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Description
This coaching package is designed to give you a clear, practical introduction to AI product management. By the end, you’ll understand the fundamentals, have hands-on experience applying frameworks, and know exactly how to take your next steps. Possible uses of coaching package, but not limited to: • Use case exploration: evaluate AI opportunities with PM frameworks • Tool setup: learn core AI/ML concepts through examples • Guided analysis: study case examples of AI products • Experimentation basics: design small-scale tests • Next steps: roadmap for deeper PM development Outcome: By the end, you’ll understand how to evaluate and manage AI opportunities with confidence.
What you'll get from this package
A framework for evaluating AI use cases
Case study analyses of AI products
Exposure to key AI/ML concepts for PMs
A personalized PM roadmap
Additional details
Coaching delivered via live sessions.
Services included:
Skill Building
Talk to a team member
Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
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Get help with Freelancing, AI Agents, and .
Offered by Jesse L.
Joined June 2021
5.0
Learn how to best use AI for Product Development | AI for PMs
I'm a PM on the new products team at GoFundMe, where I've shipped AI-powered features end-to-end: a multi-step generation pipeline for user-facing content, prompt systems tested against real user inputs, and an eval system that holds quality steady in production. I work in the actual mechanics of building with AI: scoping what an agent should do, structuring the pipeline, testing it against real inputs. And I know how this works inside a real org, where shipping AI means coordinating handoffs across Product, Design, and Eng. That's where most enterprise AI efforts stall. What sets me apart is that I build outside of work too. I've shipped several AI products solo with agentic coding tools: a fitness app, an AI image generator, a personal CRM, etc. I run a tight loop with AI at every step: write the spec, break it into tasks, execute with coding agents, then capture what worked and what broke in a file the agent reads next time. Each loop ships faster than the last. When I coach, I'm teaching the loop I run myself.
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