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Description
Work 1:1 with an expert to learn how to use AI to build functional prototypes, internal tools, and product experiments faster. Possible uses of coaching sessions, but not limited to: - Building product prototypes using AI coding tools - Creating internal tools and dashboards without engineering support - Vibe coding techniques for rapid product experimentation - Using AI to generate and iterate on front-end designs and interfaces - Validating product ideas with working demos before committing engineering resources - Building data analysis and reporting tools with AI assistance
What you'll get from this package
The ability to build working product prototypes quickly using AI coding tools
Skills to create and iterate on internal tools without engineering dependencies
Faster product experimentation through AI-assisted building and testing
Additional details
Coaching delivered via live sessions and .
Services included:
AI Automation
Prototyping with AI
AI Product Design
LLM-Optimized Code Base
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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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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