Gregory's Server@ploum I'm not a _typical_ user for certain, but I find a good LLM assistant to be quite valuable to me in all 5 of the steps listed, plus at least 2 others (0. Decide if I want to build vs buy, and 6. Document). It won't do the hardest work for me, but it saves me a lot of time and results in a better product by helping me think through hard problems (best rubber-duck ever).
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3 comments
 @Bsstahl @ploum What is the value of a machine that uses a text-based and not logic-based statistics to make the biggest decision that impact your outcomes? As a product manager, the place where it would help is consolidating/summarizing text-based input so it's faster for you to learn what the market is saying. Rubber ducking with it works for a little bit, but why not rubber duck with an SME or user who has opinions? @MayInToronto @ploum LLMs are fantastic tools for suggesting alternatives that I might not have thought of. They are assistants. They cannot make the decisions for you, but they can be an invaluable aid in making suggestions. They can also suggest things that SMEs and users couldn't possibly. For example, few SMEs can incorporate the results of research papers from multiple languages and fields of study, while any LLM that has ingested these papers can do so easily. |
@ploum The biggest problem I see is that there are a few extremists (marketers?) screaming that it will work for almost everything, and so many extremists screaming that it will work for almost nothing, that it is tough to communicate how these tools are properly used.