Why I’m building an AI coding runtime that doesn’t depend on one model

GUSTAVOSIS — Mon, 07 Sep 2026 00:02:41 +0000

AI coding tools are getting better very fast, but there’s one architectural decision I don’t really like: most of them are deeply tied to a specific model, provider, or workflow.

That works well while that model is the best option.

But models change constantly.

One month one provider is ahead, then another gets cheaper, local models improve, pricing changes, limits change, and suddenly your whole workflow is attached to a different stack.

That’s the problem I’m trying to solve with Airuncode.

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The idea is simple:

The runtime should stay stable. The model should be replaceable.

Airuncode runs locally and acts as the execution layer around the agent. The model is just one component of that system.

So instead of rebuilding your workflow around each provider, the runtime handles things like:

project files
terminal access
git
tests
execution
agent orchestration
context
provider switching

You can use cloud models, your own API keys, or local models depending on the task.

I think this matters because developers are going to use multiple models, not one.

Maybe you want a frontier model for architecture, a cheaper model for repetitive work, and a local model when privacy or cost matters.

The workflow shouldn’t have to change every time.

I’m also experimenting with a second idea inside Airuncode called V-CORE.

Instead of asking an AI agent to recreate rendering, physics, terrain, animation, and other low-level systems from scratch, V-CORE gives the agent native capabilities it can build on top of.

That leads to a broader question I’m interested in:

How much of an agent’s capability comes from the model, and how much comes from the runtime and tools around it?

My suspicion is that the runtime matters much more than people currently give it credit for.

Airuncode is already usable, and I’m building it in public:

https://airuncode.com

I’d especially like feedback from people using Cursor, Claude Code, Codex, OpenCode or local models every day.

Do you actually want model independence, or would you rather use a coding agent that is deeply optimized around one provider?

DEV Community: GUSTAVOSIS

Why I’m building an AI coding runtime that doesn’t depend on one model