𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗧𝗵𝗮𝘁 𝗗𝗼𝗻'𝘁 𝗛𝗮𝗹𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗲

If you build with LLMs, you face the same wall. The model invents a function or calls the wrong tool.

Function calling should fix this. Instead, it often makes your agent confidently wrong at scale.

To fix this, you need better architecture, not bigger models.

Use these four patterns to build reliable agents:

  1. Use a two-stage router Never pass all tools to the model at once. This causes schema bloat.
  • Use a fast, cheap model to classify intent first.
  • Only expose the tools that match that intent.
  • This reduces wrong-tool errors by up to 70%.
  1. Enforce structured outputs Stop asking models to return valid JSON via prompts.
  • Use schemas enforced at the API level.
  • Use tools like Pydantic to guarantee the format.
  • Constraints reduce hallucinations more than prompt engineering.
  1. Add validation layers Every tool call needs three layers: User Input, Pre-validation, and Post-validation.
  • Validate the model output against your schema before execution.
  • If validation fails, send the error back to the model.
  • Models fix their own parameter errors 80% of the time when they receive error feedback.
  1. Set hard limits Infinite loops destroy your budget. The model might call tools in a loop until it hits a timeout.
  • Always set a maximum iteration count.
  • Always set a maximum token limit per call.
  • Hard limits are a requirement for production.

Smart orchestration saves money too. Use different models for different tasks:

  • Small models for intent routing and output formatting.
  • Mid-tier models for tool selection.
  • Frontier models for complex planning.

This approach cuts costs by 10x to 15x without losing quality.

Track these three metrics to ensure stability:

  • Tool Selection Accuracy: Did it call the right tool?
  • Parameter Validity Rate: Did the parameters pass your schema?
  • Task Completion Rate: Did it actually solve the problem?

Reliable AI is about system design. Build constraints, validation, and guardrails.

What patterns do you use to build reliable agents? Share your thoughts below.

Source: https://dev.to/aiwave/building-ai-agents-that-dont-hallucinate-a-practical-guide-to-function-calling-in-2026-3dde

Optional learning community: https://t.me/GyaanSetuAi