You can’t fix broken systems by adding more memory. You can’t solve misalignment with token limits. And you definitely can’t outsource consequence to users and call it intelligence.

That’s the problem with how most people are talking about “context engineering” right now. It’s become a shorthand for prompt tuning, retrieval hacks, and window optimization. And sure, those things matter. But they’re not the whole thing. They’re not even most of the thing. Real context work starts higher up the stack. It asks basic questions: What is this system supposed to do? Where is it being deployed? Who has to live with the outcome? What does it mean for the system to be right? Context isn’t just a string of inputs or a clever stack of documents.

It’s the environment a system enters: the assumptions it carries, the power it holds, the feedback it’s accountable to. And it shows up across multiple layers in the interface, in the domain, in the history of interactions, in the structure of the organization deploying it.

We’re about to see agents dropped into every kind of workflow. Not just government services, but logistics, scheduling, customer service, HR, procurement, billing, healthcare. These tools won’t live in test environments. They’ll show up in the middle of someone’s shift, or someone’s urgent task, with a shiny new name and no real understanding of where they are or what they’re for.

When that happens, and the system gets something wrong, most people won’t get a second chance. They won’t have a human in the loop. There won’t be a “try again” button that resets the logic. They’ll be left to absorb the error, explain what went wrong, or try to fix something they didn’t break. That’s the new context burden. And it’s going to land hardest on people who are already carrying too much.

What makes this worse is that a lot of these failures aren’t bugs. They’re features. Systems are being built to deflect, delay, and route people toward self-service. Not because that’s better, but because it’s cheaper. So when an agent fails to understand what someone’s asking for, or refuses to escalate, or locks someone out because a form was filled wrong, that’s not always an accident. It’s the product working as designed.

If we keep treating context as a technical constraint instead of a systems issue, that’s exactly what we’ll keep building. Real context work has to take all of that seriously. It means building systems that know what they are and what they’re not. Systems that can recognize their limits, carry forward a sense of where they’ve been, and make that legible to the people using them. It means building in a way that allows for correction, escalation, or refusal, not just infinite simulation.

Otherwise, we’re not solving complexity. We’re just offloading it and calling it innovation. If we want to build systems that work, we have to start by making them make sense. Not just to the model, but to the people on the other side. That’s what context engineering ought to be.