Let’s be honest… nobody wakes up excited to write documentation. It’s not glamorous. It’s definitely not what most developers signed up for.

So, when a deadline is looming, documentation is the first thing to get pushed to the back burner.

But here’s the thing, when something breaks in production and the person who built it isn’t around anymore, or when upgrade time rolls around and you’re trying to figure out what to test — you realize how documentation could have been a lifesaver. 

And when ServiceNow releases a new feature and you’re wondering which customizations you can finally retire, that’s when you really feel it.

The truth is… documentation is the only way you can move fast without breaking things.

Why documentation matters

If you’re a platform owner, think of it as your insurance policy. If you’re an implementation partner, it’s an onboarding asset that gives your clients confidence that they can run what you’ve built, without depending on you for every small change.

When you’ve got a complex customization running critical business operations, you cannot afford to reverse-engineer it during a P1 incident.

Having the “what” and “why” documented means you can troubleshoot without guesswork.

During upgrades, documentation is your test plan. It tells you exactly what to check and why it exists. Without it, you’re left relying on memory, which is not the most reliable way to go.

When new ServiceNow features roll out, documentation helps you quickly decide what to keep, what to refactor, and what to retire, cutting technical debt before it piles up.

In short, documentation is your platform’s memory. 

Without it, you’re relying on fragile tribal knowledge that disappears the moment a key developer leaves. The best time to capture that knowledge is when it’s fresh, so you and your team can keep the platform running and avoid surprises.

Then why is documentation often an afterthought?

If documentation is so critical, why does it always get skipped or rushed?

First, it’s time-consuming. Your developers are under constant delivery pressure, and writing a clean, structured doc can feel like a luxury they can’t afford.

Second, consistency is a problem. A few team members produce clear, detailed documentation, but most do the bare minimum. When you revisit those docs later, they’re vague and don’t really answer what you came looking for.

And third, no one ensures the documents are up-to-date. Your customizations and workflows continue to evolve, but the documentation stays stuck in time. Over months and years, the gap between what’s documented and what’s actually in the system grows wider. 

Eventually, no one trusts the docs enough to use them. Without a better way to capture and update documentation, you’re left with a library that looks full, but can’t be relied on when it really matters.

What should you document?

For starters, you don’t need to document every cosmetic tweak. If you’re just renaming a field label, no one’s going to lose sleep over it not being in the document.

The goal is to document what matters most. That means the high-impact, high-complexity changes where missing details will slow down incident resolution, stall upgrades, or cause unnecessary rework.

When documenting, start from first principles: if this broke tomorrow, what would I need to know to fix it quickly? At a minimum, you need to include:

• Custom integrations including authentication, mapping, and configuration details
• Unique business logic scripts, business rules, or flow modifications beyond OOTB behavior
• Service portal widgets especially those that interact with external systems
• Major process deviations where workflows diverge from baseline ServiceNow
• Security changes like ACLs, encryption, or handling of sensitive data

For everything you document, you need to capture:

• The purpose, i.e., why it exists
• High-level functionality as to what it does, without code-level noise
• Dependencies such as related tables, fields, or other objects
• Rollback steps that tells one how to undo changes safely
• Testing notes such as ATF cases or manual validation steps

At the heart of it, documentation isn’t just about fixing issues faster. It’s about building trust. It shows you deliver work that can be maintained, upgraded, and evolved confidently.

Why templates and governance alone won’t cut it

Many teams try to fix documentation issues with templates and strict governance. They set clear rules such as use these headings, store it in this knowledge base, and update it after every change. 

But templates don’t fill themselves in. And no one has the time to review every doc or enforce formatting rules to the letter.

Are you really going to penalize developers for missing a heading when a release deadline is looming? Probably not. The bigger issue is the execution gap between having a standard and actually producing consistent, high-quality documentation at scale. 

This is where AI changes the equation, automating the tedious parts so the process is followed every time, without adding friction or slowing delivery. Templates can give you a structure; but with AI you can ensure that it’s applied.

How AI changes the game

Imagine this scenario: you finish your update set. AI immediately scans it, detects every change, and produces documentation in plain English (or whatever your primary language is).

“Created a client script to validate the Due Date on Change Requests so it can’t be in the past.”
“Modified the Incident Auto-Assign business rule to exclude the VIP Support group for priorities lower than 2.”

You simply add a note explaining why you made those changes, and you’re done. No extra formatting. No guesswork. And it all follows your template and governance automatically.

The best is that AI keeps your documentation current. Months later, if another developer updates that same client script, AI recognizes the existing documentation, updates it, and preserves its history.

The best time to document is after UAT sign-off. An ideal flow would look like this:

1. Build the solution
2. Complete UAT and confirm it meets requirements
3. Let AI generate the initial documentation
4. Add human context to explain design choices or nuances

So during the upgrade season, you’re not wading through outdated, unreliable docs. Instead, you have a living, accurate record you can trust to guide your ATF tests, inform decisions, and help reduce technical debt without slowing delivery.

How Echelon AI developer automates documentation

Any large language model can turn code into plain language. However, the real value is when your AI developer understands the platform it’s working with. 

Echelon AI is trained on real-world use cases, guided by ServiceNow CMAs who’ve seen every possible edge case, know which details matter, which can be skipped, and where changes might have downstream impact. 

Echelon not only automates delivery from intake to build and validation, but also produces documentation in language that’s familiar to ServiceNow teams, making it easier to read, trust, and act on.

That’s the difference between a generic AI output and documentation that genuinely supports your platform’s day-to-day needs.

Final thoughts…

It’s common knowledge that for years, ServiceNow documentation has been slow, inconsistent, and often left until the last minute or skipped entirely resulting in missing context and unnecessary risk during incidents, upgrades, or audits. 

By automating documentation entirely, you can eliminate those challenges and make your documents a reliable, living resource that supports your platform growth.

It not only frees your developers to focus on building and improving the platform, but also makes you operationally smarter giving you a competitive advantage.