AI agent memory is definitely needed for personal use, but I’m less sure about its value in other contexts.
For example, agents can cling to past design mistakes, circling back even when you want to move on.
Sometimes, a fresh session is all you need.
AI’s bottleneck isn’t just intelligence. It’s architecture.
Autonomous engineering needs systems that self-heal, adapt, and evolve without losing control.
Perhaps the missing architecture is one of those ideas that seems impossible to find and impossible to unsee once found.
We’re considering adopting Jev from @typesafeai. It’s amazing tech, the kind that makes me think, “Why didn’t I think of that?”
But how durable is its advantage if @OpenAI or @AnthropicAI competes directly on decision models? Switching costs seem low when it’s an API integration.
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@TipsBubble@Major_Grooves@bubble@Nodirbay Never used bubble so I don't know what granularity of the code you can see/customise. Most likely only bubble themselves could build a feature like that
Autocomplete for #AIart#prompts!
I built Teleprompter, a Recurrent Neural Network trained on 50,000 of the best #Midjourney prompts. I linked it with #GPT3 to further refine the outputs.
Link to the LIVE app and examples in comments 👇
RT for more AI projects!
#ai #stablediffusion #dalle @Replit@leap_api