The Product Manager in Me Couldn't Leave This Workflow Alone

A few months ago, a friend who runs an event planning business was telling me about the challenge of keeping track of client information.

Leads would come in through Instagram. Requirements would be discussed over WhatsApp. Inspiration photos would show up in text messages. Budgets lived in spreadsheets. Important details were scattered across notes, documents, and conversations.

As she walked me through her process, I found myself asking the same question I ask whenever I look at a product or workflow:

"Why is this so hard?"

The more we talked, the more familiar the problem felt.

Over the course of my career, I've worked on enterprise onboarding platforms, analytics products, workflow automation systems, customer communities, and AI-powered experiences. Different industries, different users, and different technologies—but many of the underlying problems are surprisingly similar.

Information gets fragmented. Processes become manual. People spend far too much time hunting for answers that already exist somewhere.

This felt like one of those problems.

Starting With the Workflow

The first thing I did was map out the workflow.

Every event followed roughly the same journey—from lead intake and discovery through proposal creation, planning, and event execution.

As I looked at each stage, it became obvious that the biggest challenge wasn't event planning itself. It was information management.

A client might mention their venue in one conversation, their budget in another, and their color preferences a week later. By the time planning was underway, finding a specific detail often meant scrolling through hundreds of messages trying to remember where it had been discussed.

I started wondering what it would look like if all of that information lived in one place.

Building the MVP

That question led me to build a simple internal application.

Nothing sophisticated—just a lightweight tool that could manage leads, clients, event requirements, budgets, planning activities, and inspiration photos.

The goal wasn't to build software for the sake of building software. I simply wanted to make the workflow easier.

As I started using the application, I realized that the most valuable information wasn't sitting in spreadsheets or documents.

It was buried inside conversations.

That's where the project got interesting.

Where AI Actually Helped

Like many product managers, I've spent the last couple of years learning about AI, experimenting with LLMs, and thinking about where they create meaningful value.

This seemed like a perfect opportunity to move beyond theory and apply it to a real-world problem.

I built a workflow that could take exported WhatsApp conversations and generate a structured summary of event requirements.

Instead of reading through dozens—or sometimes hundreds—of messages, the planner could quickly see event details, preferences, important dates, budget considerations, and open questions.

The first time it worked, I remember thinking:

"This is actually useful."

Not because it was technically impressive. There are far more sophisticated AI applications being built every day.

What excited me was that it solved a real problem. It eliminated work that nobody wanted to do and made important information easier to access.

To me, that's always been the most satisfying kind of product work.

The Part That Surprised Me

One thing surprised me.

The AI wasn't the hard part.

Getting the data was.

WhatsApp turned out to be relatively straightforward. I found a way to export conversations and upload them into the application.

Instagram was a completely different story.

Many customer inquiries start in Instagram DMs, and I assumed getting those conversations into the system would be easy.

It wasn't.

I spent far more time researching ways to extract and process Instagram conversations than I did building the AI workflow itself. Between platform limitations, data access challenges, and integration hurdles, it quickly became clear that the problem wasn't the AI—it was the plumbing underneath it.

In fact, I still haven't fully solved it.

Oddly enough, that's become one of my favorite parts of the project.

As product managers, we often focus on the feature that users see. But some of the most interesting challenges live behind the scenes—in integrations, workflows, data quality, and the countless details required to make an experience actually work.

What This Reinforced For Me

This project reinforced something I've learned repeatedly throughout my career.

Great products rarely start with technology.

They start with friction.

Whether I'm working on an enterprise SaaS platform, an AI-powered workflow, or helping a friend solve an operational problem, the process is usually the same. Spend time understanding how people work, identify what's slowing them down, and then look for ways to simplify the experience.

The technology is important, but it's rarely the starting point.

What's Next

I'm continuing to evolve the application and experiment with new ideas.

I'd love to automate event briefs, generate planning checklists, and eventually use inspiration photos to help suggest themes and décor concepts.

And yes, I'm still trying to figure out the Instagram problem.

Some challenges are harder to let go than others.

Why This Project Got Its Hooks Into Me

The funny thing is, I started this project thinking I was helping organize an event planning workflow.

What I really ended up doing was reminding myself why I became a product manager in the first place.

I've always enjoyed understanding how people work, finding inefficiencies that everyone has learned to live with, and building solutions that make those problems disappear.

Whether the user is an enterprise customer, an internal team, or a small business owner, that part never gets old.

And that's probably why this project got its hooks into me.