This is what every agentic coding tool does. You can try it yourself right now with the Gemini CLI, OpenCode, or 20 other tools.

I don't think we'll get genuine AGI without long-term memory, specifically in the form of weight adjustment rather than just LoRAs or longer and longer contexts. When the model gets something wrong and we tell it "That's wrong, here's the right answer," it needs to remember that.

Which obviously opens up a can of worms regarding who should have authority to supply the "right answer," but still... lacking the core capability, AGI isn't something we can talk about yet.

LLMs will be a part of AGI, I'm sure, but they are insufficient to get us there on their own. A big step forward but probably far from the last.

Advanced reasoning LLM's simulate many parts of AGI and feel really smart, but fall short in many critical ways.

- An AGI wouldn't hallucinate, it would be consistent, reliable and aware of its own limitations

- An AGI wouldn't need extensive re-training, human reinforced training, model updates. It would be capable of true self-learning / self-training in real time.

- An AGI would demonstrate real genuine understanding and mental modeling, not pattern matching over correlations

- It would demonstrate agency and motivation, not be purely reactive to prompting

- It would have persistent integrated memory. LLM's are stateless and driven by the current context.

- It should even demonstrate consciousness.

And more. I agree that what've we've designed is truly impressive and simulates intelligence at a really high level. But true AGI is far more advanced.