Treat Model Choice Like a Business Decision

How Product-Aware Engineers Avoid LLM Vendor Lock-In

Welcome back to HosseiNotes! 🚀

Before we dive in, a quick human pause.

Some of you know I’m Iranian. With everything that’s been happening recently in Iran, the past while has been heavy 🖤. I stepped back from writing, both here in HosseiNotes and on my LinkedIn, because for me, every Iranian feels like family.

I just want to say: I’m thinking of everyone affected, and I truly wish safety and health to people on the ground. ❤️

Now, back to building.

Last time we escaped the playground → plugged real API calls into code.
Prompts became infrastructure. Huge win. 🎉

But almost everyone then makes the quiet killer mistake right after…

They glue their whole product to one model + one provider and go “shipped! ✅”

It feels clean… until reality hits 😈

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The nasty surprises waiting in production 💥

• 💸 Pricing jumps overnight

• ⚡ Latency suddenly doubles

• 🚦 Rate limits bite exactly when users spike

• 📉 Model version “upgrade” quietly gets worse at your use-case

• 🏆 A new model crushes yours… but you’re locked in

• 🧠 Or you realize a hosted LLM no longer makes sense and you want to deploy an SLM or self-host a model instead

That’s not just a tech choice.
That’s a business gamble you didn’t sign up for.

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Real business juice you unlock 💰

• 🔁 Swap models without sweating

• 📉 Control costs proactively (hello cheaper/faster options)

• 🛡️ Survive when your main provider sneezes

• 🚀 Experiment fast & low-risk (“let’s A/B this new model next week”)

• 🧠 Even let the app decide which model to use, based on intent, constraints, or context

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Meet LiteLLM 🔦

LightLLM is a provider-agnostic interface for working with LLMs. It gives you one consistent way to call models across vendors, without pulling provider-specific details into your app.

Philosophy = dead simple:
Abstract the provider, not the product.

Your app just says:
“Generate → here’s messages + rules”
No SDK drama, no vendor quirks leaking into your logic.

Here’s our Trip Advisor… now provider-agnostic style:

from litellm import completion

model = "openai/gpt-4o-mini"

response = completion(
    model=model,
    messages=[
        {"role": "system", "content": "You are a ruthless budget travel advisor... [our full mega-prompt]"},
        {"role": "user", "content": "Weekend trip from Madrid, max €300, romantic vibe"},
    ],
    temperature=0.7,
    max_tokens=900,
    api_key="Your API Key",
)

print(response.choices[0].message.content)

For the full implementation, visit this note’s repo here: https://github.com/HosseinCodes/provider-agnostic-trip-advisor

If no access yet → ping notes@hossein.ai with your GitHub username.

Now, if you want to switch to Anthropic’s Claude, you only need to change this line
(and update your API key accordingly).

model = "anthropic/claude-opus-4-6"

That’s it.

Beautiful, right?

Feature-wise: identical output.
Architecture-wise: you just bought massive future leverage.

Provider, model, key → all config now.
No if/else hell. No rewrite pain.

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Boom! this tiny seam just supercharged your AI app’s future 🔥💥

You’ve now got a clean, powerful entry point where intelligence flows in. And because of it, you’ve unlocked massive leverage:

• 🔄 Instant model swaps - chase the hottest new LLM the second it drops

• 💸 Smarter cost plays - route to cheaper/faster options on the fly

• 🛡️ Bulletproof reliability - auto-fallbacks when your main provider hiccups

• 🚀 Lightning-fast experiments - A/B test models, prompts, or entire reasoning paths without rewriting a line

• 📈 Effortless scaling - add smart routing, evals, monitoring, or cost-aware orchestration later… and it all snaps in cleanly

We’re not doing those advanced tricks yet but once you have that clean entry point, everything else becomes additive rocket fuel, not painful surgery.

You just turned models from a risky bet… into interchangeable tools you command.

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Core mantra moving forward:

Prompts + product logic = your IP.
Models = interchangeable suppliers.

Internalize that → vendor-lock-in fear disappears. Magic.

In the HosseinCodes repo I already pushed the LiteLLM version.

Clone → drop your key → play.
If no access yet → ping notes@hossein.ai with your GitHub username.

Next week, we’ll start building something new together: a Customer Support Triage Engine, and along the way we’ll learn a bunch of really cool patterns that power serious AI apps.

Stay sharp. Keep shipping value.
See you soon! ✌️