Agent Infrastructure Is Not the Hard Problem
New agent runtimes. New hosting platforms. New ways to deploy your agents on AWS, Azure, or whatever managed service is trending this week. The entire conversation has drifted toward where agents run, as if the deployment target is the bottleneck.
Hosting agents is a solved problem. It was solved before the current wave even started. You can run them on a $5 VPS, a serverless function, or a container orchestrator. It doesn't matter. The compute layer is commodity infrastructure. Optimizing for it is like selecting a brand of shelf to put your empty product on.
And if we're being honest, AWS or GCP are not exactly the gold standard any more. They are neither the most cost-effective nor the most secure path forward for most agent workloads. The cloud giants have conditioned everyone to think that complexity equals capability, but for the vast majority of agent deployments, you're paying for overhead you don't need.
The real bottleneck is on the other side entirely, which is making agents do things that are actually useful. Net-positive, measurable, "this-changed-my-workflow" useful. Not demo useful. Not blog-post useful. Production useful.
Right now, the use cases are painfully limited. Most agents in the wild are glorified wrappers around chat completions. They can summarize, rephrase, and answer questions from a knowledge base - which is fine, but it's table stakes. The hard problems is knowing when to apply agents at all. Automation without direction just scales problems. An agent that sends emails faster is useless if nobody wanted those emails. An agent that generates content at scale is a spam machine unless the content was worth creating in the first place. An agent that writes code is, well, ... you get the point.
Pouring resources into better hosting while the capability gap stays wide is like building faster highways to nowhere. The destination matters more than the road.
Focus on what agents can do. The infrastructure will follow.
A practical note: the fastest way to find where AI actually helps is to prototype fast and fail cheap. That's why we built ChatBotKit as a rapid prototyping platform - so you can test ideas in hours, not months, and discover what's worth building before you commit to building it.