I build AI products for a living, but honestly? The biggest impact artificial intelligence has had on my life is not the software we ship to customers. It is how I manage my own chaotic schedule.
Being a product manager often feels like drowning in Slack threads while trying to write a strategy document nobody has time to read. We all know the drill. You spend all day in alignment meetings, so your actual deep work gets pushed to Saturday mornings.
I got tired of working weekends. Once I started leaning on AI for my daily tasks, I got about ten hours back every week.
If you are tired of drowning in administrative busywork, here is exactly how I use AI to save time every single week.
Will AI Take Your PM Job?
Let’s address the elephant in the room first. Will AI replace product managers? No. But a PM who knows how to prompt a language model will absolutely run circles around one who doesn’t.
Your real value to a company isn’t formatting Jira tickets or building pivot tables. Your value is talking to users, understanding the market, and making hard tradeoff decisions. The trick is letting the machine handle the administrative fluff so you can actually focus on the hard stuff.
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Stop Staring at Blank PRDs
Writing Product Requirements Documents (PRDs) is arguably the biggest time sink we face. Staring at a blank page trying to list out every single edge case is exhausting.
Instead of writing from scratch, I now use ChatGPT or Claude to generate a baseline draft. You just feed it a simple prompt. Tell the tool what you are building, who the feature is for, and the main business goal. Ask it to spit out a standard PRD template with some starter user stories.
It won’t give you a perfect document. You still have to edit the scope and fix the technical criteria. But editing a messy draft takes twenty minutes, while writing one from nothing takes three hours.
Quick side note: AI only works well if you already know what a good PRD is supposed to look like. If you are new to the field, taking a solid product management course is the best way to learn those foundational skills before you start automating them.
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Speed Run Your Feedback Analysis
If your app is growing, user feedback piles up incredibly fast. App store reviews, support tickets, and random social media complaints turn into a mountain of unstructured data.
I used to waste entire afternoons highlighting spreadsheets trying to categorize these complaints. Now, I just export the CSV file and drop it into an AI tool.
You can literally just tell it: “Group these app reviews into bugs, feature requests, and UX issues. Give me the top three complaints and pull a few direct user quotes for each.” It reads hundreds of rows in ten seconds and gives you a clean summary you can drop right into your next team presentation.
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Clean Up Your Graveyard of Jira Tickets
We all have a graveyard of poorly written Jira tickets. Someone logged “fix login screen” six months ago, and now nobody remembers what the actual bug was. AI is amazing at cleaning up this kind of mess.
I copy a vague ticket, paste it into my prompt window, and add a quick note like “the login button lags on Android.” Then I ask the AI to rewrite it as a proper user story with acceptance criteria.
It instantly formats the text into a clean “As a user, I want…” format with testable conditions. The engineers love the clarity, and sprint planning goes way faster.
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Use AI as a Skeptical Brainstorming Partner
Sometimes you just hit a wall. You know users are dropping off during onboarding, but your brain is too fried to think of a new approach.
I treat AI like a sparring partner. I will ask it to list five ways competitors handle onboarding, or ask it to critique my current strategy. I even tell it to act like a highly skeptical stakeholder and tear my feature idea apart. This weird little exercise forces me to see blind spots I missed because I was too close to the project.
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Translate Engineer-Speak for Stakeholders
Translating technical jargon into marketing copy is another task that drains my energy. When a sprint ends, stakeholders want to know what shipped. They do not care about API refactoring or database migrations; they want to know how the product got better.
Now, I just copy the raw engineering notes and ask the AI to translate them into a quick, friendly email for the sales team. It pulls out the user benefits automatically. I send the update in five minutes instead of stressing over the wording for an hour.
Going Beyond Basic Prompting
Using these tools for busywork gives you a ton of breathing room. But the real shift happens when you go from using AI as a personal assistant to building it into your actual products.
Companies are desperately hunting for people who understand how to manage machine learning features and AI product lifecycles. If you want to make yourself completely indispensable, look into an AI product management course. It bridges the gap between basic prompting and actually leading technical AI engineering teams.
Pick just one administrative task to hand off to AI this week. You will be amazed at how much mental energy you get back.
