You’ve sat in the meetings. You’ve read the pitch decks. Everyone is obsessed with “autonomous AI agents.” They paint a picture of a monolithic black box that wakes up, thinks for itself, and magically solves your business problems. But when you actually try to build one, it falls apart. The context window overflows, the API calls fail, and the “autonomous” decision-making turns into an expensive hallucination loop.
The problem isn’t your engineering. The problem is the mental model.
Calling every AI system an ‘agent’ is like calling every vehicle a ‘transportation event’—it’s technically true and completely useless.
We have been so distracted by the hype of autonomy that we’ve ignored the actual mechanics of how these systems work. We treat the agent as a single, living entity. But if you want to build scalable, composable AI architectures, you need to look at the class/instance distinction.
In software engineering, a class is the blueprint. It defines the architecture, the goals, and the constraints. The instance is the running, contextualized entity that actually interacts with the environment. An AI agent is not a monolith. It is an instance of a carefully designed class.
The field’s obsession with autonomy is just engineers romanticizing the instance while ignoring the blueprint that actually makes it work.
When you obsess over making a single agent autonomous, you build fragile, one-off prototypes. You hardcode behaviors that break the moment the environment shifts. But when you shift your focus to designing the class layer—the reusable patterns, the strict boundaries, the constraint frameworks—you gain real leverage. You create systems that can be instantiated anywhere, predictably and systematically.
The magic isn’t in the AI waking up and deciding what to do. The magic is in the architecture that tells the AI exactly what it is allowed to do.
If you are an engineer or researcher still chasing the dream of a fully autonomous black box, you are playing a losing game. You are trying to build a god instead of writing good software.
Stop trying to build a god. Start building a really good blueprint.
FAQ
Q: Isn't autonomy the whole point of an AI agent?
A: No. Autonomy is a byproduct of good constraints. If you build a system without strict boundaries, you don't get an autonomous agent; you get a chaotic liability.
Q: How does the class/instance model help me build better systems?
A: It forces you to design reusable patterns instead of one-off scripts. You focus on the architecture and constraints (the class) so that when you instantiate it, it behaves predictably in any environment.
Q: So we should just give up on AGI-level autonomy?
A: We should stop treating autonomy as the starting line. Real AGI won't come from removing constraints; it will come from perfectly structured instantiation.