You can build production ready AI applications in hours, not months.
You don't need a massive team.
You don't need custom models.
You just need a plug and play mindset.
It's all about plugging the right pieces together to be deploy ready.
Unfortunately, many developers feel overwhelmed by AI.
I originally thought I needed to:
Fine tune my own LLM
Manage GPU heavy cloud infra
Spend months building something useful
But it turns out that we can get result quite rapidly.
AI Abstraction Strategy
The goal is to set our minds to wrap existing models in a production-ready interface.
I built an AI Sentiment API in a day using the following ingredients:
Hugging Face Transformers to leverages LLMs
FastAPI to expose it with a web-ready endpoint
Docker to containerize it and run it anywhere
I built an /analyze endpoint that
Accepts user input
Processes it through a hugging face sentiment model
Returns a JSON output with a label and confidence score
This can easily be plugged into
Chat bots
Support systems
Dashboards
Email processors
Swapping it out
This model can be swapped out for classification, summarization, PDF parsing, etc.
The biggest take away is to start thinking about AI as a Strategy Pattern
The behavior changes, but the interface stays the consistent.
In video games we can swap out weapons but keep the same controls.
With this architecture, we can swap out models while keeping the API the same.
LLMs are becoming modular. Your role is to plug them together intelligently.