CUBE × Optura AI: Workshop Mode

Overview

Champaign-Urbana Business and Engineering Consulting (CUBE) is a student technical consulting organization that pairs student consultants with startups. I was paired with Optura AI, a startup building "Workshop Mode," a tool meant to hold an entire AI-opportunity discovery workshop, from the initial intake conversation to the synthesized business cases at the end, in one place instead of scattered across notes and someone's memory.

Most of the work was requirements translation: sitting with Optura's team to figure out what a workshop facilitator actually needed to capture in the room, then turning that into a product spec the software side could build against. That went well enough that Optura brought me onto their own team afterward, as a Technical Product Intern helping build the product I'd been advising on.

My Role

CUBE Technical Consultant (Jan 2026 – May 2026): Advised Optura on Workshop Mode strategy across three discovery phases (pre-workshop, live, and post-workshop), covering how discovery inputs get captured and how AI-assisted synthesis turns them into something usable afterward. Defined three core user roles and structured the engagement into four phases: discovery, design, implementation, and validation.

Optura AI, Technical Product Intern (Jan 2026 – Apr 2026): Moved from advisor to builder, translating the workshop requirements from the consulting phase into an actual product flow: spec'ing the two AI Analyst features that ended up shipping, designing parts of the frontend myself, and defining how workshop context should carry through to prioritization down the line.

Technical Approach

The spec I wrote defined what the two AI Analysts needed to do: take unstructured workshop input, sticky notes, call transcripts, an offhand comment mid-discussion, and turn it into a structured card with a title, a summary, and value/viability scores a team could actually rank against each other. Whether that logic ended up in a prompt or in code was up to the software side at Optura; my job was specifying exactly what "good" looked like on the output side, then checking what got built against it.

I also mapped the handoff between the live workshop and later prioritization work, so context captured in the room (who raised it, what team it affects, what constraints apply) survived long enough to matter once a business case reached implementation.

Beyond the spec work, I designed parts of the frontend directly, including the live workshop view and panel layout shown above, turning the original wireframe and an ongoing back-and-forth with Optura's team into screens the software side could build straight from.

Challenges

The hardest part was operating in two different modes on the same problem: as a CUBE consultant, influence had to come through recommendations an external team could choose to accept or reject; as an embedded Optura intern, I owned implementation directly.

Keeping my recommendations consistent across that shift meant re-checking my own earlier assumptions once I actually had access to real usage patterns and technical constraints, not just what Optura's team described in meetings.

Outcome

Workshop Mode ended up with the four-phase roadmap I'd mapped out, two shipped AI Analyst features that turn raw workshop input into ranked business cases, and a capture-and-handoff structure that keeps workshop context intact through to prioritization. The Optura engagement wrapped in May 2026; I'm still active with CUBE outside of it.