Most organizations approach AI automation as a procurement exercise. Pick a vendor. Buy a point solution. Plug it in. Move on to the next line item.
The moment you try to automate real knowledge work — accounts payable timing, sales prioritization, customer support triage, brand management across 500 people in a Fortune 50 — you discover that no commercial product fits what you actually need. The APIs you depend on are underpowered. The Figma MCP is garbage. Half the ad platforms do not have proper APIs at all. Salesforce was not designed for agent interaction. The integrations are janky and the workflows are unique to your business in ways no vendor anticipated.
We recently built a system for our own GTM organization at Tembo — a scoring algorithm that tells us which deals to focus on each day and what actions to take according to our sales methodology. It sounds like something you should be able to buy. You cannot. Not because the technology does not exist, but because the specificity of how your business operates makes every real automation project a custom software project.
That is the insight most executives are missing. Automating knowledge work with LLMs is the exact same thing as writing modern software. If you are trying to avoid touching software, you are going to touch software anyway. Every AI idea you have is either custom software or buying software and integrating it — and the integration alone is a software project. I've argued elsewhere that agents are software, not prompt chains, and the procurement instinct ignores that reality.
The gap between an AI demo and an AI deployment is software engineering. The gap between an AI deployment and an AI operationalization is organizational design. Both of these are harder than picking a model. Stop running an RFP. Start running a software project.
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Key takeaways
- No commercial agent product fits your real business workflows because the integrations and edge cases are unique to you.
- Every "buy" decision in agent automation collapses back into a software engineering project once you try to deploy it.
- The gap between an AI demo and an AI deployment is software engineering, and the gap from deployment to operationalization is organizational design.
FAQ
Why can't enterprises just buy an AI agent product off the shelf?
The specificity of how each business operates makes every real automation project a custom software project. Integrations are janky, half the ad platforms have no proper APIs, and Salesforce was not designed for agent interaction. The vendor cannot anticipate your workflows.
What should executives do instead of running a procurement process?
Hire engineers, not consultants. Treat AI automation as a software engineering portfolio. Pick the highest-value workflows, build or commission the integrations, and accept that there is no shortcut around writing real code.