Why Claude AI Is Not Production Ready
For months, I’ve been using Claude, specifically Sonnet 3.5 Model, which I believe is one of the best large language models (LLMs) on the market.
Its capabilities in generating code are UNPARALLELED.
But for all its brilliance, I’ve run into a recurring issue:
Claude is simply not production-ready.
Let me explain.
The Native UI
As a developer working on real-world applications, Claude’s native UI feels restrictive.
It’s fine for light usage or exploratory work, but anyone looking to scale their workflows will hit its daily message limits.
Even for paying (Pro) users, the constraints on usage are frustrating and make it feel like you're working on borrowed time.
This led me to rely more heavily on their API.
But... didn’t improve much.
The API Experience: 429 Errors
While integrating Claude’s API into my tools, I kept encountering 429 Too Many Requests errors.
At first, I assumed I had maxed out my usage quota, but that wasn’t the case.
These errors appeared even when I was well within my allowance.
After reaching out to Anthropic support, I received this response:
We have recently experienced unprecedented demand which our team is actively working to better support. This behavior isn't limited to you or your usage. The impact of this increased demand is widespread across all of our user base. Since your original message, we've introduced fixes to improve capacity and we're continuing to do everything we can to mitigate this behavior
Translation?
Even paid users are competing for limited capacity.
If you’re looking for reliability, this situation is less than ideal.
Why It Matters
When you’re building production-grade tools or customer-facing applications, reliability isn’t optional—it’s the baseline.
A 10-20% failure rate (or more) is a deal-breaker.
As incredible as Claude is, these limitations make it impractical for serious deployments where uptime and consistency are crucial.
My Solution: An Open-Source UI
Given these challenges, I’ve decided to build a custom interface that relies on the API to sidestep the restrictions of the native UI
It's built using Nuxt 3 and Nuxt UI, and have used the SQLite database to store user data and for keeping track of the conversation history and tokens usage .
It’s clear that Anthropic needs to focus not just on improving Claude’s brain but also its operational backbone.
Final Thoughts
Claude’s potential is undeniable—it’s one of the most impressive LLMs I’ve ever worked with.
But until Anthropic resolves its scalability issues and improves its API reliability, Claude will remain a brilliant but flawed tool for anyone aiming to use it in production.