Ai

The AI Agent as a Personal Research Librarian

The research trap we all fall into

I reckon every professional knows this feeling. You're working on a new project – maybe a competitor analysis for a fintech product launch. You fire up Google, skim a few articles, take some hasty notes. A few months later, you're doing a similar analysis for a different project. And you start from scratch. You find some of the same sources. You re-read the same reports. You type out similar summaries. It's a complete waste of time.

I've been there more times than I'd like to admit. The problem isn't that we don't do research. It's that we don't organise it in a way that compounds. Each research session lives in isolation. Notes get buried in folders, bookmarked pages get lost, and that brilliant insight you had about consumer behaviour in 2023? Gone. That's where my local AI agent – I call it Hermes – has completely changed how I work.

How an AI agent changes the game

Think of Hermes not as a chat bot you use once and forget, but as a personal research librarian. A librarian who doesn't just fetch books – they remember what you've read, file your notes properly, and remind you of relevant material when you need it. They work in the background, organising your knowledge so that every research effort adds to a growing base of understanding, rather than disappearing into the void.

The key difference from a regular search tool is persistence. When I ask Hermes to research something, it doesn't just give me a summary and move on. It saves that summary, along with the source links, into a structured knowledge base that I own locally. Over time, that base becomes incredibly valuable.

Saving summaries with context

Here's a concrete example. Last quarter I needed to understand changes in Australia's ePayments Code for a compliance project. I fed Hermes a few regulatory documents and a couple of industry newsletters. I said: "Summarise the key changes to the ePayments Code as of March 2024, and note where each change affects merchant onboarding." Hermes gave me a clean summary, bullet points, and a table linking each change to a specific business process. It also saved that summary with metadata – the date, the sources, and my project tag "compliance-2024."

A few weeks later, I was advising a startup on card payment integration. I didn't need to re-read the code. I just asked Hermes: "What were the key ePayments Code changes that impact new payment flow designs?" and it surfaced the relevant summary from its library, cross-referenced with new details I'd added since. That saved me at least a couple of hours.

Structuring notes for later use

Research isn't just about finding information – it's about making it useful later. Hermes helps me structure notes in a way that makes retrieval natural. I can tag each research item by project, topic, date, or even by the person who recommended the source. When I'm working on a new deck, I can ask: "Show me everything you have on open banking in fintech, sorted by relevance to merchant acquiring." It pulls up notes, summaries, and links from multiple research sessions, all in one view.

This structure also means I never have to worry about losing a good source. If I read a brilliant article from a payment industry analyst, Hermes saves both the URL and my personal notes on why it mattered. Later, if I need to quote that analyst, I can find it in seconds. It's like having a personal reference manager, but one that actually understands the content.

Comparing sources over time

One of the biggest benefits is comparing information across different time periods. For example, I track competitor pricing and feature changes in the fintech space. Every few months I feed Hermes new press releases and product update pages. I can then ask: "Compare the latest Square pricing changes with what we saw in June this year." The agent highlights the differences, notes any contradictory information, and even flags if a source has become outdated. That kind of longitudinal analysis is a nightmare to do manually – you'd need to open multiple browser tabs and cross-reference dates. Hermes does it in seconds.

This works especially well for regulatory research. Rules change, and keeping up manually is a full-time job. With Hermes, I can maintain a living record of regulatory updates. When a new discussion paper comes out, I compare it to the saved summary of the old one. The agent points out the shifts, and I don't have to re-read the whole document. It keeps my knowledge current without constant effort.

Building a reusable knowledge base

The real magic happens after a few months of doing this consistently. Your AI agent becomes a repository of everything you've researched – reports, articles, internal documents, meeting notes. It's not just a pile of files. It's an interconnected web of ideas. Because I've asked Hermes to link related topics – like "buy now pay later regulation" and "credit card surcharging" – it can surface connections I might have missed. It might say: "You saved a summary about the RBA's surcharging review in 2023. That directly relates to your current project on interchange fee disclosure." That kind of cross-reference takes minutes of my time but saves hours of re-identification.

This knowledge base is especially valuable when managing multiple projects. I'm often working on several initiatives at once – a partnership deal, a product enhancement, a regulatory submission. Each project draws from overlapping research. Without Hermes, I'd be repeating work across projects. With it, every piece of research enriches every project. The base compounds, and the value grows exponentially.

Connecting old research to new decisions

Perhaps the most practical use is when I'm making a decision. Recently I was evaluating two different payment gateways for a client. I didn't have time to re-do a full comparison. Instead, I asked Hermes: "Based on my saved research from the last six months, what are the key risks and benefits of each gateway?" It pulled together notes from a webinar, a few product comparisons, and an internal assessment I'd done for another project. In under a minute, I had a concise summary that informed my recommendation.

That's the value of a personal research librarian. It doesn't just help you find information – it helps you remember, connect, and apply what you already know. And for anyone managing multiple projects, that's not a luxury. It's a necessity.

Need help setting up your own AI assistant? Feel free to contact me at [email protected].