How I AI: 3 Game-Changing Workflows for Product Managers

This week, I had a great conversation with Amir Klein, an AI PM at monday.com. Amir ranks #4 out of 90 PMs in AI tool usage at his company – and that's after taking two months of paternity leave!

He’s gotten so used to using AI that, as he puts it, he’s “maybe incapable” of doing his job without it. After he walked me through his workflows, I could see exactly what he meant.

Amir has figured out how to offload the mental burden of context switching from his brain to AI. As product managers, we're constantly juggling multiple projects, feedback loops, and stakeholder requests. Amir’s solution is to set up separate, fully-loaded 'brains' within Claude and ChatGPT. This lets him hold huge amounts of context for different initiatives and work with a kind of super-human efficiency.

In our chat, Amir walks us through three AI workflows that have completely changed how he approaches product management. We’ll get into how he builds these 'second brains,' uses AI to scrape and analyze thousands of customer conversations, taps a custom GPT to sharpen his writing, and even preps for high-stakes interviews using GPT Voice Mode.

Amir shares the exact prompts, tools, and processes he uses, offering practical tips that you can start using in your own work right away.

Workflow 1: Building Your AI-Powered 'Second Brain' for Product Management & Customer Feedback

One of the biggest headaches for any product manager is keeping track of all the context across different projects, teams, and feedback channels. Amir’s first workflow gets right at this problem by creating dedicated AI 'brains' or project folders in tools like Claude and ChatGPT. These 'brains' hold all the relevant documents, discussions, and insights for a specific project, which lets him recall information quickly and make good decisions without all the mental heavy lifting. The approach is especially useful for understanding what customers need and what the market is saying.

Step-by-Step: Creating a 'Second Brain' & Scraping Customer Feedback

Amir's journey into creating an AI 'second brain' started when he was put in charge of the AI agents initiative at monday.com. Faced with countless internal opinions and ideas, he wanted to find an unbiased source of truth from outside conversations. That search led him to Reddit, a goldmine of genuine user discussions.

1. Initial Context Upload: Laying the Foundation for Your AI Brain

To get started, Amir feeds his custom GPT projects a foundational set of documents. This gives the AI a solid understanding of the core mission, product, and goals.

Start with Core Documents: Upload company kickoff decks, team kickoff decks, PRDs (Product Requirements Documents), and even internal product documentation. Amir mentioned uploading a kickoff deck from his manager and pages from the monday.com site as PDFs.

"I had my kickoff that I had, um, that my manager did, and I had a couple of pages that like, I, took from our site of like how Monday works and I just. Command P it. So it's a PDF. And put in another classic example of everything is a text and then it, so it has an idea, it knows what Monday is, it knows what in more or less, like what our goal is as a team."

The "Everything is Text" Mindset: A key tip from Amir, and one I fully agree with, is to think of almost any piece of information as text you can feed into an AI. This could mean printing web pages (like marketing sites or support pages) as PDFs to upload, or converting slides into text-readable formats. It really broadens the scope of what your AI 'brain' can learn from.

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2. Crafting the Scraper with Claude: No Deep Coding Skills Required

Amir needed a way to automatically gather thousands of customer conversations from Reddit about AI agents and monday.com. Even though he doesn't have a deep technical background, he turned to Claude for help.

Define the Problem Broadly: Start by telling the AI your big-picture goal.

Amir's Initial Prompt: "I wanna find everything that's written about monday.com, whether it be on Reddit, Twitter, LinkedIn, anything that's online. I wanted like a sort of an automated freeway to do this."

Iterate on Platform Access: Claude helped Amir focus on Reddit because its API is more accessible than LinkedIn's or X's.

Request Step-by-Step Instructions: Ask the AI for a detailed guide, assuming you have very little technical knowledge. Amir asked for instructions "as if I'm five years old," which is a great way to make sure you don't miss any critical setup steps.

Generate and Run the Python Script: The AI will then write a Python script for you. You just need to input your Reddit API client ID, client secret, and username (which you get by creating a developer account on Reddit).

