Mayson has no prompt guide because you don’t need one to use it. In my experience, it plans the app from a plain-language description of your idea. It works out the pages, logins, data and payments before it builds anything. The skill that matters is describing what you want clearly, the way you’d explain it to a friend over coffee. There’s no special syntax to memorise. I went looking for the guide on my first day anyway, and what I found instead changed how I build.
When I signed up, I did what any consultant would do and looked for the framework. Every tool I’d tried before had a page somewhere called “how to prompt” or “best practices”. I assumed I’d need to study it before writing a single line. I searched the site, then the help pages, then searched again in case I’d missed it. There was nothing to find. So I opened my Google Sheets spec, described the app the way it was written there, and pressed go.
Why most AI app builders publish a prompt guide
The AI app builders I’d used before all published some version of a prompting guide. The advice tends to look similar across them:
Be specific about layout.
Name the components you want.
Break big requests into small steps.
Tell the tool what not to change.
That’s sensible advice, and it exists for a reason. Many of these tools build directly from the words you type, so your prompt is the plan. If the prompt leaves out the login screen, there’s no login screen. If it describes a button vaguely, you get a vague button. The guide teaches you to do the planning inside the prompt, because nothing else in the process is doing it.
For a developer, that’s fine. They already think in components and steps. For someone like me, it meant learning a second skill before I could use the first one. I knew my business. I didn’t know how to translate it into the shape the tool wanted.
The casino problem with prompting
When the prompt is the plan, building starts to feel like a slot machine. You write something, pull the lever and see what comes out. Sometimes it’s close to what you meant. Often it’s close but wrong in one important place. You rewrite the prompt, pull again, and something that was working before has quietly changed.
I spent one evening on a previous tool regenerating the same signup page again and again. Each version fixed one thing I’d complained about and broke another. By the end, I had a long document of prompts that had worked slightly better than others. I had no idea why any of them worked. That’s the casino problem. The occasional win keeps you playing, and you never learn the rules, because the rules keep shifting.
A prompt guide tries to fix this by teaching you to play the machine better. It helps a bit. You’re still the only one doing the planning.
What Mayson does instead: it plans before it builds
What I found Mayson did differently was the step between my description and the code. As of November 2026, when I describe an app, Mayson first works out what the app needs. That means the pages, who can log in and what each type of user can see, what data has to be stored, and where money changes hands. Only then does it build.
I can only describe what I observed from the outside. On why BackStract built it this way.
My consulting brain understood this immediately. On every engagement I’ve worked, we agreed the scope before anyone built a model. Most AI building tools I’d tried skipped the scoping conversation and went straight to the deliverable. Mayson does the scoping first. That’s why there’s nothing for a prompt guide to teach: the planning has moved out of your prompt and into the product.
What helps Mayson build what you meant
Without a prompt guide, the quality of your description decides the quality of the plan. What helps most is the habit I had before any AI tool existed: the spreadsheet stage.
My Google Sheets spec has three columns that matter here. They translate directly into a better description.
Who it’s for. Name each type of person who uses the app. “Parents” and “the tutor” are two different users with two different views. If you only describe one, you’ll get an app built for one.
What they do. List the actions in ordinary verbs: book, cancel, pay, upload, approve. Each verb tends to become something the app has to support. Missing verbs become missing features.
What they need to see. Describe what each person looks at when they open the app. The tutor needs today’s bookings. The parent needs their child’s next slot. This column is where most of my early descriptions were thinnest. It’s also where the clearest improvements came from.
Compare that with my first attempt at building anything. I spent ₹12,000 on a Fiverr developer after describing my idea in a couple of messages, and received a Figma mockup before he disappeared. The developer and the AI have the same need: they can only build what you’ve described.
What this means if you’re not technical
The hard part of building has moved to the part you’re already good at. You know who your customers are, what they’re trying to do and what they’d pay for. That knowledge used to be stuck on the wrong side of a translation problem. You either learned to speak the developer’s language or paid someone who did. Now the description in your own words is the starting point.
You still have to think, though. A muddled idea described clearly produces a muddled app, only faster. The founders I’ve seen struggle most are those who haven’t decided what the app is for, and no tool fixes that, with or without a guide.
Testing stays your job too. Once the app exists, log in as each type of user and try to break it. The planning step gets the structure right far more often than a raw prompt did for me. You should still click through your own app before a customer does.
Where Mayson still gets it wrong
Planning from plain language has a weak spot: whatever you leave out, the plan has to guess. Mayson’s guesses have usually been sensible defaults. A sensible default is still a decision you didn’t make.
In my experience, Mayson handles common structures well: users, logins, records and payments. It’s weaker where your business has rules that aren’t obvious from the description, like pricing that changes by customer type or a cancellation policy with exceptions. Those rules have to be spelled out, and they’re where a misbuild is most likely. If your app’s value sits in complicated business logic, expect to describe that logic in more detail and to check it carefully.
You don’t need to study anything before your first build. Open a spreadsheet, fill in who it’s for, what they do and what they need to see, and turn those rows into a few plain sentences. Start with the free tier: 10 credits, no credit card required. build your first app
Frequently asked questions
Do I need to learn prompt engineering to use Mayson?
What should I write in my first prompt?
What happens if Mayson builds the wrong thing?
Can I change my app after it’s built?
Do I own the code Mayson writes?
Abhishek is a strategy consultant and non-technical founder based in Delhi NCR. He studied commerce in Delhi, worked at a Big Four firm in Gurgaon and completed an MBA in Australia. After two years of false starts with freelancers and no-code tools, he shipped a small SaaS product with an AI app builder, which now runs alongside his consulting work. He writes about building products without a technical co-founder.
