If you live and breathe technical marketing content – like those of us here at Fixate – you’ve probably heard more than murmurs over the past year about GPT-3, and more generally, about generative AI. GPT-3 is an early version of just one of a multitude of nifty open-source tools that use large language models (LLM) to generate text with stunning accuracy. The idea of replacing human writers (not to mention programmers) with Artificial Intelligence (AI) that can do the job faster and more cheaply has some managers salivating — and some technical writers shaking in their boots.
Write Totally Accurate Technical Content
Probably the biggest limitation for technical content marketers is that tools based on AI language models sometimes end up saying things that sound accurate, but aren’t.
Fortunately, AI is improving almost daily and has come a long way since I started testing it in December 2022. At that time I asked a GPT-3* based AI model in OpenAI’s playground “What are the most important log files to monitor on Ubuntu?” Here is the response:
- auth.log
- syslog
- dmesg
- kern.log
- apt/dpkg.log
- secure
- boot.log
- Xorg.0.log
- faillog
- user.log
If you know about Ubuntu, you’ll know that most of the items on that list are accurate. But it was a little off in subtle ways. For one, Ubuntu doesn’t have a user.log file; OpenAI appears to have made that up. For another, there is a dpkg.log file on Ubuntu, but it’s not inside a subdirectory named apt, as the list above suggests.
These are examples of technical inaccuracies that would be easy to gloss over if you lack deep domain expertise. Informed readers, though, will notice and call them out. If you entrusted your technical content generation entirely to GPT-3, you’d likely end up publishing information that is just plain wrong in certain respects; although you may never have known it until readers start leaving comments that criticize your company for not knowing its stuff.
*GPT-3 is a basic version of one of OpenAI’s solutions. It is the tool we started playing with as soon as it was available. This foundational technology has already advanced beyond recognition. However, many of the lessons we learned from our original research and testing still apply.
Generate Truly Original Technical Content
Most AI tools work by ingesting vast amounts of existing data and using it to generate new data.
That approach works well if the new content you want to create is fundamentally similar to content that already exists. If you want to bless the world with yet another article about “The top 10 reasons to move to the cloud” or “5 ways to start your digital transformation journey,” generative AI will probably be pretty good at writing the article for you. This is because it draws on the vast amount of content that already exists on subjects like these.
But if you’re looking to create something more original – say, documentation about your product, or a how-to article about a new tool that no one has written about before – generative AI won’t have much (if any) relevant data to work with.
If you want to create original content – which you probably do if you’re hoping people will actually read what you publish, and it won’t be buried on page 12 of the search results – you’ll need human writers.
Self-Curate Technical Marketing Topics
One thing you learn quickly in the world of technical marketing is that no matter how good your content is, few people will care about it if the topic is boring or irrelevant to your target audience.
This is not a problem that AI can solve totally on its own. AI models can generate good enough topic ideas based on keywords that you feed to them. But you have to come up with relevant keywords. This requires a deep understanding of your marketing goals and audience needs.
Fixate’s process now includes the use of “Curio,” a proprietary curator of industry-specific topics.
Are you a content strategist or creator? Participate in our survey here, AI-Generated or Not? to contribute to research about the efficacy of artificial approaches for curating topics.
With Curio, our customers benefit from the efficiency of AI without the distraction of switching to a separate platform. Curio is streamlined into the overall content creation process.
Plan Content Formats and Type
Along similar lines, AI isn’t capable of strategic reasoning. You need to decide if you want to position your content as, say a blog post or a whitepaper. That type of decision requires a deep understanding of the type of audience you are trying to reach, as well as the part of the sales journey that the content is designed to support.
Here again, it’s hard to imagine AI automating this work away. There are too many nuances at play to give this job to anything other than a human.
Conclusion: Generative AI is Innovative, but Not Revolutionary
To be sure, generative AI may help technical marketers in some ways. For example, imagine using the tool to write summaries of articles written by engineers. It might also be cool to explore the use of AI as a type of “smart” copy editor. It could, for example, use context to determine that you actually meant to write “OpenShift” in an article where you wrote “OpenStack.” That’s the type of nuance that only copy editors with specific domain expertise (which are hard to find) will understand. So AI may be a useful aid.
In other words, we’re in a world where generative AI is to technical marketers and writers what AIOps is to IT teams. It is a way to automate mundane tasks so that knowledge workers can focus on more innovative work. But it’s hardly a full replacement for a skilled team of technical content curators, writers and editors.