From: Marlon Sanders
RE: The almost unbelievable new way I am creating products with AI
I know it sounds incredible.
But it is true.
You can now create amazing, valuable, professional-looking, sellable information products at light speed with AI...
Simply by talking into your phone.
I have already been creating sales letters this way.
And that alone is remarkable.
But this is a whole new level.
As I write this, I am lying in bed and talking into my phone.
I recently created an entire information product by talking through part of it while lying in bed and another part while sitting at my kitchen table.
Not merely an outline.
Not a rough pile of notes.
A real, organized, attractive product that contains useful information and is designed to be sold.
And I want to show you how I do it.
There Is A Huge Difference Between Making AI Produce Words...
And Using AI To Create A Product People Will Actually Buy.
That difference is where almost everyone gets tripped up.
Because this is not quite as simple as it sounds.
You cannot merely talk for a few minutes, accept whatever AI hands you, and expect buyers to line up.
A sellable product has to begin with the right kind of idea.
It has to feel different enough to get attention.
It has to be organized correctly, provide real value, look complete, and leave the buyer glad they bought it.
Miss one or two of those pieces and you may end up with a lot of AI-generated words...
But not much of a product.
Today, almost anyone can ask AI to write a report. The problem is, most of what it produces is what people now call “AI slop.” Very few people know how to turn AI into a product-development partner instead of an AI slop generator. That is exactly what I will show you how to do.
The Exciting Part Is What Becomes Possible...
- You can capture ideas the moment they occur instead of waiting until you have the time and energy to sit at a computer.
- You can put more of yourself into the product—your experience, opinions, stories, illustrations, and hard-won lessons—without typing every word.
- You can use AI to move dramatically faster while still creating something useful, substantial, attractive, and worthy of being sold.
I have created dozens and dozens of products over the years.
I know the difference between information that merely fills pages and a product built to satisfy a buyer.
Now I have combined those years of product-creation experience with the newest AI capabilities and a method that lets me work in ways that would have sounded impossible not long ago.
I am going to reveal the tricks, the shortcuts, the tools, the decisions, and the little details that make the difference.
Not just how to make AI generate something...
But how to turn a raw opportunity into a polished product with a real chance to sell.
This Is Where The Real Method Begins
Five Bottlenecks Stand Between A Good Idea And A Finished AI-Created Product
Once I organized the complete process, I realized that nearly every delay, weak product, and unfinished draft could be traced back to five distinct bottlenecks.
Remove those bottlenecks in the right order and product creation can move astonishingly fast.
Find the complaints people already repeat—then uncover the deeper need hiding underneath them.
Most weak products begin with the creator asking, “What could I make?” The Lightspeed method begins with a better question: “What are people already trying—and failing—to solve?”
At this stage you are not asking AI to invent a clever idea. You are using it as a tireless research assistant that can sort patterns, group complaints, and help you notice the gaps hiding in plain sight.
- The “first-answer trap” that makes AI research look more useful than it really is—and the simple follow-up sequence that pushes past the same obvious complaints your competitors already know.
- How to separate the surface complaint from the real buying motive underneath it, so you do not build a product around what people say while missing what they are actually trying to gain, avoid, protect, or prove.
- The four “easy-gap” signals that deserve special attention in almost any market—especially when the existing solution is too slow, too expensive, too complicated, or depends on a skill the buyer does not have.
- A quick way to make AI show its work before you trust the pattern, so you are less likely to build a product around a confident-sounding answer that has no real market weight behind it.
- Why broad desires such as “make money,” “get traffic,” or “save time” are not product ideas—plus the narrowing question that turns a vague category into a complaint specific enough to support a headline.
- How to make the competition check useful without drowning in competitor research, including what to look for when current products technically address the problem but still leave buyers frustrated.
- The stopping point that keeps research from becoming productive procrastination, so you know when you have enough signal to move into product concepts instead of collecting complaints forever.
What stays semi-blind until you are inside: the exact complaint-mining prompt sequence, the deeper-need grouping instruction, and the follow-up wording that forces AI to go narrower instead of merely giving you “ten more ideas.”
Turn raw market pain into an offer that feels different—not merely another version of what buyers have already seen.
Research gives you ingredients. It does not automatically give you a product people can understand, remember, and want.
This stage shows you how to convert complaint themes into product concepts and then choose one clear positioning lens. That keeps the promise sharp and prevents the mushy “does everything for everyone” offer that AI loves to produce.
- The 15-concept generation prompt that makes AI give you more than a title—including the audience, core promise, delivery idea, and the specific reason AI makes the product faster or easier to create now.
- The “short-report filter” that quickly identifies which ideas can become a useful 10-to-30-page product instead of quietly expanding into a giant course, complicated software project, or six-month production commitment.
- Four distinct product lenses you can use to create a sharper offer: owning one important attribute, winning on total value, serving a genuinely neglected need, or removing unnecessary steps to deliver the result faster.
- Why trying to use all four lenses at once weakens the offer—and the practical question that tells you which lens the market research is already pointing toward.
- The difference between “better” positioning and “different” positioning, including how to ask AI for an angle buyers can recognize without requiring a paragraph of explanation.
- A title-development sequence that starts with the finished outline rather than a blank page, then divides title ideas between result-driven hooks and mechanism-driven hooks before applying a simple clarity test.
- How to create curiosity without sacrificing comprehension, so the buyer wonders how the method works but never wonders what the product actually helps them do.
- The beginner-body/advanced-callout structure that lets one product serve mixed skill levels without making beginners feel lost or experienced buyers feel they paid for recycled basics.
The hidden advantage: when your angle is chosen correctly, the title, sales bullets, examples, bonuses, and upsell ideas become easier because they are all being pulled in the same direction.
