
Memora
An AI-powered system that creates a living paper trail of requirements across the lifecycle of a complex product. Born from a decade of managing requirements in aerospace, Memora tackles a problem every Engineering, Product, and Design organization knows: context gets lost.
Context
ArtCenter MDes | Design Strategy & Leadership (GIXD-609)
Role
Product Designer & Strategist
Tools
Figma, GenAI
Timeframe
1 Semester (Spring 2025)
Deliverables
Product Strategy Pitch, Fictional Organization Case Study, Three Role-Specific Prototype Flows, Presentation Deck
The Problem
Requirements are always changing and no one remembers why.
90% of memories are forgotten after 7 days. EPD teams flip between 6 to 9 tools every week. Decisions scatter across Slack threads, meetings, JIRA tickets, and Figma comments until no one can say why a requirement changed, what tradeoffs were made, or where the source of truth lives.
I know this pain viscerally. At JPL, I manage requirements that decompose from top-level mission needs down through multiple subcontractors. I've watched context evaporate every time personnel rotate off a program, leaving newcomers to reverse-engineer decisions from old commits and orphaned threads.
Figma's annual State of the Designer report surfaced the same tension. One product manager put it plainly: "Sometimes we get caught up in the what and why, but not so much on the context or how we got to this iteration of the product."
Memora started as a question: what if a tool could trace the why behind every requirement, automatically, without adding process to already overloaded workflows?
Process | Research Far and Wide!
Early in the semester our entire MDes cohort tapped-in to our professional network where we interviewed C-suite leaders and individual contributors to understand product failures involving Engineering, Product Management, and Design teams. Executives framed lost context as a velocity and compliance risk: delayed decisions, duplicated work, misaligned teams. ICs experienced it as daily cognitive overhead: scrolling old threads, asking around for institutional memory that no single person holds.
The convergence of research fed into each of our projects and for myself, it gave Memora a defensible position: this is a traceability problem affecting every layer of an organization, and any solution that adds workflow overhead will fail on arrival. Weekly critique from faculty and industry guest speakers pressure-tested the pitch until it compressed to a single line.
Solution | Meet Memora
Surface the decisions, changes, and tradeoffs that shaped your requirements, wherever they happened.
Memora works like a digital detective. Using APIs and optical content recall, it ingests artifacts from the tools teams already use (Slack, JIRA, Figma, email, meeting transcripts), links them to requirement objects, and narrates a clear lineage: what changed, who changed it, and what insight drove the shift.
The core design principle: traceability without extra workflow. Memora never asks people to change how they work. Agentic AI handles the context-linking; explainable AI lets teams interrogate and trust the rationale it surfaces. Every requirement becomes a living document with a narrated history of its own evolution.
Memora In-action
To demonstrate Memora in context. The semester also had us to frame our products to how it would apply to an organization. I proposed Horizon Motors: a fictional electric vehicle startup deploying cross-functional EPD pods (Integrated Product Teams) across vehicle subsystems. The fictional framing let me stage realistic organizational failure without any single company's politics. It's also interesting to note this framing reflects a lot what I've seen in the aerospace industry - the auto industry, which shares the common pain points between hardware and software development nicely plays an analog here!
The story follows the Interactive Unit Group, where three people each hold part of the story and none can trace the whole:
Ollie (Design) joined three weeks ago. He finds design spec parameters with no context. Safety requirement? Compliance? Someone's habit from two years ago? He searches Notion, Slack, Confluence. Nothing connects.
Marcos (SWE) keeps the system running, but years of undocumented decisions leave him guessing in the codebase. No changelogs, no comments, just old commits and unease about the team's versioning habits.
Annie (PM) fields questions from clients, leadership, and legal about critical UI changes and can't find a coherent explanation. She spends entire days toggling tools, piecing the story together manually.
The scenario plays out across one week. A font size change ripples through the team until Friday's all-hands, when leadership asks: "Who approved this? Is it compliant?" No one knows. Emergency all-hands to manually trace a single UI spec change.
Three Role-Specific Flows
Memora was prototyped with Figma to exercise how Memora supported each of those roles in the Horizon Motors scenario.
Design: Memora surfaces the decision trail. Ollie queries the animation parameter and immediately sees the linked requirement, the original review thread, and the compliance constraint behind the value. He tags the design lead to confirm before publishing. Newcomers onboard without archaeology.
Engineering: Memora reveals the gaps and raises the bar. Tracing incomplete change histories shows Marcos how fragile past practices were. He starts championing clearer code rationale and traceable implementation trails. Memora doesn't just answer his question. It shifts his behavior.
PM: Memora finds the why. Complete rationale lets Annie translate complexity into clarity for stakeholders. She models a shift from chasing clarity to building it in, making context-sharing a team habit rather than an optional task.
Fun Excursion | Meet Tracy
A film noir detective remora fish, because requirements deserve personality too.
Tracy is Memora's mascot: a detective-minded remora fish, magnifying glass always at the ready, inspired by Salesforce's mascot ecosystem. Requirements traceability is dry subject matter, and Tracy gave it a narrative hook. A detective who follows the trail of decisions through organizational murk made audiences lean in, and made the concept stick.
GenAI tools were exploding that semester, and Tracy became my testbed: rapid character exploration through generative iteration until the mascot felt playful, on-brand, and genuinely useful as a storytelling device. The pitch closed with a brand activation concept: photos with Tracy, limited edition keychains for the first 100 visitors.
Impact | Question Organization Culture
"What has to happen in the company for this to succeed?"
The sharpest prompt of the course pushed the project beyond product design into organizational strategy. Memora requires two cultural shifts.
Teams must value the rationale behind decisions, not just the outcomes: documenting why things changed, using capabilities already in their stack like AI meeting notes and comment fields. And requirements ownership must spread across EPD, breaking the silo that says "requirements = PM responsibility." Design and engineering must feel empowered to contribute to requirement evolution, not just receive it. Memora only works as a connective layer if the organization treats it as a shared asset.
Reflection
Always have the elevator pitch ready. Memora taught me to compress a nuanced systems problem into one line: requirements are always changing and no one remembers why. That compression skill shows up in every stakeholder conversation I have professionally.
Hold every altitude at once. The problems that matter look different depending on where you sit. Good product thinking means holding the executive view and the IC view simultaneously, then designing for both.
CONOPS and service design are the same discipline wearing different badges. Both map actors, touchpoints, and decision flows across complex systems. Memora made that bridge explicit and gave me the vocabulary to carry aerospace documentation rigor directly into product strategy.
Personality earns attention for serious tools. People remember Tracy. More importantly, they remember the problem Tracy solves.