Hey guys. I am sorry i am late, but Melissa is in the hospital currently with our daughter. She wanted me to reach out and let you guys know she is sorry for not having new content as if right now. They have been there since Thursday night, with no idea of release date. She did also want me to say, she will pop on sometime real soon with a udate from her. Just been hetic right now for our family. You guy can talk to each other and maybe help one another as well, in her absence

One of my biggest tips for you: Use NotebookLM & Google Gemini together. Use the Notebook as your source of truth. Keep all of your pertinent documents there. Create a separate notebook for each niche/project/task. In Gemini, use the '+' to add the Notebook and ask questions querying the data within in. Do you use NotebookLM and/or Gemini and have any tips to share? Post them below and let's build out a toolkit for everyone.

Ever feel like the AI is just making stuff up? It’s not trying to lie to you—it’s just a world-class pattern-finder following the "breadcrumbs" you left. If the crumbs are too far apart, the AI fills in the gaps with its best guess. In the Lab, we think of a prompt as a trail. If you want the AI to reach a specific destination, you have to place the crumbs closer together. 3 Quick Tips for a Clearer Trail: 1. Skip the Subtext: AI doesn't "get" hints. If you want a friendly tone, tell it: "Use a warm, conversational tone." 2. Define the Scope: Instead of "Tell me about marketing," try "Give me 3 beginner strategies for digital marketing." 3. The Goal Check: Always include a verb. Use "Summarize," "Rewrite," or "Brainstorm" so the AI knows exactly what action to take. What’s one task you’ve been "vague" with lately? Let’s try to tighten that breadcrumb trail together!

Are you still throwing words at a wall and hoping they stick? It’s time to stop the guessing game. In this video, we’re diving into the "Big Four" Framework we use at The Prompt Lab to get consistent, high-quality results from AI every single time. The 4 Pillars of a Perfect Prompt: 1. Clarity: Skip the jargon and use plain, direct language. 2. Context: Give the AI the "who, what, and why" behind your task so it understands the mission. 3. Format: Tell the model exactly how to "dress" the information—do you want bullet points, a table, or a short email? 4. Iteration: Your first response is just a draft! Don't be afraid to refine and steer the model as you go. I’ve put together a template so you can start using these pillars today. Download the resource attached to this post. The Pillar Challenge: Which of these four pillars do you struggle with the most? Let me know in the comments, and let’s refine your prompting style together!

Today at my W2, I decided to take on a long-overdue task and organize our internal documentation into a functional knowledge base. We've been using some big, name brand platform for the last 18 months after transitioning from another smaller, independent platform prior. This one is allegedly one of the best in the industry, but it's proven to be clunky and ineffective for our team as we are often unable to find the documentation we need and often the search functionality has issues as soon as our activity increases due to customer tickets during outages or post-upgrade bugs. It's been a headache. Enter NotebookLM. I've been using it personally for a while now (about a year, maybe a little over - I used it in Labs prior to release) and I have found it to be everything I had hoped some others would have been years ago. I can put my source information in and the Notebook helps me synthesize the sources into clean, digestible information in the structure and format I need. For our company, because of the way our internal KB is designed I'm having to pull the actual PDF URLs individually and can't get a good scrape on the site yet, but even with only the core system foundational documentation ingested, NotebookLM has generate customer-ready documentation I could put out in a presentation or provide back in a support ticket RIGHT NOW. My long-term goal is to use this to assist with onboarding new engineers and assist with troubleshooting for existing engineers, ensuring they don't overlook the simple steps as we often tend to look for the complex solution first these days. I'll let you know how it goes and how well it's received when I present it at our AI project meeting later this month. As a Senior Engineer in my product area, being able to use NotebookLM to synthesize the wealth of documentation we have on the product and generate video overviews, audio overviews, data tables, slides, and more is absolutely invaluable and will save many hours creating similar documentation manually, ensuring we can keep the documentation current without as much manual work.