3
Filter For Demand And Profit
Stop falling in love with the idea before the market has had a chance to vote.
An idea can sound wonderful in your head and still produce silence when you offer it for sale.
The goal here is not academic certainty. It is a fast decision aid that helps you avoid spending a week building the idea your audience ranks last.
- The 12-Product Forced-Choice Survey that gives you a clearer demand signal than “Would you buy this?”—because polite yes/no answers disappear when people must actually choose between competing offers.
- How to keep the survey short enough that real buyers will complete it, while still learning purchase intent, desire strength, perceived uniqueness, price expectations, and the obstacle that has stopped them so far.
- Why a small group of engaged respondents can be more predictive than a large group of casual opinion-givers—and what you are really looking for when the goal is a quick product decision rather than a scientific paper.
- The question that often hands you future sales bullets, objection answers, and even guarantee language before the product has been written.
- A simple 50/50 ranking method that balances audience demand against business reality, including likely price, production difficulty, delivery cost, and the strength of the backend path.
- Why the survey winner is not automatically the most profitable idea—especially when the second-place concept creates two or three logical upsells while the first-place idea leads nowhere.
- The hardbound-notebook test Marlon uses to add human judgment back into the numbers, ranking ideas by speed, ease, and estimated profit without pretending the process is more scientific than it is.
- The commit-and-move rule that prevents validation from turning into another endless research cycle, so you choose a realistic winner and begin building while the market signal is still fresh.
You are not trying to eliminate risk. You are trying to replace blind enthusiasm with enough evidence to make a faster, better-informed decision.
4
Run The AI Assembly Line
Give AI one controlled production job at a time—so you get a coherent product instead of 40 pages of polished repetition.
This is where most people either save enormous time or create an enormous mess.
They ask AI to “write the whole ebook,” receive a generic draft, and then spend longer repairing it than they would have spent writing it correctly in stages.
- The five-column legal-pad method that gives AI a human-built skeleton to improve, so the structure begins with your judgment instead of whatever outline pattern the model happens to default to.
- Why the outline should come before the final title—and how the finished content map often reveals a stronger promise or mechanism than you could have invented cold.
- The section-by-section ghostwriter loop that protects focus and consistency, including how to allocate pages, define the reader, request an example, and stop one section from repeating material that belongs somewhere else.
- How to correct course on page five instead of discovering the problem on page forty, using quick review prompts that tighten depth, tone, examples, and usefulness before the mistake spreads.
- Two content frameworks that keep AI from merely “explaining information”: one built around explanation, application, and illustration; the other built around tension, problem, solution, and immediate action.
- How to choose the framework section by section, rather than forcing every part of the product into one rigid template whether it fits or not.
- The voice-preservation step that lets you dictate rough thinking, stories, and opinions, then use AI to organize and polish them without sanding away the personality that makes the product yours.
- A practical way to write for beginners while still rewarding intermediate and advanced readers, using strategically placed pro tips, mistakes, warnings, and nuance boxes instead of making the main lesson harder to follow.
- The “draft, inspect, push back” habit that separates useful AI collaboration from one-click disappointment—because the first answer is raw material, not the finished product.
The real speed gain is not one giant prompt. It is a production line where every prompt has one job, every output has a review point, and every stage hands clean material to the next stage.
5
Add Eye Candy And The Profit Path
Make the product easier to consume, easier to deliver, and naturally connected to the next thing your buyer needs.
A useful product can still feel cheap when it looks like an unedited transcript. And a good front-end offer can still underperform when it ends without showing the buyer what to do next.
The final stage finishes the product as a buyer experience—and then looks one step beyond it.
- The specific “eye-candy” formatting request that produces more than random bold type, telling AI exactly where to add punchy subheads, pull out lists, and create tip, warning, or takeaway boxes.
- How to make the product skimmable without making it shallow, so a reader can scan the subheads and understand the path, then slow down wherever the detail matters.
- The visual hierarchy checklist that keeps a report from looking assembled, including paragraph length, repeated design cues, brand colors, callout purpose, and the disciplined use of emphasis.
- Why the simplest delivery method is often the most profitable for a low-priced front-end product—and how reducing login friction can matter more than trying to lock down every page against piracy.
- The “next problem” question that reveals stronger upsells than simply adding more information, because the best backend offer solves the bottleneck the buyer meets after using the front-end.
- How to make the upsell feel like help instead of homework, leaning toward finished assets, templates, tools, customization, implementation, depth, or scale rather than explaining the same basics again.
- The instruction that stops AI from writing an upsell for a beginner who has not bought the first product, so the next offer begins at the correct awareness and skill level.
- How to map the product line while the front-end is still fresh in your mind, giving you a clearer path from the impulse purchase to the higher-value outcome before launch-day pressure takes over.
- A quick-reference sequence that puts the complete machine on one page, so you can run the process again without rereading the entire report every time you create something new.
This is where a report becomes a system. The buyer receives information they can use, a format they can navigate, and a logical next step that can increase the value of the customer relationship.
You can continue watching other people create with AI while your own best ideas remain trapped in notes, half-finished chats, and unrecorded thoughts.
Or you can discover the complete method Marlon is using to turn spoken ideas and AI into finished products at remarkable speed.
The advantage is not simply that you finish one report faster.
The advantage is that the second product becomes easier than the first. Then the third becomes easier than the second. You stop rebuilding the process every time.
That is how you create at lightspeed without turning your products into generic AI sludge.
Best wishes,
Marlon
P.S. The five stages are designed to remove the five places product creators most often stall: finding the opportunity, choosing the angle, validating the idea, producing the content, and finishing the product with a profitable next step.
P.P.S. You do not have to use every prompt exactly as written. The report shows you how to treat each one as a starting point, inspect the output, and push AI deeper until it gives you material worth using.
