conversations across
146 PE-backed companies
Four constraints. That's the whole map.
Almost every business bottleneck reduces to one of four barriers. Click each letter.
Build. Buy. Borrow. Choose deliberately.
The right sequence is also the right time order. Click each path.
Use a horizontal LLM (Claude, GPT, Gemini) directly via chat or API. Zero infrastructure. Lowest cost to test. Every AI initiative should start here. If a borrowed model can't move the needle in two weeks of real use, the buy/build decision is premature.
Specialized tool for a specific job: Gong for calls, Harvey for legal, Cresta for support, EvenUp for claims. Faster to value than building. Captures vendor R&D spend. The trap: stacking too many vertical tools creates integration debt that erodes the savings.
Custom workflows, agents, or applications using your own data and judgment. Only justified when the capability is competitively defensible — meaning the data, workflow, or judgment is uniquely yours. Otherwise you're paying engineering costs to rebuild what's available off the shelf.
The constraint diagnostic. Output: a one-page brief.
A real bottleneck, six steps, a fundable brief. Hand it to your sponsor.
Be specific enough that a frontline operator could read it and recognize themselves in it.
Pick one, even if you see two. The dominant constraint determines the starting move.
Be specific in dollars, hours, deals, retention, NPS, or share. The CEO who can't size the prize won't get the budget.
No accountable owner = no real initiative.
Four failure modes we see every week.
If your AI initiative is stuck, it's almost certainly one of these. Hover or click any trap to see the tell.
Where this lives in the Playbook.
28 use cases across 10 functions. The constraint you named almost certainly lives in one of these.
The leaders who win this cycle won't have the most tools. They'll ask the better question.
Name and size it. Dimension it. Pilot it. Industrialize it. The tool was always the easy part.