AI for Product Teams: Idea to Spec to Ship

Aki Wijesundara

AI Advisor | Google AI Accelerator Alum

Manu Jayawardana

AI Founder | Co-Founder & CEO at Krybe

AI for Product Teams: Idea to Spec to Ship

In one focused day, your product team compresses the path from idea to shipped. We open with a free discovery call to map how you research, spec, and build today, then spend four hands-on hours using Claude and Claude Code to synthesise research, draft clear specs, and stand up working prototypes. Your team turns interviews, tickets, and feedback into themes in minutes, often with RAG over your own user data, then drafts a spec engineering can build from, with the edge cases and acceptance criteria you would have missed and the research kept attached so the why is never lost.

From there the prompt engineering and agentic workflows take a spec to a clickable prototype the team can react to today, so you test an idea before committing. Everything is built on a real feature and slots into your existing process. By the end of the day each group ships a synthesis, spec, or prototype, and you leave with a shared playbook plus a follow-up office hour to hold the new pace.

What you’ll learn

Your team compresses idea to shipped, synthesising research, drafting specs, and standing up prototypes with AI.

Turn interviews and feedback into themes and insights in minutes
Cut a pile of tickets and notes into the few things that matter
Pull signal from your own user data without reading every line by hand

Draft a clear spec from a rough idea, ready for engineering to read
Spell out edge cases and acceptance criteria you would have missed
Keep the spec tied to the research so the why is never lost

Stand up a working prototype to test an idea before you commit to it
Turn a spec into a clickable draft your team can react to today
A shared playbook so the team keeps shipping faster after we leave

Workshop agenda

Before the day: Discovery call (1 hour, free)
We meet your product team, look at how you research, spec, and build, and tailor the day to your tools and process.
Hour 1: Research synthesis
We turn real interviews, tickets, and feedback into clear themes and insights, live in the room.
Hour 2: Idea to spec
Take a rough idea and draft a spec the team can build from, with edge cases and acceptance criteria.
Hour 3: Spec to prototype
Stand up a working prototype from the spec so the team can test the idea before committing to it.
Hour 4: Capstone on a real feature
Each group ships a synthesis, spec, or prototype on a real feature, then presents it to the room.
After the day: Office hour
A follow-up session to unblock the team as the new workflow moves into the product cycle.

Learn directly from Aki & Manu

Aki Wijesundara

Contact

AI Advisor | Educator | Google AI Accelerator Alum

Manu Jayawardana

Contact

AI Founder | Co-Founder & CEO at Krybe | Co-Founder of Snapdrum

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Who this workshop is for

Product leads who want a shorter path from idea to something they can test.
Product managers spending more time on docs and notes than on decisions.
Founders building product who want to ship and validate ideas faster.

What's included

Live sessions

Learn directly from Aki Wijesundara & Manu Jayawardana in a real-time, interactive format.

Free 1-hour discovery call

We map how your team researches, specs, and ships before the day begins.

4 hours of hands-on teaching

Live building on your real research, specs, and features, not generic demos.

A capstone build

Your team ships a synthesis, spec, or prototype on a real feature and presents it by end of day.

A product playbook

The prompts and workflows your team uses to keep moving from idea to ship faster.

Follow-up office hour

We unblock the team as the new workflow settles into the product cycle.

Maven Guarantee

Your purchase is backed by the Maven Guarantee.

Testimonials

Engineers improved the real systems they ship every day, and left with production-ready Claude integrations and a reusable AI playbook.
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The AI training approach is outstanding. Our team learned to build practical AI solutions that we could implement immediately in our educational platform. The hands-on methodology made complex AI concepts accessible to our entire development team.
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