The contents of this email will stand you out in the hiring world

Some metrics from Microsoft's 2024 Work Trend report caught my eye:

• 66% of leaders say they wouldn’t hire someone without AI skills.

• 77% say they’d rather hire a less experienced candidate with AI skills than a more experienced candidate without them.

What are we going to do in light of this information? 

We’re going to dive, headfirst into building out our AI knowledge resulting in an indispensable, you.

My (not so) bold prediction

While AI chatbots dominate headlines, the real enterprise impact will come in the form of RAG (Retrieval Augmented Generation). At its core, RAG simply means allowing AI to pull from an organization's own knowledge base to provide relevant, company-specific answers to questions.

What makes RAG so transformative - and why I predict its widespread adoption - is its ability to solve a universal business challenge: organizing scattered company resources.

By converting databases, documentation, links, videos, images, and meeting notes into a unified, AI-readable knowledge layer, RAG creates a ChatGPT-like experience that draws from your company's specific information, enabling better:

• New-starter onboarding - instant access to company information that typically takes months to absorb

• Knowledge management - connecting information across previously siloed departments and documents

• Customer support - giving reps immediate access to accurate product information and past solutions

Understanding the what (not the how) of RAG

I start all of these conversations with a simple truth:

The same goes for AI and RAG systems. You just need to know what they do, not how they do it.

Here's RAG in its simplest form:

First, you give it some information:

• Upload your documents (anything from manuals to meeting notes)

• The system breaks these down into smaller "chunks" - maybe a few sentences each

• It then organizes these chunks by how related they are to each other similar to organizing books on a shelf - similar topics go together

Then, when someone asks a question:

• The system looks at their question

• Finds the most relevant chunks of information

• Gives back an AI-powered answer using only those specific chunks as context

That's it. No rocket science, just a smart way to organize and retrieve information when you need it.

Homework (5 minutes)

“Homework again?!”

Yes, there is always homework and today we’re becoming badge-carrying RAG users.

• Go to: notebooklm.google.com (it’s free)

• Under “My Notebooks”: Click “Create new” and name it “Moon Landing”

• Click “Add source”: add these links:

  • https://en.wikipedia.org/wiki/Moon_landing

  • https://en.wikipedia.org/wiki/Mars_landing

• Ask: “How will lessons from the moon landing guide decisions around travel to Mars?”

You can see how the tool neatly retrieves information relevant to the question you asked. And remember, it's doing this across two fairly dense Wikipedia articles.

The Bottom Line

Your new found strategic edge on getting to Mars illustrates a larger point: RAG's power in leveraging verified, specific information rather than generating answers from scratch.

Armed with this knowledge, you're now on your way to joining the 77% of candidates employers prefer - those who understand and can harness AI solutions to provide massive value for organizations.

You've seen firsthand how RAG connects information meaningfully, revealing insights that manual searching might take hours to uncover. You could apply this to nearly anything - study materials, project documentation, medical histories, financial reports - the reality is, our moon landing example barely scratched the surface of RAG's capabilities.

While others are still asking ChatGPT to write blog posts and generate pictures of cats, you're equipped with a tool that transforms how organizations handle their most valuable asset: information.

Go you.

PRO TIP

Combining last week’s homework with this week’s will send Notebook LM to another level.

• Search a topic in Perplexity.ai: and ask it to return only peer reviewed journal articles or reports from major consulting firms on the subject

• Add to Notebook LM: the cited results and expand the conversation

I wish I had this when I was at university