---
title: The hype around AI coding tools needs a reality check.
type: post
date: 2025-09-18
source: linkedin
original_url: "https://www.linkedin.com/feed/update/urn%3Ali%3Ashare%3A7374436381139480577"
topics: ["ai"]
summary: The hype around AI coding tools needs a reality check. One of the leading AI copilots I tried went so far as to invent an API. It started building an app around this imaginary API and even pointed me to “documentation” that didn’t exist—completely fabricated.…
draft: false
---

The hype around AI coding tools needs a reality check.

One of the leading AI copilots I tried went so far as to invent an API. It started building an app around this imaginary API and even pointed me to “documentation” that didn’t exist—completely fabricated.

I then pointed it to the correct documentation, thinking it would recover. Instead, after “reading” it, the copilot fabricated another API. That was the moment I stepped back.

I genuinely wanted it to work. But reality hit—these tools still struggle once the problem goes beyond boilerplate.

Leaderboards and benchmarks may look impressive, but they don’t capture what happens when you try to build real applications. In practice, copilots:

-> Shine at small, repetitive tasks.  
-> Struggle with abstraction, system integration, and real-world constraints.  
-> Often add more debugging than acceleration.

Unless you’ve been through the full cycle of designing, coding, and deploying with these tools, you won’t see the gap between demo performance and production reality.

I’m preparing a detailed breakdown from the app I’ve built—and will share soon. This will help manage expectations and shape how we think about building with these tools.