Building internal AI is different from building internal applications. It requires a new approach.

For years, the competitive landscape in software has been framed around the application layer.
Platform A vs. Platform B. Dashboards stacked on dashboards. Functionality compared feature by feature.

That approach is outdated in an AI age.

AI requires a different strategy. The focus shifts away from applications and functionality and toward models. Each model produces outputs. The question is how those outputs can be aggregated and fed into a larger client AI.

In practice, this may look like:

• Model 1 and Model 2 developed in-house

• Model 3 from a software provider

• Model 4 from a niche AI provider

• Model 5 from a generalized AI (think the OpenAIs of the world)

The value doesn’t come from each model in isolation — it comes from connecting them so the client AI benefits from all of them together.

Historically, this wasn’t possible. Applications competed at the platform layer, integration was painful, and everything stayed siloed.

Now, with advances in API frameworks, MCP integrations, and platforms like OpenRouter, aggregation is not only possible but far easier than before. This changes how companies should approach internal builds.

• The applications mindset says:
  “We need another internal platform or dashboard that does X, Y, and Z.”

• The AI mindset says:
  “We need many models that work together — each best at what it does — connected into a larger AI that learns and adapts.”

That is the fundamental shift.

Companies that stay locked into the application mindset will keep adding siloed platforms. Companies that move to a model-first mindset will build internal AIs that are more powerful, flexible, and cost-effective.

That’s where the competitive landscape is headed.
And it’s where internal organizational design needs to evolve — from building applications to building AI systems that integrate, learn, and improve continuously.

The sooner organizations make this shift, the sooner they unlock the real potential of AI.