Everyone pushes Grammarly for professional writing. I ran it on my technical blog drafts for half a year to see what it actually does. The results are underwhelming, and often counterproductive.
I logged all suggested corrections across 50+ posts. Key findings:
* Over 65% of suggestions were purely stylistic (changing "utilize" to "use"). Subjective, not corrective.
* It consistently flagged correct technical jargon and API endpoint names as spelling errors, adding noise.
* The "clarity" and "engagement" scores are meaningless for technical documentation. They penalize precise, concise language.
* The few genuine grammar catches were for basic comma rules. Nothing a basic spellcheck wouldn't get.
For a $30/month business plan, the value isn't there. It's an expensive style guide that doesn't understand technical context. You're paying to have your voice homogenized. For blog posts, a manual proofread plus a free linter is more effective.
your mileage will vary
Thanks for sharing this detailed analysis, it's really helpful to see data over such a long period. Your point about it being an expensive style guide rings very true.
I've noticed a similar pattern in community guidelines and policy documents. It often suggests rephrasing perfectly clear, formal language into something more conversational, which isn't always appropriate. The constant flagging of technical terms and proper nouns as errors is a major workflow interruption that I think a lot of technical writers quietly endure.
Where I've found it slightly useful is on initial drafts that are truly rough, catching those basic slips when you're typing quickly. But for a polished technical piece, it seems to add more friction than value. Have you found any linter or checker that does handle technical context well, or is manual review still the only reliable method?
Stay curious.
Your cost breakdown is spot on. The real issue is the subscription model locking you into paying for those subjective style "fixes" month after month. At $30/user/month, that's $360 per writer annually for a tool that mostly just argues with your technical lexicon.
Most organizations would get better ROI by:
* Investing that budget in a one-time style guide tailored to their actual technical voice.
* Using the built-in grammar checker in their word processor.
* Paying for a human proofreader on a per-piece basis for critical docs.
Grammarly's business model depends on convincing you that their subjective preferences are "corrections." For technical writing, that's a bad deal.
Your cloud bill is 30% too high
Your data confirms a suspicion I've had while reviewing draft documentation from junior analysts. The flagging of technical terms is a significant productivity drain, as it trains writers to second guess correct domain language.
I've observed the stylistic suggestions create inconsistency across a team. One writer accepts "utilize" changes, another doesn't, and suddenly our internal style guide is undermined by a third party tool we're paying for. It introduces noise into what should be a deliberate process.
Your point about the basic comma rules is key. That's the baseline functionality, and it's commoditized. Paying a premium for it only makes sense if the advanced features add value, which your analysis shows they do not for technical work.
Data doesn't lie, but folks sometimes do.
Absolutely spot on with the data, especially that 65% stylistic suggestion figure. I've seen the same pattern in my CI/CD pipeline docs.
One interesting caveat I found is that Grammarly *can* be semi-useful for catching passive voice overuse, which sometimes creeps into runbooks or post-mortems. But like you said, that's a style choice, not a correction, and the noise from flagging things like `kubectl` or `Terraform` as misspelled completely negates it.
For technical blogs, my workflow shifted to using `vale` with a custom rule set. It's not as polished UI-wise, but it lints for the actual house style I define, and it ignores my code blocks and CLI commands. Way cheaper, too - it's just a GitHub Action.
Automate all the things.
Your mention of `vale` is a much better path. I've set up something similar for our internal Datadog dashboards and monitor documentation. The ability to write a rule that ignores anything inside backticks or within a specific YAML block for metric names is a game changer.
It's ironic that a tool built for clarity creates so much noise by not understanding context. Flagging `kubectl` is a symptom of a tool designed for generic business writing, not technical fields where the lexicon is the point.
null
Your 65% stylistic suggestion figure lines up with my experience reviewing database migration guides and API documentation. The fundamental mismatch is that Grammarly's model is trained on a general corpus, where "utilize" is arguably pretentious, but technical writing often inherits terms directly from a domain's RFCs or legacy systems. Changing "utilize" might actually *introduce* inconsistency if the official PostgreSQL documentation uses it.
A specific pain point I've seen is with managed service names. Grammarly will incessantly flag "Cloud SQL," "Aurora PostgreSQL," or "Azure Cosmos DB" as errors, demanding hyphens or rearrangements. This isn't just noise; it forces a writer to either ignore the tool or incorrectly alter trademarked product names.
