AI isn’t just another piece of software you plug in. And the real skill isn’t knowing which model topped a benchmark or how to craft a perfectly engineered prompt. I used to think the best prompt writers would win, but that’s not where the leverage is. The real advantage comes from changing how you work, making it more structured, more repeatable, more pattern-oriented so the AI actually has something consistent to learn from.
AI Is a Pattern Engine and Your Workflows Are the Patterns
At its core, AI is a pattern engine. It gets exponentially better when it can see and reuse consistent patterns in how you get your work done: meetings, tasks, documents, decisions. That’s a hard truth for those who grew up hearing their parents insist they “be more organized.” And now AI shows up asking the same thing. Its performance is a direct reflection of the person or system it serves. If it had a favorite aesthetic, it would be: everything in its place, happening the same way, every time.
Let me show you what I mean: imagine you hired a world-class chef to cook in your home kitchen (as we all casually do, right?). The chef is brilliant but when they walk in, they find olive oil next to the cereal, spices split across three cabinets, the counter covered in machines promising to cook your food in every imaginable way, and jars of rice and exotic flours you don’t remember buying. There’s no space to actually cook, and the chef is entirely unfamiliar with the environment.
Under these circumstances, can you really expect to get the best of their skills? They’ll spend half their time navigating the mess, uninspired by the chaos and you’ll quietly wonder why the meal wasn’t more magical.
Organization here isn’t just “good file hygiene.” (Although, yes, if your drive consists of “New Folder (7)” and three versions of “Final_FINAL_v7_USETHIS,” we should talk). What I mean is turning your day into something AI can actually learn from, habits that run the same way every time.
What “AI-Friendly” Work Really Looks Like
For example:
- Every important meeting gets recorded, auto transcribed, run through the same summarizer prompt (decisions, owners, risks, next steps), and saved in the same place with a consistent name.
- Key client or project conversations live in one running document or workspace, so context stacks over time, memory over memory instead of being scattered across inboxes and chats.
- Tasks don’t live half in email, half in your head, and half in a project tool. They land in a single system, with predictable fields: owner, due date, status, links, notes.
- Research isn’t a pile of tabs you swear you’ll come back to. It’s dropped into a repeatable template where AI can help you compare, synthesize, and challenge the sources.
- Your go-to prompts are saved as templates, not reinvented from scratch in a rush before the next meeting, so you can improve upon them over time
- Your projects start with a well-structured brief that all talent contributing can utilize. Then all projects get connected, building a common brain where all meetings, findings, changes are added to a place everyone involved can access, utilizing AI.
- Your information is consolidated into comprehensive summaries that preserve key decisions and learnings to inform future projects.
For this, you don’t need agentic AI tools or a custom LLM hooked into enterprise data. It starts at the smallest scale: one person and their laptop. Scale that to a team, a department, an organization and you're truly utilizing AI.
AI doesn’t reward the most skilled user. It rewards the most consistently organized one. So just accept it, your mom is back into your life, nagging you to pick up your room!
— Yas Dalkilic
Head of AI, RAB2B