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منشورات القناة
A new product edition usually starts with a copied manual. It's fast, and for one copy it works fine.
The trouble comes later. The support address changes, and now it has to be found in four manuals and two languages. One copy gets missed, and a user calls the wrong number.
Single-sourcing keeps one content base and builds every manual from it. Shared procedures are written once as reusable topics. Product names, versions, and contacts go into variables. Enterprise-only sections are handled with conditional content, and warnings or legal notices live in snippets.
The approach has limits. Too many conditions make a topic hard to read, and if two products share less than 50–60% of their content, separate projects may be simpler.
Read the article
| 2 |  A company ships its second product, and the docs team starts arguing: one site for everything, or a separate site for each product?
Both camps have a point. Split the docs, and legal pages, security policies, and shared how-tos get maintained twice. Merge them, and readers of one product keep landing on another product's pages.
The argument goes in circles because layout alone guarantees nothing. A more useful test: do readers always know where they are, and can the team avoid maintaining the same content twice?
Seen that way, "separate for readers" and "shared for the team" are two independent settings, and most of the trade-off disappears.
In the article, we look at four setups teams usually start from, three levels where separation is actually required, and why reuse should be in place before the second documentation site.
Read the article | 88 |
| 3 |  Your documentation calls it "SSO configuration." Your reader types "can't log in with my work account."
It's the same problem. But keyword search sees two unrelated phrases, and the reader leaves without an answer.
In the September release, AnswerGenius started searching by meaning as well as by keywords. When readers describe a problem in their own words, AnswerGenius still finds the right topic and answers from it. The answers themselves are now written by a newer AI model.
Also in this release: Documentation Sites on a ClickHelp subdomain with nothing to set up on your side, Restricted publications in the Published Docs MCP Server, and five features out of beta.
Read the September Release Notes → | 89 |
| 4 |  Most documentation is written for people the author never talks to. Nobody interviews the admin who opens a release note at 2 a.m. or the developer skimming an API reference between meetings.
That doesn't mean the reader is unknown. Product type tells you who uses it. The search query tells you how urgent the problem is: "resolve 503 error" and an onboarding portal visit call for very different pages. Role terminology and compliance requirements fill in the rest.
The hard part is keeping the profile honest. A persona built on one signal, usually product type, drifts from reality. So does one written for "Jenkins-familiar DevOps engineers" after the team moves to GitLab CI/CD.
The article lays out a method: a one-sentence reader profile, a five-stage knowledge model, and a 10-item checklist before publishing.
Read the full article | 168 |
| 5 |  Documentation generation with AI takes under a minute. It reads naturally, matches the tone of your docs — and is wrong in three places, because the ticket behind it was overridden by a decision no one wrote down.
That's not an AI problem. It's a timing problem. The decisions that shape documentation (terminology, defaults, edge cases) get made during requirements and design. Documentation usually gets attached to testing and release, long after those decisions are already settled.
AI removed the friction of writing. It did nothing about access to reliable information. If accurate info only exists after release, AI just produces plausible-sounding misinformation faster — and support bots reproduce that error at scale.
We laid out a practical model: where writers need early access to specs, and where it isn't worth the disruption.
Read the full article | 190 |
| 6 |  Release notes usually get written last, under time pressure, by whoever's left in the room. A dev tries to remember what shipped. A PM fills gaps from memory. Someone turns "fix: null pointer in auth" into something a user can read (five minutes before the release goes out.)
None of that needs to come from memory. It's already in your commits, PRs, and issue tracker. A commit like fix(auth)!: handle expired tokens tells you exactly what changed and whether it's breaking. Tools like semantic-release can turn a history of these into a changelog automatically.
What automation still can't do: decide if a "feat" commit is something users should hear about, or whether five performance commits are really one story worth telling.
👉 Full story here | 189 |
| 7 |  Two dictionaries just picked "slop" as their word of the year. In documentation it looks different: a portal that doubled in size over a year while support tickets stayed flat.
New on our blog: why cheap writing killed scoping, what happened at Snowflake after they cut ~70 tech writing roles right after a 30% revenue year, and the 6 questions nobody's left to ask anymore.
Full piece here | 205 |
| 8 |  Ask machine translation to handle the same product term twice, and there's no guarantee it comes back the same way. Multiply that across a documentation set, and one button ends up with three different names in three different languages.
We sat down with Alconost to talk through where this actually comes from — and why the fix isn't a smarter MT engine. It's a maintained termbase with an owner, real review, and a process that keeps up when the product changes.
Real incidents included: a core product term that came back as a compound word that doesn't exist in the target language, and a single bad string that spread through a translation memory badly enough to break a client's build.
👉 Full story | 210 |
| 9 |  Wrote up a comparison of 10 docs-as-code tools: free and commercial.
The short version: MkDocs if you want something running in an afternoon, Docusaurus if you need versioning, Antora if your docs are spread across multiple repos. For managed hosting, Read the Docs is the most mature option. Swimm is in a different category — it's less about publishing and more about keeping docs accurate as code changes.
Full breakdown is here | 189 |
| 10 |  New in ClickHelp this August 👇
Readers can now plug their own AI agent (Claude, Cursor, ChatGPT, Gemini) straight into your published docs — the Published Docs MCP Server reads your current content and answers only from what's actually there, not a guess or an outdated training snapshot.
Search also got smarter: AI Overview answers questions right in the results, and you can keep asking follow-ups without leaving search.
Smaller but useful: Watch + version history are now in the Next Reader UI, and Quick Publish shows you the full list of topics before you hit publish.
