Documentation hinges on context, and where it matters the most is with the environment. The wrong operating system may be right or wrong for a given instruction, without any indication to the reader for which case to expect the instruction to work. For example, if the instruction were to be used on another operating system, the instruction may not work and thus cause the program to malfunction. This concept is known as “fragile documentation.” This example demonstrates the importance of environment when providing documentation.
That is why version numbers, prerequisites and tested environments belong at the top of the page rather than in a footnote nobody scrolls to.
The goal of the testing software was usually to help the user run system level commands on machines that actually mattered to the test user. Users would run system commands that they didn’t even understand. Ambiguity is expensive. The command “Update the config file” means nothing to the test user. They have to guess which config file and where that file may even be. Naming the path, the flag and the expected output turns an anxious task into an easily checked task.
Generated install guides appear to include flags. The syntax is astute, but the flag does not exist in your edition, and the user loses an afternoon before reasoning your software is faulty. Nothing in a model’s training informs it which of two similar command line options your build, in fact, accepts.
The author installs it on a blank machine, following the instructions if any exist, at which point he/she records each instance of a discrepancy. The first painful installation yields far more interview data compared to a week of interviews, and is the only reliable method of capturing the step of the process that one of your engineers stopped noticing a while ago.
Deployment docs aren’t meant for users or visitors to follow your software instructions. Our deployment documents include all important information next to an open console. To help with UI text searchability, we copy and paste error messages. Every deployed version includes what version it was tested against.
One rate, whatever the format: $10 per 100 words. You are paying for the writer’s time and judgement, so the price scales with the words rather than with a package tier.
| Typical software documentation | Words | Writing | Fee (1%) | You pay |
|---|---|---|---|---|
| Single reference | 800 | $80 | $0.80 | $80.80 |
| Standard doc set | 2,000 | $200 | $2 | $202 |
| Full documentation | 5,000 | $500 | $5 | $505 |
The writer receives 100% of the writing price. Our 1% fee is added on top of it, and 0.5% is donated to tree planting. Full pricing breakdown.
Ask on the contact page and a person will answer, usually the same working day. For a live order, reply to your confirmation email and it reaches whoever is handling it.
Ask on the contact page and a person will answer, usually the same working day. For a live order, reply to your confirmation email and it reaches whoever is handling it.
We trace your steps in a clean environment when we draft, and we ask one of your engineers to do the same before we publish. Two people following a certain set of steps usually helps to uncover any issues that may occur. Someone writing the steps from memory usually misses a lot of important steps.
Completely. Copyright transfers to you on delivery, with no attribution requirement and no licence back to us. Nothing written for you is resold, repurposed or republished.
Reviews from completed, paid orders in this category.
Our release notes went unread, but they serve the purpose of listing what breaks and what doesn’t when considering whether to upgrade. Two customers actually took the time to send thank yous in the same week, something that had never happened before.
Mostly excellent. Your improvements to the auth section are better than what our engineers wrote. Your pagination endpoints, however, were explained in the spec according to how they behave rather than how they are, which required two revisions. Our spec is incorrect in that area as well.
Our changelog has little snippets about why the change happened, and that seems to have solved the issue of support receiving the ‘what does this actually do?’ tickets. I honestly never thought that release notes would give us the answer for that.
We do not ask you to take the no-AI promise on trust. Each draft is run through these platforms and the reports are attached to your delivery email.
Originality.aiAI detection + plagiarism
GPTZeroAI detection
TurnitinAI detection + similarity
CopyleaksAI detection + plagiarism
Winston AIAI detection
ZeroGPTAI detection
SaplingAI detection
Content at ScaleAI detection
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$10 per 100 words · all of it to the writer · 0.5% to trees