Leher Pathak

I am constantly learning new ways to use AI to be more efficient and impactful as a PMM, just like the rest of this PMM community. A few things I've found to be helpful: * Product naming: I've used ChatGPT to help me come up with inspiration for product names, especially when I'm trying evoke something intangible, like a concept or feeling. (Note: ChatGPT loves being creative, so you'll definitely get some names that you make you chuckle.) * First drafts: Sometimes I'll ask ChatGPT to help me with a first draft of an email or a tweet. It's important to remember that ChatGPT's written drafts are only as good as the information you feed into it. So try to be as detailed as possible—you can even upload a PRD into ChatGPT to help give it context. * Charts: I've been really impressed with ChatGPT for creating charts. You can upload a spreadsheet directly to ChatGPT and ask it to create any kind of chart (bar chart, line graph, etc.) You can even specify the x- and y-axis and color-coding. * Slide visuals: While I haven't figured out how to get ChatGPT to make a slide deck for me yet, the DALL·E capabilities can really help when you need to create images for a presentation.

While I know you're looking for course recommendations, I genuinely believe that nothing can teach you more about AI than doing. While you can watch YouTube videos and listen to podcasts, being willing to dive into a tool like ChatGPT is the best way to quickly grasp AI and stay ahead of the curve. I'd suggest creating a challenge for yourself: open ChatGPT in your browser every morning and make it a point to try to use it for at least one task a day. This could be anything from writing an email to doing competitive research to coming up with a clever name for your PMM team. The more familiar you get with AI, the more you'll start to test the boundaries of what's possible.

This can be tricky in an industry where new products seem to be launching every day. Here's how I think about differentiation: * Having strong positioning and use cases. Building and launching products means nothing if your customers don't understand why they should use them. Illustrating the "why" through specific use cases and customer examples goes a long way. * Making the product extremely easy to use. Competitors may have similar products, but not everyone thinks deeply about the user/developer experience. Providing clear guidelines, offering tutorials, and hosting educational webinars are all tactics to consider. * Focusing on the product ecosystem, not the feature. It's easy to over-rotate on a single product or feature. But the real value comes from how all of the individual capabilities work together and fit into the bigger picture of the product ecosystem.

Personally, I'm always impressed by candidates who are deeply curious and eager to find new ways to use AI in their day-to-day jobs. For example, building a GPT to help write a first draft of an email campaign or using ChatGPT to analyze registration data for a webinar. So while I don't look for specific skills that AI can't replace, I do look for candidates who are open to embracing AI in new ways.

For PMMs working at AI companies, turn to the people who use your AI products every day. Learn about their AI use cases, understand the gaps in the product, and listen to their aspirations to use AI in new ways. There's so much we don't know about the potential of AI, so informing the product roadmap isn't just about filling product gaps but also about shaping what the future of AI might look like. For PMMs working at non-AI companies and trying to influence Product teams to add AI to the roadmap, start exploring specific use cases of AI. Would launching AI-powered personalization into your products improve the customer experience? Would translating content for global audiences help expand your reach? The key is to propose a few solutions backed by real customer examples, and then work with your Product team to focus on one solution to start testing.

Building trust in AI products starts with the product and company itself—is there a dedicated AI safety team? Are the right AI safety checkpoints in place to safeguard from abuse? Is the company taking a principled approach to rollout? If the foundations of AI safety are there, then the messaging becomes much easier. I approach messaging with a few things in mind: * Being transparent about the intended use of the technology and the risks, including how the company is mitigating those risks through safety precautions * Knowing your audience and using the right language that will resonate with them (which generally means: no unnecessary jargon!) * Illustrating the use cases of AI to make the technology feel more tangible and less mysterious