✍🏼 Full Release Notes | 168 |
| 11 |  Another one on content reuse — this time about snippet management.
Short version: if the same warning or install step is copy-pasted across 20 topics, and every product change means editing all 20 by hand — that's the sign it should be a snippet instead.
We go through the difference between variables (values: version number, email, company name) and snippets (blocks: procedures, warnings, legal text), what's actually worth turning into a snippet vs. what should stay inline, and how to keep a snippet library from turning into a pile of note1, temp_block, and snippet_new.
👉 Read the full article | 154 |
| 12 |  Technical documentation has a text problem — not too little text, but text doing jobs it's not good at.
Describing a multi-tab configuration wizard in prose takes 200 words and still leaves users guessing what the screen looks like. A 90-second screencast answers the same question and gets out of the way.
The article breaks down when each format earns its place:
- Screencasts work when the workflow is short, stable, and UI-heavy.
- Automated capture (Scribe, Tango, iorad) wins when the product changes often ( updating one step is faster than re-editing a full video.)
- Full video makes sense for onboarding and training where production quality matters.
The part worth noting: video without a transcript is a dead end for search. Users type questions into search boxes, not video players. Text stays the primary layer — multimedia just fills in what text can't show.
👉 Read the full article | 166 |
| 13 |  Claude writes well. But without access to your actual data, it's writing in a vacuum.
MCP fixes that. One server, and any compatible client (Claude, Cursor, Windsurf) can reach your tools and data without a custom connector for each one.
We wrote a step-by-step guide to building a local MCP server in Python:
— project setup with uv
— a working tool with @mcp.tool() in 30 lines
— local testing with MCP Inspector before touching Claude Desktop
— the claude_desktop_config.json file and where to find it
— the most common failures: wrong path, missing uv, vague docstrings
For technical writers: the guide ends with a pointer to ClickHelp's MCP server — which gives AI agents direct read/write access to your documentation portal.
👉 Read the full guide here | 178 |
| 14 |  Docs aren't just read by people anymore. So we tested how AI handles them.
We ran a quick test: gave ChatGPT a link to one of our documentation pages and asked it to summarize what it was about.
It opened the link, read the page, and answered in seconds. No extra steps.
Small result, but a good reminder — docs today get opened by more than just people.
Search engines, AI assistants, link previews in Slack and LinkedIn all try to do the same basic thing: open a link, get something useful back.
Read the full story | 158 |
| 15 |  DITA is powerful. But does your team actually need it?
Topics, maps, reuse, single-source publishing — it all works. Just comes with an XML editor, a publishing engine, a CCMS, and months of setup.
For a 3-person team with one product: almost always overkill. For 20+ authors, five languages, and regulatory requirements: almost always worth it.
Between "Word doc chaos" and "full enterprise CCMS" there's a whole spectrum of tools that don't get talked about enough.
We broke it all down — structured authoring explained, tools compared (DITA OT, Paligo, Heretto), and a practical guide to picking the right setup for your team size and workload.
👉 No fluff | 177 |
| 16 |  Ever nodded along when someone said "send me the BRD" — and then quietly Googled what that actually means?
New article breaks down five core product documents: MRD, BRD, PRD, Tech Spec, and User Stories. What each one is, who writes it, when it appears — and how they all connect in a real SaaS product example.
Plus: three scenarios at the end (startup, agile team, enterprise) so you know exactly which docs your situation actually calls for.
👉 Read | 190 |
| 17 |  📢 New in ClickHelp: multiple documentation sites, one portal
If you publish docs for more than one product, brand, or audience, this one's for you.
You can now run several independent, public-facing documentation sites from a single ClickHelp portal. Authors manage everything centrally — but each site appears as a fully separate website to readers, with its own custom domain, branding, home page, and set of publications.
How teams are using it:
▪️ A dedicated site per product or product line
▪️ Separate brands for different markets
▪️ A public Support Center + a developer knowledge base with API docs
The feature is in public beta — try it for free. Message us and we'll set up a sandbox where you can build a few sites with your own content, with no impact on your live portal. | 167 |
| 18 |  Regular expressions are one of the most powerful tools for technical writers — yet often underused.
They can turn hours of manual editing into seconds:
- bulk replace patterns,
- clean markup,
- extract data,
- and automate repetitive documentation tasks.
If you work with large docs, APIs, or structured content, regex is a skill worth mastering.
👉 Read the full guide here | 208 |
| 19 |  📄 Google Docs works great when documentation is small. A few guides. A few contributors. A few updates.
But things change when documentation grows across products, teams, languages, and publishing channels. Content gets duplicated, updates become harder to track, and maintaining consistency turns into a challenge.
At that point, you start needing a more structured way to manage content.
In our latest article, we compare Google Docs and ClickHelp, exploring why many growing documentation teams eventually move from document-based workflows to a dedicated CCMS.
👉 Read the full comparison | 197 |
| 20 |  Something shifted in how technical writers think about video, and it's mostly because the editing part got a lot less painful.
AI tools like Descript, Synthesia, HeyGen, and Guidde are making it possible to go from a rough screen recording to a polished, captioned, multilingual video, without a production team or a full day of editing.
That changes what's realistic for documentation teams. Voiceovers, captions, avatar-based walkthroughs, workflow capture: things that used to require specialists now fit into a solo writer's process.
And once the video exists, embedding it into ClickHelp is straightforward – via URL or an HTML block.
This article breaks down the tools, the workflow, and what actually matters when adding video to a documentation project.
Read the full article 🎬 | 198 |
