when a business actually sees a dollar of ROI from it.

Right now, we are swimming in tools. Every morning there is a new model, a new wrapper, a new "game-changer." But for most teams, the gap is widening, not shrinking.

Here’s why: we are treating AI like a search engine when we should be treating it like a colleague.

When you hire a new person, you don't just give them a login and say "go." You give them context. You show them how you talk to customers, where the data lives, and what a "good" outcome looks like.

AI needs the same onboarding.

The win isn't in the prompt. The win is in the permissioned context you wrap around the prompt.

I’m seeing this play out in real-time as I build out new workflows this week. The agents that have access to my specific CRM data and past writing are 10x more useful than the "smartest" raw model on the market.

Context is the only moat left.

If you’re feeling overwhelmed by the pace of change, stop looking at the new models. Start looking at your own data. That’s where the value is hiding.

What’s one task you’ve tried to give AI that failed because it just didn't "know" enough about your business?

#AI #Building #Context #HubSpot #FutureOfWork

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