A Conversation with Mini Me

What if you could talk to yourself about everything you’ve ever written?

I’ve spent years capturing notes, strategies, and reflections across roles and projects.
Then I built a system that lets me have a real conversation with all of it – in my own voice.

Why I Built It

Like most strategists, I’ve accumulated years of thinking – buried in OneNote pages, PowerPoint decks, and half-finished ideas. The insights were there, but they weren’t accessible. Even OCR scans still retained the messiness of my scribbles and the lack of structure in early notes.

I wanted to know: what would happen if I could ask my past work a question – and it could answer back?

How It Works

The first stage in any project like this is working out the tech. There were a number of criteria that I used:

• Does it actually do the job! Sounds obvious, but I didn’t want to spend lots of time figuring out bits of technology then finding out that it didn’t cover what I needed
• Price. My target was sub-$10 per month. I tried doing it for $0 per month but the difference in effort and quality was enormous, for just the price of a burger.
• My prior knowledge. There is some tech I know about and a lot that I don’t. I didn’t want to spend months learning something new, even if it could be argued it was more appropriate.
• Variety. It might have been easier to do everything in a single unified tech stack for example Microsoft, but that would make the project less interesting for me.

Given the above, this is what I went with:

Process at High Level

Step 1 – Collect all the Data

By far the most interesting, laborious but useful part of the process. I have around 14 years worth of information about all of the work I have done. With hindsight I would have had all of that formatted in the same way and well structured for AI ingestion.

That was absolutely not the case:

A lot of the work is the preprocessing often unstructured and poorly scribbled information. here are just a few of my data sources as well as lots of blog posts, Word documents, PowerPoint documents; really, everything.

• PowerPoint files
  These were manually selected and hardcoded into the script — a reasonable tradeoff given how few I needed to track.
• RSS Feeds
  • My blog at bjrees.com
  • A few curated industry insight feeds
• OneNote Notebooks, such as:
  • Project documentation (e.g. Skynet, The Oracle)
  • Notes from a Cambridge Judge Business School programme
  • Third-party and personal research logs
• iCloud Backups
  These contained archived slide decks and supporting materials.

Step 2 – Index

Once there is some structure to data you can start the next stage of building a database. I used Pinecone, a vector database, perfectly suitable for the task.

Step 3 – build an online interface where I couldn’t ask questions

Nothing fancy, but I wanted an easy way where I could ask questions without having to use the command line, firing up services or anything. For this I used Google Cloud Run extensively.

Step 4 – Voice

This stage was certainly unnecessary. But as mentioned part of this is about learning and growing your knowledge. I wanted to see if there was a way of using a cloud service to speak like me (a “Mini me!”). The following voice recordings are not me. they are from ResembleAI, and cost me around $2 to make. The one word it struggled with was BJREES sadly.

What Happened?

The conversation surprised me. what was particularly impressive and I think the most important part of the project is that it pulled out ideas from previous years into coherent answers. We all have a recency bias in our memories personally I’m a long way from having total recall. The world of marketing has evolved significantly but there are certain core concepts that have remained. A simple example – understanding your customers was the main task of marketing from the first project I did to the most recent.

Example exchanges:

Real me: “What’s the biggest barrier to marketing and product alignment?”
Mini me: “In your past notes you wrote that alignment isn’t the real issue — it’s trust in shared metrics.”

Real me: “What motivates you to keep building?”
Mini me: “You wrote once: progress feels meaningful when it changes how people work, not just what they do.”

The key point here is that though I remember writing this many years ago, I certainly didn’t remember the detail and I certainly didn’t remember the connections with other pieces of work that I did.

Why It Matters

it was enjoyable doing this work but crucially this wasn’t about creating a gimmick. It’s a glimpse of what happens when brand, knowledge, and AI converge.

Imagine your company being able to talk to its accumulated knowledge:

• Every customer insight.
• Every proposal, presentation, and lesson learned.
• All accessible through natural conversation.

I see this as a future direction for Brand intelligence – providing more to your customers to help them do their jobs well.