I have had this exact conversation hundreds of times.
Someone pulls me aside after a keynote, or sends me a DM, or says it quietly in a leadership meeting:
"Monica, I tried AI. It just doesn't work for what I do."
And every single time, I ask the same follow-up question.
"Which model did you use?"
Nine times out of ten, the answer is some version of: "I don't know, the free one?" Or the one their company rolled out two years ago. Or something they tested once in 2023 and never went back to.
That is the problem. And it is a bigger problem than most leaders realize.
Because the difference between a free-tier AI model and the best model available today is not a small upgrade. It is the difference between a paper map and a GPS that reroutes in real time. Between an intern on their first day and a senior strategist who already knows your business. They are not even in the same category.
I have been watching people dismiss AI based on one outdated experience for years. And lately, as I have gone deeper into my own Claude setup, I keep thinking: most people have not actually tried AI yet. They have tried the free version.
There is a meaningful difference. Let me show you what it looks like.
THIS WEEK'S INSIGHTS
The most expensive misconception in business right now is making strategy, hiring, or investment decisions based on what you think AI cannot do, when your last real test was a weak model in a weak year.
1. Model quality is not a minor detail. It is the whole game. Assuming all AI tools perform the same is like assuming all doctors give the same diagnosis. The frontier models available today are handling things that would have seemed impossible two years ago: building production-ready code, flagging six-figure financial errors that trained professionals walked right past, and running multi-step workflows that used to require entire departments. If your last test was on a free or legacy tool, you have not seen what this technology actually does.
2. A single bad test is not a verdict. It is a data point from a different era. When a leader closes the door on an entire category because of one underwhelming interaction, that is not prudence. That is a blind spot with compounding consequences. The AI landscape in 2026 looks nothing like the one you may have walked away from.
3. Outdated assumptions have downstream consequences. When your mental model of AI is three years behind, every decision that flows from it is built on a cracked foundation. Who you hire. How you structure your team. What you invest in. Which vendors you trust. The tech question becomes a strategy question very quickly.
The question is not whether AI works. The question is whether you have tested the version that actually does.
TRENDS
When I look at where the most effective AI users are right now, one pattern is unmistakable. The gap is not between people who know better prompts and people who don't. The gap is between people who have built a system and people who are still improvising.
The shift from "asking AI" to "working with AI." The professionals pulling ahead are not writing longer prompts. They are building context, rules, and structure around their models so every session starts smarter than the last.
Setup is the new skill. The top 1% of Claude users are not better at prompting. They are better at configuration. They have taught their model who they are, how they think, and what they need before a single task begins.
Systems compound. Improvisation doesn't. Every time you start a session from scratch, you are leaving leverage on the table. Professionals who build a reusable AI setup are creating an advantage that grows over time. The ones who keep winging it will always be catching up.
The secret was never the prompt. It was always the setup.
3 MYTHS TO REFRAME
I hear these in boardrooms, breakout sessions, and DMs every single week. They are the beliefs keeping smart, capable professionals from accessing a tool that could genuinely change how they work.
Myth #1: "I tried AI and it was bad, so AI is not ready."
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Why we believe it: One frustrating experience becomes the whole story. We tested it, it underwhelmed us, and we moved on. That feels like due diligence.
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Reframe: You did not test AI. You tested one model, probably on a free tier, probably in a year when the technology was genuinely less capable. That is like tasting a bad cup of coffee and swearing off coffee forever. The category moved. The verdict should not be permanent.
Myth #2: "If I just learn the right prompt, AI will work for me."
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Why we believe it: Every LinkedIn post promises a magic prompt. It feels like the key is somewhere out there.
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Reframe: Prompting is the least powerful lever. The real power is in what you set up before you ever type a word. Context files. Rules. Model selection. When Claude already knows who you are and how you think, the prompt barely matters.
Myth #3: "AI should just work out of the box for serious work."
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Why we believe it: Every tool promises to be plug-and-play. We expect AI to be the same.
- Reframe: The best collaborators in your career did not show up on day one already knowing your communication style, your priorities, and your standards. You built that relationship over time. Claude is the same. Teach it. Configure it. Then watch what it can do.
TOOLS
I want to walk you through exactly how I use Claude. Not the theory. The actual setup, step by step.
1. Start with the desktop app, not the browser. There is a meaningful difference. Download it at claude.ai and open it from your computer.
2. Choose "Cowork" over "Chat." Most people never find this mode. Cowork lets Claude pull directly from a folder on your computer, which means it arrives to every session already knowing your context. No more re-explaining who you are.
3. Build a simple context folder with three files:
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about-me: your role, your background, what you are working on right now
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my-voice: how you write, your tone, what to avoid, what sounds like you
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my-rules: how you want Claude to behave, your preferences, your non-negotiables
A paragraph each is enough. You can refine them over time.
4. Adjust two settings before you begin any task:
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Extended Thinking — this tells Claude to reason through a problem before responding, rather than just reacting to your words.
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Opus 4.6 — the model that handles complex, multi-step work best.
5. Replace your prompt with this:
"I want to [TASK]. Read all files first. Ask me questions using AskUserQuestion before you execute. Do not guess."
What happens next is different from anything most people have experienced with AI. Claude reads your files, asks targeted clarifying questions, and then executes with your actual context in mind. It is not guessing. It is collaborating.
TRY IT THIS WEEK (Micro-Actions)
These are designed to take you from knowing to doing. Share these with the leaders in your circle.
1. Run the same task twice. Pick something you do regularly: drafting an email, summarizing a report, prepping for a meeting. Do it in the free model you have been using. Then do it in Claude with the Cowork setup above. Compare the outputs. That comparison will tell you everything.
2. Create your three files. Open a folder on your desktop. Write your about-me, my-voice, and my-rules files. Do not overthink them. A paragraph each is enough to start. You can refine them as you go.
3. Force Claude to ask before it acts. Use the instructions above on one real work task this week. Notice what happens when Claude asks you clarifying questions instead of guessing. That is the version of AI most people have never experienced.
Closing Thought
Most of the smart, capable professionals I know are not behind on AI. They are just working with the wrong version.
Do not let a stale experience write the story of what is possible for you now.
No te quedes con la primera impresión. (Do not stay stuck on the first impression.)
The tool changed. It is time to test it again.
♻️ Share this with a leader who needs to see this.
Hasta la próxima, ¡Abrazos! 💃🏻
Monica Marquez
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