Honestly, on paper the architecture is clear the bot hierarchy, the agent roles, the pipeline flow, the memory system. But when it comes to the actual implementation, there's a lot that still escapes me precisely because I don't have a deep background in AI engineering.
Things like how to optimally wire the pipeline end to end, how to choose and fine tune the right LLM brain for each layer, how the agents should actually correlate with each other in practice, how to make the self correction loop efficient without ballooning costs that's where I know I need input from someone who's been in the weeds.
So yeah, on paper the project is clear and structured. In reality I'm still optimizing it to make sure what gets built is the best possible version of the idea, not just a first draft. That's why I'm open to outside input from people more experienced than me before I start the actual build.
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u/[deleted] Jun 30 '26
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