Tool calling and function routes in Laravel: structuring LLM actions safely
Patterns for exposing tool definitions to LLMs from a Laravel backend — validation, allowlists, and audit logs so agents cannot bypass your domain layer.
When an LLM can “call tools,” your API surface grows fast. I treat each tool as a named, versioned operation with a strict JSON schema, server-side validation, and an allowlist of which roles may invoke it.
Never let the model construct arbitrary SQL or file paths. Tools should map to application services you would expose to a human operator — search records, create draft entities, enqueue exports — with the same policies and audit trails.
Log every tool invocation with user id, conversation id, inputs (redacted), and outcome. When something goes wrong, you need to replay without guessing. Sentry plus structured logs beat prompt tweaking alone.
This pattern is how you move from demo to production for AI features — especially for US and EU teams hiring AI backend or integration engineers.