​The True Age of Engineering Documentation is Coming

Or: How you can instantly become the old guy who has seen it all!

As an engineer, you probably don’t like the documentation side of things. You should at least see its value, but, in my experience, engineers are usually not fans.
We know that it protects the organisation, supports future work, and helps others understand what we have done. And yet, under time pressure, documentation is often the first thing to be condensed, deferred, or quietly abandoned.
This is not new.
But there is going to be a new pressure to create even more documentation.
Not because management suddenly cares more. Not because standards have become dramatically stricter.
But because the value of documentation has fundamentally changed. And it’s because of AI.
How AI Will Make Documentation More Valuable
Historically, documentation has been hard to use well.
It was often written because it needed to be and then just left. People might refer to meeting minutes to double-check their deliverables. But usually, it would be left until there was an audit or something official like that.
And that meant it was written in a way that was only useful for such things. Which in turn meant that it was hard to use for other things. Things like:

• Understanding why an engineering system was set up the way it is. Ideal for new members of an engineering team.
• Knowing if options had been considered or tried – and if they would work or not.
• Explaining how the system works – to engineers and non-engineers.

This was, and is, a great loss. People could easily make the same mistakes or not understand the system well enough to think of improvements.
AI changes that completely.
With comprehensive documentation of an engineering project (design decisions, options considered, trade studies, constraints, assumptions, experiments tried, and outcomes), it is possible to interrogate all of it quickly.
Not by reading everything line by line, but by asking the question you want answered.
Interrogating Engineering History
Imagine you are looking at an existing engineering system and considering a change.
If you have good documentation, you can now ask an AI system questions like:

• Was this kind of change considered previously?
• What alternatives were explored at the time?
• Was something similar attempted and found to fail?
• What constraints drove the original decision?
• What assumptions were critical—and are they still valid?

The AI does not invent the answers. It mines your own engineering record.
This documentation becomes your operational knowledge.
You won’t repeat the same mistakes and you can better assess new ideas with the knowledge you now have. It’s like you have become the old guy in the company who has seen it all!
Documentation Will Be Demanded More – Because It’s Easier
There is definitely a certain irony here.
The same technology that makes documentation more valuable also makes it easier to produce. Engineers can now:

• Dictate notes instead of typing them
• Generate concise summaries from long discussions and disjointed meetings
• Convert rough thoughts into structured explanations
• Maintain logs with minimal friction

As I mentioned in the previous article on one-pagers, AI can help you turn raw notes into something readable and useful. That capability will remove many of the traditional excuses for under-documentation.
And once that happens, the expectation will shift.
If documentation is easy and highly valuable, it becomes harder to justify not doing it.
For the Global Engineer (and Company)
This matters even more in a global engineering context.
When documentation exists, AI allows it to be repurposed for different audiences.
Language barriers are reduced. Differences in writing style, cultural expectations, and technical depth can be adapted on demand.
That means documentation no longer has to be perfect for everyone. It just has to exist. Making it easier again for an engineer to work anywhere in the world.
It also means an engineering company can be more robust.
Engineering teams change – sometimes when you least expect it.
People get reassigned. Projects ramp down. An entire engineering team gets taken out by food poisoning at a corporate barbecue.
When a new team comes in, good documentation plus AI dramatically reduces the recovery time. New engineers can interrogate the history of the project instead of starting with fragments and assumptions.
Think about all the lunar exploration knowledge that needs to be relearned with the recent efforts to return to the Moon.
Knowledge that can be reused, transferred, explained, and interrogated is far more valuable than knowledge locked inside a few people’s heads. When all past experience within a company is documented and easy to use, it increases the value of the company’s intellectual property by orders of magnitude.
And an engineering firm would be foolish not to demand all knowledge now be documented.
The Shift That’s Coming
Engineers are probably going to be asked to document more than they ever have before.
You might not like it. You might resist. But, as the above shows, the payoff will be real.
The best you can do now is start using AI to make this documentation easier to generate and then be mindful to use AI to access that documentation (and others) in the future.