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After the AI Engineer conference, I'm thinking about some problems from AI models to overcome. I got this list from the top of my head. Anything missing? • continuous learning or better memory? • long-term planning • prompt quality resilience: different prompts shouldn’t alter the outcome cont

• pushback: they shouldn’t agree in all cases and infer the real goal • multi-step reliability • cost aware: they should know when writing a Python script is better than doing it themselves

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