Understand AI as a CEO
The other paths on this site teach you to install and run AI. This one teaches you to understand it, so the decisions you make about it are your own and not borrowed from a hype thread. It is eight reads, no setup, no terminal. By the end you will know what an AI agent actually is, when to use one and when not to, why the impressive demos fall apart in real work, why the output can be confidently wrong, which of the weekly releases deserve your attention, and what to actually do with all of it inside your company.
Do them in order. The order builds: define the thing, learn to aim it, learn where it breaks, learn to filter the noise, then apply it and roll it out to your team. Each piece ends with a concrete move. You do not need to do those moves to finish the path, but the ones that fit your week are where the reading turns into leverage.
This is the foundations track. It pairs with the hands-on paths rather than replacing them: read this to build the mental model, then run I'm new to AI · 10 hours that change everything to put your hands on the tools.
What you'll have when you're done
- A working definition of an AI agent, and a clear line between an agent and a chat assistant, so the word stops being marketing and starts being a decision.
- An honest model of where AI breaks: why long agent tasks degrade (it is the context, not the model) and why output can be fluent, confident, and wrong.
- A filter for the firehose of model releases, so you stop feeling behind every Monday and only act on what actually changes your business.
- A concrete menu of high-leverage uses you can start this week, plus a realistic picture of what a full AI stack replaces.
- A plan for the hardest part: getting your team to actually use any of it.
Unlock the path
Operators get the connective prose for every step · why it's here, what to look for, what you'll have when you finish. Plus everything else inside: the courses, the templates, the community, the workshops.
The path
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1What is an AI agent?Read it →
Start with the word everyone uses and few can define. An AI agent is a model put in a loop with tools: it decides, acts, looks at the result, and repeats until the job is done. That is the whole idea, and it is the difference between a chatbot that talks and a system that does. Read this slowly. Everything after it assumes you hold this distinction.
After this you will be able to tell, in any pitch or product, whether you are looking at an agent or a glorified chat box.
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2AI agents vs AI assistants: which one for which job?Read it →
Now that you know what an agent is, learn when you actually want one. An assistant keeps you in the loop and waits for your next instruction. An agent takes a goal and runs. The real question is never which is better, it is which fits the job in front of you, and the cost of getting that wrong is either wasted autonomy or wasted attention. This piece gives you the rule.
After this you will know which of your own tasks belong to an assistant and which are worth handing to an agent.
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3Why most AI agents fall apart in real work (and how to fix it)Read it →
The honest counterweight. Agents look magical in a two-minute demo and then come apart on real, multi-step work, and the instinct is to wait for a smarter model. That is the wrong fix. The failure is almost always context, not intelligence. This read shows you why, and what setting an agent up to succeed actually looks like.
After this you will stop blaming the model and start fixing the setup, which is the part you control.
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4Why AI sounds confident when it's wrong (and how to catch it)Read it →
The other failure mode, and the more dangerous one because it hides. AI predicts plausible text, not verified truth, so it can hand you a fluent, well-formatted, completely wrong answer in the same confident voice it uses when it is right. For a busy CEO that confidence is the trap. This is hallucination as a business risk, plus the habits that catch it before it ships.
After this you will know exactly where you can trust AI output and where you have to verify it, and you will have a rule you can hand your team.
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5Which AI releases actually matter, and which can I ignore?Read it →
Step back from the tools to the noise around them. The labs ship something new almost every week, each launch dressed up as a turning point, and the result is a low hum of falling behind. You are not behind, you are running the wrong filter. This piece gives you a three-signal test for which releases actually deserve a CEO's attention and which you can ignore without cost.
After this you will be able to skim the next launch in ten seconds and know whether it changes anything for you.
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610 ways a CEO can put AI to work this weekRead it →
Now turn understanding into motion. This is the concrete menu: ten specific, high-leverage uses you can start in the next five business days, ordered from the ones that cost nothing to try to the one with the highest ceiling. Pick two or three that map to your actual week.
After this you will have a short list of things to actually do, not just things you now understand.
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7How I replaced a $10K/month agency with an AI stackRead it →
See the pieces add up to something. This is a representative teardown of replacing a five-figure monthly agency with an AI stack: what it does, what it costs, what it measurably changes, and, just as important, the honest list of what AI cannot replace. Read it as proof of concept and as a realistic expectation-setter, not a promise.
After this you will have a picture of what a full stack looks like, and where the human still has to sit.
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8How to get your team to actually use AIRead it →
The last and hardest mile. You can understand all of this and still watch the licenses you bought sit unused, because access is not adoption. This read is the adoption playbook: how to get past the announcement and make AI a habit your team actually reaches for, including what to do about the people who quietly refuse.
After this you will have a plan to move AI from your own screen into how your company works, which is where the leverage finally compounds.
What's next
You now have the model. The next move is to put your hands on the tools. If you have never seriously used Claude or GPT, run I'm new to AI · 10 hours that change everything for a structured first install. If you already use a chat tool and want to graduate to workflows that compound, try I have ChatGPT, I want real leverage. When you are ready to commit, 30 Days to Real AI Leverage (Course #1) takes you from understanding to an operator-grade install with workflows that save you hours every week.