We trained a product group to build better, faster with Generative AI
Services offered
- Generative AI & LLM Foundations Training
- Prompt Engineering Workshops
- AI in the Product Lifecycle (SDLC/PDLC)
- AI Agent Design
- Custom GPT Creation & Memory Tools
- Rapid Prototyping with AI
- Feature Brief Development & Refinement
- Backlog & Sprint Planning with AI
Outcomes
Over the course of a custom, three-day bootcamp, product managers and designers developed fluency in generative AI, learned to integrate AI into their product development lifecycle, and built working prototypes powered by AI tools. Teams left with practical assets - custom GPTs, feature briefs, and prototypes - that directly accelerate their day-to-day work.
Key outcomes included:
- 17 participants trained across product, design, and operations roles
- Increased confidence in AI use cases: participants reported a 50% improvement in comfort applying AI to their daily work
- 65 re-usable prompts created since the bootcamp
- Clear integration path mapped for AI across research, design, build, and test stages of the SDLC
“...for those that did not have much exposure before, it was a very good course to introduce them to the terms, some of the technical details, and lots of great examples. It generated a lot of excitement and I hope we continue to build on it.” - Testimonial from bootcamp participant
The Story
Incident IQ, a leading K-12 technology platform, partnered with Able to accelerate their product teams’ understanding of Generative AI. With AI reshaping the product landscape, the challenge was not only building technical fluency, but also embedding AI directly into the product development lifecycle. Over three days, Able designed and delivered a hands-on bootcamp that moved from GenAI fundamentals to applied use cases, giving product managers and designers the tools to think AI-first and work faster. By the end of the program, participants not only understood AI’s potential but had created tangible assets that could accelerate their next product cycle.
Our Approach
Comprehensive Architecture Assessment
1. Grounding in Core AI Fluency We began by demystifying Generative AI and Large Language Models, giving participants a shared foundation. Through live demos and interactive lectures, teams explored how models work, where they excel, and where their limitations - such as hallucinations and bias - require human oversight.
2. Embedding AI into the Product Lifecycle Rather than treating AI as an abstract tool, we showed how it could map directly onto the product development lifecycle. Teams experimented with AI-driven research, market analysis, and feature brief creation, learning how to integrate AI into discovery, design, build, and test phases.
3. Hands-On Learning Through Custom Tools Participants didn’t just hear about AI - they built with it. Teams created custom GPTs, designed feature briefs, and prototyped product concepts using tools like Lovable. These exercises gave them tangible takeaways to use in their day-to-day roles.
4. Building an AI-First Mindset The bootcamp wasn’t only about tools; it was about culture. Through structured reflection, team discussions, and collaborative exercises, participants practiced approaching problems with AI-first thinking - seeing AI not as a shortcut, but as an accelerator for better product outcomes.
