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codingapihallucination

AI Hallucinates API Endpoints That Don't Exist

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Ask AI to help you integrate with an API and there's a solid chance it'll reference methods, parameters, or endpoints that are completely fabricated. It'll give you the exact URL, the request body, even sample responses — for an endpoint that was never built. Developers waste hours debugging 'why doesn't this work' before realizing the entire API call is a hallucination.

When AI Makes Up API Endpoints


The Problem

You're integrating with Stripe, Shopify, Twilio, or any popular API. You ask AI for help. It gives you a clean code snippet with a specific endpoint, headers, request body, and even a sample response. Looks legit. You implement it. It doesn't work.


You spend 30 minutes debugging your auth. Then 20 minutes checking your request format. Then you finally go to the actual API docs and discover: that endpoint doesn't exist. Never did. The AI made it up.


Why This Happens So Often

1. APIs change constantly. The AI's training data includes documentation from multiple API versions. It might give you a v1 endpoint when you're using v3.

2. Pattern matching, not understanding. If an API has /users/{id} and /orders/{id}, the AI might invent /invoices/{id} because it fits the pattern — even if that endpoint doesn't exist.

3. Multiple APIs get mixed. AI blends Stripe's patterns with PayPal's parameters and gives you a Frankenstein endpoint that belongs to neither.

4. Community content in training data. Blog posts, Stack Overflow answers, and tutorials sometimes contain errors. AI absorbs and amplifies them.


Real Examples

  • Shopify: AI confidently suggests /admin/api/products/{id}/images/{id}/alt.json for updating alt text. Doesn't exist. You need the product update endpoint with images nested.
  • Stripe: AI invents webhook event types like payment_intent.partially_refunded — sounds logical, doesn't exist.
  • OpenAI's own API: AI references deprecated endpoints, old model names, or parameter formats from previous API versions.
  • Google APIs: AI mixes up Google Cloud, Google Workspace, and Firebase endpoints constantly.

    • The Cost

    This isn't just annoying. Every fake endpoint costs 30-90 minutes of debugging. In a complex integration, you might hit 3-5 hallucinated calls before you learn to stop trusting the AI and start reading docs.


    That's potentially a full day wasted on code that was never going to work.


    How to Protect Yourself

  • Always have the official API docs open in a separate tab while using AI
  • Verify every endpoint exists before writing implementation code
  • Check API version numbers — AI often references outdated versions
  • Use the API's own SDK when available instead of raw HTTP calls
  • Feed the actual API docs to the AI as context rather than relying on its training data
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    Steps

    1. 1Always keep official API documentation open alongside AI-generated code
    2. 2Verify every endpoint, method, and parameter against the official docs before implementing
    3. 3Check API version numbers — AI frequently references deprecated or outdated versions
    4. 4Use official SDKs when available instead of raw HTTP calls the AI suggests
    5. 5Feed actual API documentation to the AI as context rather than relying on training data
    6. 6When something doesn't work, check if the endpoint exists BEFORE debugging your code

    ⚠️ Gotchas

    !

    AI will give you the endpoint URL, request body, headers, AND a sample response — all for an endpoint that doesn't exist

    !

    The more popular the API, the more versions exist in training data, the more hallucinations you get

    !

    AI mixes up similar APIs — Stripe/PayPal, GCP/Firebase/Workspace, AWS services

    !

    Deprecated endpoints in training data get served up as current best practices

    !

    You'll waste 30-90 minutes debugging auth or formatting before realizing the endpoint is fake

    !

    AI-invented endpoints often follow logical patterns — that's exactly why they're convincing

    Results

    Before

    AI generates clean API integration code with specific endpoints, parameters, and sample responses

    After

    30-50% of suggested endpoints are hallucinated, deprecated, or from wrong API versions. Hours wasted per integration.

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