After receiving feedback that his writing was too long, a PM built a custom GPT to make messages more concise. He fed it newsletters and books on effective writing from experts, creating a personalized coach that helped him apply the feedback in his daily work, leading to better engagement from colleagues.
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After testing a prototype, don't just manually synthesize feedback. Feed recorded user interview transcripts back into the original ChatGPT project. Ask it to summarize problems, validate solutions, and identify gaps. This transforms the AI from a generic tool into an educated partner with deep project context for the next iteration.
For experienced leaders new to AI, building a custom GPT is an ideal starting point. A simple but high-value project is to feed a conference schedule into a GPT, allowing users to ask "Which sessions should I attend if I'm a senior PM?" This teaches core AI concepts without requiring coding.
For those without a technical background, the path to AI proficiency isn't coding but conversation. By treating models like a mentor, advisor, or strategic partner and experimenting with personal use cases, users can quickly develop an intuitive understanding of prompting and AI capabilities.
When employees are 'too busy' to learn AI, don't just schedule more training. Instead, identify their most time-consuming task and build a specific AI tool (like a custom GPT) to solve it. This proves AI's value by giving them back time, creating the bandwidth and motivation needed for deeper learning.
Instead of generic PRD generators, a high-leverage AI agent for PMs is a personalized reviewer. By training an agent on your manager's past document reviews, you can pre-empt their specific feedback, align your work with their priorities, and increase your credibility and efficiency.
To simulate interview coaching, feed your written answers to case study questions into an LLM. Prompt it to score you on a specific rubric (structured thinking, user focus, etc.), identify exact weak phrases, explain why, and suggest a better approach for structured, actionable feedback.
Building a single, all-purpose AI is like hiring one person for every company role. To maximize accuracy and creativity, build multiple custom GPTs, each trained for a specific function like copywriting or operations, and have them collaborate.
Don't let performance reviews sit in a folder. Upload your official review and peer feedback into a custom GPT to create a personal improvement coach. You can then reference it when working on new projects, asking it to check for your known blind spots and ensure you're actively addressing the feedback.
Go beyond using AI for research by codifying your North Star, OKRs, and strategic goals into a personalized AI agent. Before important meetings, use this agent as a 'thought partner' to pressure-test your ideas, check for alignment with your goals, and identify blind spots. This 10-minute exercise dramatically improves meeting focus and outcomes.
An automated workflow analyzes call transcripts and sends immediate, private feedback to the sales or CS rep on what they did well and where they can improve. This democratizes high-quality coaching, evens the playing field across managers of varying skill, and empowers motivated reps to upskill faster.
