cebert
I think the author is overlooking a lot of compelling, simpler use cases for agents beyond the complex example provided. For example, I’m working on a Bedrock AI Agent that interacts with some control plane APIs for an application I manage. My goal is to enable L1 support staff to handle basic support tasks through a chat agent, reducing the need to escalate issues to engineering.
This approach has been working well so far. By exposing OpenAPI specs to Bedrock Action Groups and leveraging some prompt engineering, the agent can call APIs on behalf of support. I’ve found that even relatively inexpensive models can handle this use case effectively, given its simplicity. I’m not trying to parse data and insert it in MongoDb like the author is here, but rather simple support tasks like please let this customer change ownership of a previous submitted report.
The business value here is significant. We can offload trivial support tasks to less expensive team members, freeing up engineers. Plus, I can deliver this capability without the overhead of building an entirely new UI, which makes it even more practical.
sandropuppo
In a few years from now, they will be everywhere tho. But I understand the points of the article!
JSTrading
You are an absolute moron for believing this bullshit website. The guy is spamming it all over Reddit on any vaguely trading related subs.
This piece is ignorant at best. It hinges on the argument that current models are too large, and too expensive. It assumes nothing will change with regards to 1) the intelligence of smaller, open source models and 2) the price of larger, more capable models. They are very clearly trending towards "intelligence too cheap to meter", as smaller research labs release highly capable local models (see: ModernBERT for small models, DeepSeek v3 for large models) and larger companies decimate each others margins with continual price decreases (see: the amount of large models that can be accessed for free on OpenRouter).
As we build larger, more capable models, and distill them into smaller, more affordable models, intelligence will only grow in the long term. At that point, creating intelligent agents that operate within your environment is an engineering problem, not a research one.