Leap of Faith: AI Hopping is Essential for Best Results
There are loads of artificial intelligence tools available to professionals. Even lawyers, frequently late adopters of technology, are aggressively utilizing AI. But, different AI models are better at different things – even when they exist on the same platform. For example, Google Notebook LM can design a robust set of instructions for building graphics; but, Google Gemini can actually execute those most effectively. In some cases, you may want to use one AI to create a prompt for a different AI. Some of this also depends on whether you want a single output from a GPT, or whether you’re looking to build an agent.
There’s been lots of virtual ink spilled over the question of which AI to use for which tasks, via Reddit threads & longform articles & YouTube videos & product guides, etc. So, if you’d like to explore the matter further, there’s plenty of reading to be done.
But, the best way to figure out which AI you prefer for which tasks, is try them out for yourself. There is truly no substitute for experience. So, A/B test various AI tools with the same project, and see which perform best. That learning phase of the program is inefficient, for sure. However, if you can get a handle on which projects to deploy – or, which segments of projects to deploy – in which AIs: you’ll be leveraging artificial intelligence like a pro; and, your ‘AI hopping’ will become more efficient than utilizing singular ill-fitting tools for the wrong projects.
Artificial intelligence is like a glorious all-you-can-eat buffet, that’s never going to be cheaper. So, why are you filling your plate with tapioca pudding, and pretending to enjoy it?
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