Why Doesn’t AI do the right thing with Variables?

Why your AI says the right thing — but doesn’t do the right thing

One of the most frustrating realities of enterprise AI is that while models like ChatGPT or Claude are excellent at talking, they’re far less reliable at doing. Specifically, passing variables — like a user’s name, a date, an ID, or a workflow command — from an AI response into your application often breaks in unexpected ways.

Why? Because LLMs don’t know your business logic. They aren’t structured programs — they’re prediction engines that guess the next most likely words. That means even when they generate the correct-sounding answer, those answers are not reliably parseable, consistent, or machine-actionable unless heavily engineered.

For example, an AI might respond with:

“Sure, I’ll schedule your meeting with Sarah at 10am Tuesday.”

But under the hood, it failed to provide a usable datetime object or reference a valid user ID. So your app has no clue what to do next.

This becomes a major issue in use cases like form submission, CRM updates, task creation, or any workflow where structured data must be extracted and executed. A chatbot might say the right thing, but unless it outputs clean variables in a predictable format — and your app knows how to interpret them — nothing happens.

How to Solve It

There are a few solutions emerging. OpenAI’s function calling or Anthropic’s tool use allow developers to define the structure of expected variables. With these tools, you can tell the AI: “Only respond using this schema” — which makes the response reliably parseable by your system.

Here’s an example JSON output from function calling:

To get there, you need to:

1. Define your app’s expected function schemas
2. Use models that support structured outputs (e.g., GPT-4 with function calling)
3. Test and handle fallback cases when AI guesses incorrectly

Enterprise AI doesn’t just need to talk — it needs to act. Getting variables right is the difference between a smart-sounding bot and a truly integrated, outcome-driven system.

If you’re ready to move from potential to production, AndMine can help engineer these logic layers so your AI doesn’t just respond — it gets things done.