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Why so many prompts seem not to work
Many people open ChatGPT, paste a prompt they found online, and get an answer that looks fine, but isn’t really usable.
It lacks precision, consistency, and reliability.
This doesn’t happen because the LLM “isn’t good enough.”
It happens because there’s still very little clarity about what a prompt can realistically do, especially when it comes to practical, repeatable tasks.
A prompt is not software
A Large Language Model - whether it’s ChatGPT, Claude, Gemini, LLaMA, or others - always works within a limited context window.
It can only reason about what it sees at that moment, without any persistent structure.
If you ask it:
to write a formal meeting report starting from messy notes
to merge information from multiple files into a clean table
to perform structured data entry from different text sources
to extract precise information from documents that are similar but not identical
a single prompt - no matter how “well written” - is not enough.
The problem with one-shot prompts
Most prompts you find online assume that:
one request → one final, ready-to-use output
In real work, tasks usually look like this:
first you read
then you select
then you normalize
then you verify
then you reformat
An LLM can do all of this - but not all at once.
When you try to compress everything into a single prompt:
you lose control
errors increase
outputs become inconsistent
This is not a limitation of intelligence.
It’s a process problem.
Why documents and intermediate steps matter
Practical use cases work when the LLM:
operates on real documents you upload
receives clear instructions on what to do before and after
separates analysis, transformation, and final output
This is how you can reliably:
consolidate data coming from multiple files
transform similar texts into a unified structure
produce repeatable, consistent outputs
All of this requires multiple calls to the model, not just one.
External tools: what you’re really paying for
Many AI tools exist specifically to handle these limitations.
One thing is important to understand:
the underlying engine is always an LLM
(ChatGPT, Claude, Gemini, LLaMA, etc.)
What you’re paying for with external tools is not “better AI,” but:
multiple prompts running behind the scenes
persistent rules
databases
step orchestration
convenient interfaces
These tools can be useful.
But they are often expensive - and not always necessary for solo/ small teams or specific tasks.
The alternative: manual prompt systems
There is a less visible, but very effective approach.
Instead of using:
one single prompt
or a complex external tool
you build:
a sequence of 2–3 prompts or more
each with a precise role
passing inputs and outputs between them
effectively replicating what external tools do
The engine is the same.
What changes is how you use it.
This approach is more manual, but:
fully controllable
adaptable
no additional subscriptions required
The philosophy behind this site
This site collects only prompt systems I actually use - or that I build for real-world use cases involving freelancers and solopreneurs.
You won’t find:
endless prompt collections
generic prompts
one-line “tricks”
Because in practice, you don’t need ten thousand prompts.
You need a few - built properly:
designed for a specific task
tested on real inputs
refined over time
What to expect (and why it’s valuable)
Each prompt system you find here typically requires:
gathering requirements
designing the workflow
writing the prompts
testing them on real cases
refining edge cases
This easily amounts to 10 hours of work per system.
If you’re a developer, you could build these yourself.
If you’re not, you probably wouldn’t know where to start.
In both cases, using these systems lets you save that time and rely on something that has already been thought through, tested, and refined.
How to use this site
Browse the prompt library and see if you find something that fits what you need.
If you do, you have two options.
Option 1: One-month access
If you need a prompt for a specific task, you can subscribe for one month.
This gives you full access to the prompt you’re looking for - and, at the same time, to all the other prompt systems available on the site.
You can take what you need and follow the included instructions to customize it if needed.
Option 2: Annual access
If you’re interested in more than a one-off solution, the annual plan is the better option. It costs only slightly more, and it gives you:
access to all existing prompt systems
ongoing refinement of prompts as LLMs evolve
updates when models can do more, or when workflows can be improved
the release of a couple of new, well-built prompt systems every month
There won’t be thousands of prompts.
Because you don’t need them.
You need a small number of systems that actually simplify your work.
Stay updated
Regardless of whether you choose a monthly or annual plan,
if you want to stay informed about:
new prompt systems as they are released
updates or refinements to existing prompts
general changes and improvements across the library