You Already Have AI. You're Just Not Using It Right.

Here's a question worth sitting with for a second.

You have access to AI. Probably more than one tool. You've asked it things. You've received answers. I know I’ve used it for a menu plan, a workout schedule, a draft email, a summary of something I didn't have time to read. Sound familiar? 

But something isn't clicking. It feels transactional. Scattered. You're not getting the compounding value everyone keeps talking about. You're not sure what you're missing.

Tatsiana Maskalevich knows exactly what you're missing.

As a former product leader at OpenAI and a builder of AI systems that serve millions of users across industries, she has watched this same pattern play out across every profession, every level, every sector. Smart people. Real tools. Incremental results.

The gap, she says, is not the technology. It's how we're using it.

The Biggest Misconception About AI Right Now

Most people treat AI like a vending machine. You put in a question, you get out an answer, you walk away. Maybe you come back tomorrow with a different question. But each interaction lives in isolation, disconnected from the last one and disconnected from what actually happened after you used the output.

That is the gap.

"The biggest misconception I see," Tatsiana says, "is that people get incremental value from day-to-day AI interactions, but there's a big gap between that and when it truly compounds."

The compounding happens when your AI system knows you. When it has context — your preferences, your feedback, your history, your outcomes. When you stop treating it like a search engine and start treating it like a system you're actively building.

She uses her own tax process as an example. What started as a one-time task to AI for it to  sort through her inbox for expenses quickly became a weekly scanning system, which became a monthly business review, which became a financial intelligence layer that now runs largely on its own. How did she do that? She fed it, iterated on it, and let it compound.

Most people never get there simply because no one told them that's how it works.

The 5 Things You Should Be Doing With AI Right Now

These are not hypothetical. They come directly from someone who has built the systems, shipped the products, and watched where people get stuck.

1. Stop forcing your old workflows onto new tools. The single biggest unlock, according to Tatsiana, happens when you stop asking, "How do I do what I've always done, but faster with AI?" and start asking: “If I were starting this from scratch, knowing what this technology can do, how would I design this process entirely differently?” That question, which is from first principles thinking, is where the real results live.

2. Give your AI feedback. Consistently. Your AI doesn't know if the meal plan worked. It doesn't know the email landed wrong. It doesn't know the report was off. If you don't tell it, you'll keep getting outputs calibrated to a version of you that doesn't exist. Feedback isn't extra credit. It's the mechanism that makes everything better over time. Think of it the way you would think about a new colleague: they can only improve if you tell them what's working and what isn't.

3. Protect your thinking. Don't outsource it. This is the counterintuitive one. AI can summarize. AI can draft. AI can compile and structure and synthesize. What it cannot do,  and what you must not let it replace, is your judgment and critical thinking. Your ability to ask the right question, spot the one nuance that changes everything, and evaluate whether an output is actually true and useful. "The best people you work with," Tatsiana says, "knew how to ask the right question and saw the one detail that actually mattered. That doesn't come from summaries or outsourcing." Use AI for speed. Keep your critical thinking for yourself.

4. Think about security before you give anything access. AI agents which are tools that can access your email, calendar, contacts, and files to act on your behalf, are genuinely powerful. They're also genuinely risky if you hand over access without thinking it through. Tatsiana, who has built these systems from the inside, is clear: the fear is warranted. Before connecting any agent to sensitive data, ask yourself where that data lives after you share it, how the company uses it, and what guardrails exist if the system decides to be "helpful" in a direction you didn't intend. Start small. Limit permissions. Build trust gradually.

5. Curate ruthlessly. You cannot keep up with everything. There is a new AI announcement every single week. New tools, new models, new capabilities, new companies. Trying to track all of it is a fast road to paralysis. Instead: find two or three voices you trust who have interesting, specific takes on a podcast, a newsletter, or a Substack and let them do the filtering for you. Then, experiment hands-on with the tools that surface from that curated input. Reading about AI and using AI are not the same activity.

"Will AI Take My Job?" — The Honest Answer

It's the question underneath all the other questions, and Tatsiana doesn't dodge it.

Her view: AI will not eliminate your job. It will change how you do it. And the people who thrive will not be the ones who resisted longest or the ones who automated everything fastest. They'll be the ones who figured out which parts of their work only they can do and leaned hard into those.

The exercise she recommends is to sit down and honestly map out everything you do in a given week. Then ask, which of these tasks could AI do, or is already doing? The answer to that question is usually more nuanced than people expect because most jobs contain far more judgment, context, and relationship work than the job description captures. That's the part that isn't going anywhere.

The part that is changing? The mechanics. The data pulls. The first drafts. The routine reporting. The scheduling. And if you're currently spending most of your time on mechanics, now is the time to move up.

What You'll Hear in the Full Episode

The blog gives you the framework. The conversation gives you the texture and the moments where two people actually working through these questions in real time get somewhere unexpected.

In this episode of Work Unscripted, there's more waiting for you:

• The agent access question answered honestly. Tatsiana worked inside OpenAI; she knows exactly what these systems can do when given access, and she doesn't sugarcoat the risk or the reward

• AI and the erosion of collaboration. She talks about the trend she says no one is talking about loudly enough, and why she considers it a genuine danger for organizations moving fast with AI.

• The "monoculture" problem. What happens to innovation, creativity, and problem-solving when everyone is building alone, prompting alone, and getting outputs from the same models.

• Whether business leaders should take AI courses. She has a specific, practical take on what actually works versus what just makes you feel like you're catching up.

• Her one-sentence billboard for every executive in America. Six words that cut through all of it to the truth no one is telling you.

The Bottom Line

Tatsiana's closing line in this conversation is worth repeating:

"You already have AI. Now you just need to use it."

Not better tools. Not more time. Not a course or a certification or permission from your organization. You have what you need. The question is whether you'll take the time and whether you’re willing to do something harder than prompting, which is actually rethinking how you work, what you feed back, and what you keep for yourself.

That's the shift. And it's available to you right now.

Listen to The AI Shift at Work: What Executives and Mid-Career Professionals Need to Do Now with Tatsiana Maskalevich.