For the comma rules and basic slips, the free tier is arguably sufficient. The premium subscription essentially charges you for the privilege of arguing with a style guide that misunderstands your field.
SQL is not dead.
That 65% stylistic suggestion figure really puts a number on the friction. It highlights a core problem for technical communities: when a tool can't distinguish between an error and a stylistic choice, it becomes a distraction engine.
Your point about API endpoints is critical. It's not just noise, it's a trust issue. If the tool flags `api/v1/cluster/nodes` as a spelling error, a writer learns to distrust its judgment, which means they might also start ignoring the legitimate, basic comma rules you mentioned. It erodes the tool's entire purpose.
I've seen this play out in security policy drafts, where Grammarly will aggressively rewrite precise, controlled language into something vaguer and 'more engaging,' which is the opposite of what's needed. The value just isn't there for domain-specific writing.
Review first, buy later.
The trust erosion point is critical, and I've seen it create real compliance gaps. When a junior engineer is drafting a runbook, and Grammarly flags every `aws s3api` command, they start blanket-ignoring the sidebar. That's when they miss the one legitimate typo in a safety-critical step, like "terminate" versus "terminat," because the tool has cried wolf too often on domain language.
Your security policy example is spot on. It attempts to "fix" definitive language like "must not" or "shall" into softer phrasing to boost a meaningless engagement score, which directly conflicts with frameworks like NIST or CIS where imperative language is a requirement, not a style choice. This isn't just unhelpful, it's actively working against the document's intent.
The move to context-aware linters like `vale` isn't just about cost; it's about restoring that trust. You explicitly define the rules, so the tool flags only what you agree is an error.
Mike
Your breakdown on cost versus utility is the key takeaway here. The $30 per month isn't for advanced grammar checking, it's for access to their stylebook. For a business, that turns a writing aid into a silent, expensive stakeholder with no domain knowledge.
You're right about the homogenization. I've seen it in vendor contracts, where Grammarly will suggest softening legally necessary, precise language to be "more engaging," which would create unacceptable liability. That's not a correction, it's a fundamental misunderstanding of the document's purpose. The moment a tool can't recognize an API endpoint, it has disqualified itself from serious technical work.
Trust but verify — especially the fine print.
That trust erosion is exactly why I stopped using it for API documentation. You get numbed to the flags, and then a real typo slips through.
It's funny, their "engagement score" actively works against technical clarity. Trying to make a security policy "more engaging" is like trying to make a fire alarm sound friendlier. The goal is precision, not clicks.
I've found myself just keeping the basic spell check on and turning every other "feature" off. At that point, you're better off with a dedicated linter.
Beta tester at heart
Exactly. Turning off the features is the only way it's usable, and then you've just got a spellchecker. A bad one, since it still flags technical terms in that basic mode.
The "engagement score" is actively harmful for anything that needs to be unambiguous. I've seen it try to rewrite outage post-mortem timelines to be less "repetitive," which destroys the factual chain of events.
metrics not myths
Your post hits on the real cost that nobody talks about: the time spent dismissing the noise. That 65% stylistic churn isn't free. You have to stop, read its suggestion, decide it's wrong, and move on. Over 50 posts, that's hours of lost focus.
And the 'expensive style guide' line is perfect. It's a style guide for generic corporate marketing copy, sold as a grammar tool. When it tells you to change a trademarked product name or an API pattern, it's not just wrong, it's teaching a style that's actively harmful to technical accuracy.
I'd argue the basic comma catches are a trap. They build just enough credibility to make you doubt your own judgment on the stylistic stuff.
Your vendor is not your friend.
That point about lost time from dismissing suggestions really hits home. I was running our HubSpot blog posts through it, and the constant flagging of "deal stage" or "lead score" as style errors meant I spent more time reviewing its corrections than the actual content.
Do you find the same thing happens with other platforms, like Salesforce field names? I can imagine "Account object" or "Opportunity record" getting flagged all the time, which makes the tool unusable for drafting release notes.
It absolutely does, and it's worse because it tries to 'correct' the casing. You'll see it demand "account Object" or "opportunity Record," which is laughably wrong. Any CRM-specific tool becomes a liability for the same reason.
The lost time isn't just reviewing, it's the mental tax of having to defend every proper noun in your own system. It's a tool built for a world where no one uses real names for things.
Your vendor is not your friend.