Comment by d4rkp4ttern
Comment by d4rkp4ttern 4 days ago
An interesting shift I’ve seen over the past few weeks, is we’re starting to refer to bare LLMs themselves as “agents”.
Used to be that agent = LLM + scaffold/harness/loop/whatever.
Comment by d4rkp4ttern 4 days ago
An interesting shift I’ve seen over the past few weeks, is we’re starting to refer to bare LLMs themselves as “agents”.
Used to be that agent = LLM + scaffold/harness/loop/whatever.
GPT 5.2 in a simple while loop runs circles around most things right now. It was released barely a month ago and many developers have been on vacation/hibernating/etc. during this time.
I give it 3-4 more weeks before we start to hear about the death of agentic frameworks. Pointing GPT5+ at a powershell or C#/Python REPL is looking way more capable than wiring up a bunch of domain-specific tools. A code-based REPL is the ultimate tool. You only need one and you can force the model to always call it (100% chance of picking the right tool). The amount of integration work around Process.Start is approximately 10-15 minutes, even if you don't use AI assistance.
Yes this “REPL/CLI is all you need” realization is exactly what’s behind the wild success of Claude Code and derivative CLI coding agents.
This is exactly how I think of it. An agent has three elements: intelligence (LLM), autonomy (loop) and tools to do anything interesting/useful.
I think some of the distinction here is that the more recent "bare LLMs" have been more purpose built, augmented with "agent" specific RL, and in general more fine tuned for the requirements of "agents". Things such as specific reasoning capabilities, tool calling, etc.
These all make the "bare LLMs" better suited to be used within the "agent" harness.
I think the more accurate term would be "agentic LLMs" instead of calling them "agents" outright. As to why its the case now, probably just human laziness and colloquialisms.