The script looks for discussions related to Monday and AI or other specific keywords Amir provided.

Result: Amir was able to generate a .csv file with 34,000 rows of conversations.

3. Analyzing the Data with AI: Identifying Patterns and Priorities

Once you have a huge dataset of customer feedback, the next step is to pull out useful insights. Amir simply fed this .csv file back into Claude and asked it to act as his data analyst.

Upload the Dataset: Give the AI the scraped .csv file.

`Prompt for Analysis: Tell the AI what kind of analysis you're looking for. Amir wanted a summarized table showing frequency, percentages, weights, and key discussion points.

Amir's Analysis Prompt: "Here, I'm giving you this, this file. This is one of the files that was pulled out with 30,000 rows, of conversations. And I said, I want you to summarize it. In a table, where you put like the frequency, so how often it comes up, at what percentage I need weights because I need numbers to go back to my team and for myself to know what to prioritize, see what the biggest hottest topics are that people are, are discussing, and some of the key discussion points."

Verify Accuracy: Always double-check the AI's work. Amir’s method is to ask the AI to provide specific quotes or references from the original document for its claims, and then he checks those citations himself. This helps make sure the AI isn't making things up.

Integrate Analysis into Your 'Brain': After the analysis is done, upload the summarized insights back into your custom GPT project folder. Now, the AI has a deep understanding of customer feelings and expectations about AI agents.

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4. Configuring the AI Brain's Persona

Amir doesn't just feed his custom GPT data; he also tells it how to behave so it can be a better thought partner.

Define AI's Role: Tell it to act like a "professional in product management," an "expert," with a "good product strategy mindset" and "product sense mindset."

Demand Candor: This part is really important: Amir tells the AI not to be "too nice." He wants it to challenge his ideas and push back, using its huge knowledge base to help him think better.

"I also gave it like a lot of like instructions on, you know, you know how to give feedback to me, you know how to give candid feedback and you're not gonna be like, too nice to me. You know how to challenge. It's 'cause I hate it when the AI will be like super supportive of every idea that I come up with, like push back on things."

Outcome: Amir now uses this AI 'brain' for everything from drafting initial outlines for PRDs to quickly answering stakeholder questions about product releases. It’s made a huge difference in his efficiency and the quality of his strategic work.

Workflow 2: Creating a Custom GPT for Concise Writing

Feedback is a gift, and Amir is great at using it. He kept hearing that his writing, while good, was often too long (especially in Slack messages). So he decided to build a custom GPT to be his personal writing coach. This is a perfect example of using AI for your own professional development.

Step-by-Step: Building Your AI Writing Coach

1. Gather Expert Guidelines

Amir didn't just tell the AI to "be more concise." He gave it principles on effective communication from actual experts.

Leverage Newsletters and Books: Amir uploaded content from Lenny's Newsletter (specifically an article with Wes Kao's advice on concise writing: "Become a better communicator: Specific frameworks to improve your clarity, influence, and impact"). He also referenced classic writing books like "On Writing Well" by William Zinsser and "The Elements of Style" by Strunk and White. He printed these resources as PDFs and fed them into his custom GPT.

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2. Define the GPT's Instructions and Persona

Clear instructions are essential for getting the output you want.

• Core Function: "This GPT rewrites Slack messages to be more concise, to be more clear, to be readable."
• Maintain User Voice: "maintains the natural voice of the user." This is key to making sure the output doesn't sound robotic or obviously AI-generated.
• Specific Style Directives: Amir also included negative constraints, like "avoid too much dashes, don't give so much bullet points," to fine-tune the writing style.

3. Daily Application: The Instant Coaching Loop

Amir works this coach right into his daily routine.

Draft and Paste: He writes a message, copies it, pastes it into the custom GPT, and lets the AI suggest improvements.

Iterate and Learn: This instant feedback loop shows him how his writing can be better in real-time, which helps him learn much faster than a human coach might be able to.

