For the last decade, companies have invested heavily in data. Pipelines, warehouses, dashboards, metrics. We got very good at moving data around. We did not get very good at agreeing on what it means.

Now AI has raised the stakes.

LLMs have plenty of data. What they lack is context that holds up in the real world. Context that is structured, interoperable across systems, composable across use cases, and durable over time. They do not know how your business actually works, how entities relate, where definitions come from, or which assumptions are safe to make. So they hallucinate, overreach, or quietly produce answers no one should trust.

A context strategy is how a company encodes shared understanding into a system its people and agents can rely on.

It defines entities, relationships, processes, constraints, and ownership. It captures how the business reasons about itself. Not in docs. Not in dashboards. In structure that both humans and machines can use.

This is why adding more tools alone does not fix the problem. Dashboards show results, not meaning. Agents execute tasks, but without guardrails they become risky. You end up with faster answers and lower confidence.

In 2026, the most important question will not be how fast your systems are or how much data you have. It will be whether every human and every agent is operating from the same understanding.

Companies that treat context as a first-class strategy will move faster, operate more efficiently, and compound leverage over time. Those that don’t will see AI add cost before it adds value.

Context is not a nice-to-have.

In 2026, context is the strategy.

It belongs in the foundation of how teams and systems operate.

Galaxy is that foundation.