From the course: Chief Technology Officer Career Guide

AI tools for product

From the course: Chief Technology Officer Career Guide

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AI tools for product

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- [Narrator] With the advent of AI, an entirely new suite of tools is available to aid and speed the product process. Understanding your users and what to build in what order is the main focus of most product managers, and to do this correctly requires research. There are a number of tools and AI techniques for research. Using tools like ChatGPT, Perplexity, and Google Gemini, you can search the web and do competitive analyses, pricing analyses, and more. Using AI research tools like Strella that can automate user research can help get research faster, and speed insights. You can also use tools like NotebookLM to interact with data and get better insights. Once you have your data, you'll need to plan and prioritize. There's an emerging tool set that can help prioritize features, write product documentation, and even write user stories. This can range from using a ChatGPT folder or a chat of your data to help you by simply asking it, to tools like NotebookLM or Crackle that allow you to pull in data and research from just about anywhere and use it to prioritize roadmaps, create product requirement documents, and even create a full backlog prioritized of user stories. When it comes to design, Figma continues to integrate AI tools to speed up the creation of screens and content. Additionally, Miro's Uizard is a prototyping tool that can generate designs and an interactive prototype using a simple prompt, or screenshots, or even a sketch. AI has given the ability for non-technical users to create applications without having to write any code. Tools like Lovable, Replit, and Bolt give users the ability to create real applications using just a prompt. This can allow PMs to build working prototypes and MVPs of new products and features without having to take up critical dev cycles. On the other hand, if you have your Figma designs ready, you can use some Figma plugins like Locofy, Builder.io, and Anima to go directly to React, HTML, or even mobile code. This new workflow can save hundreds of laborious dev hours. Lastly, product analytics are integrating new machine learning and AI algorithms to better understand your user, and even to predict behaviors. And now for a word of caution, while these tools can be invaluable, they are new, and their results should always be reviewed by humans. Because they're trained on the web, they may provide false hallucinations, or more likely, mediocre and non-innovative results. In spite of that, AI is having a strong impact on how product managers do their jobs, helping them speed up by doing research, strategy, design, getting code built faster, and better understanding their users.

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