Outcome: Amir has noticed that people now respond more often to his Slack messages. It's a direct result of the AI helping him make his communication clearer and more to the point. This workflow shows how AI can fill a gap in professional development by providing specific, on-demand coaching.

Workflow 3: Acing Product Interviews with GPT Voice Mode

Preparing for interviews is stressful, especially for complicated roles like product management. Amir’s third workflow changes the game for interview prep by using GPT Voice Mode to run realistic mock interviews that offer immediate, honest feedback.

Step-by-Step: Mastering Interview Prep with AI Voice Mode

Like a lot of us, Amir found that the usual ways of prepping for interviews (watching tons of videos, practicing in a mirror, or roping in friends who aren't trained interviewers) just weren't cutting it. He discovered that GPT Voice Mode could be the perfect, always-available interview coach.

1. Configure Your Interview Coach GPT (Optional but Recommended)

You can just start talking to the AI, but creating a custom GPT gives you a more structured and informed interview practice. Amir made one just for this.

Define Interview Structure: Load the GPT with information about different types of interviews (like product sense or product execution) and how they usually flow. For example, a product sense interview often starts with clarifying the mission, then identifying users and pain points, and finally designing a solution.

"It has like instructions on like what product sense questions like you need to look out for and what product execution questions you need to look out for... the interview needs to clarify the company's mission and the product goals and identify specific target users and pinpoint their real pain points, and then design a solution that solve those pain points."

Add Expert Knowledge Base: Include well-known resources on product coaching. Amir uploaded his "own product manager interview prep document" and posts from "Ben S" (likely Ben Tossell or a similar product coach) on product and product execution.

Provide Personal Context: Upload your CV and a link to the specific job you're applying for. This helps the AI tailor its questions and feedback to you.

2. Set the Ground Rules for the AI Interviewer

This is how you get practice and feedback that's actually valuable.

Specify Role: "I want you, um, to interview me, um, for a product sense interview. I'm interviewing for a role@monday.com. As an AI product manager."

Demand Candor and No Guidance: This part is crucial. Tell the AI not to lead you or give you hints, and to give you honest feedback when you're done.

Amir's Voice Prompt (to the AI): "It's really important that you don't guide me in anything that you are super candid, that you let me, take the reins on where I take this interview. And in terms of like the direction, um, don't lead me to anything. Don't be, um, specific or gimme any hints. Um, and at the end of it, gimme some candid feedback. Let me know if that makes sense to you."

3. Engage in a Live Mock Interview

Open up GPT Voice Mode and start the conversation. The AI will ask you a product sense question that's tailored to the role.

Example AI Question: "Imagine you are tasked with improving the user experience for one of Monday.com's AI powered features. How would you go about identifying areas of improvement and what steps would you take to implement those improvements?"

4. Leverage Continuous Feedback

What's really neat is the AI's ability to learn and give you feedback on your progress over time.

Track Progress: If you practice regularly, the AI can point out where you're getting better. Amir mentioned it told him, "your, your, um, user segment actually has improved. You really figured out how to like narrow down different user segments that are super different."

Outcome: Amir said he felt "super prepared" walking into every interview, which gave him a huge boost in confidence and performance. This workflow does a great job of simulating the pressure and feel of a real conversation in a way that typing just can't. I also pointed out that GPT Voice Mode could be used for other things, like practicing a public speech or even helping kids with oral dictation and reading comprehension.

Conclusion

What Amir Klein shared with us is more than just a few cool AI tricks; it’s a whole new way of thinking about how we handle complex work. He's turned the hassle of context switching into a strength by creating AI-powered 'second brains,' which lets him offload mental strain and pull up information in an instant.

His data scraping and analysis workflow shows how anyone can now tap into huge amounts of customer feedback, turning raw online chatter into real product insights. And his use of a custom GPT for writing and GPT Voice Mode for interview prep shows how AI can be a personal coach for developing our professional skills.

These workflows are perfect for busy PMs, helping us be more efficient, insightful, and confident. I hope you'll experiment with these ideas, build your own AI 'brains,' and see how these tools can help you in your own career.

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