Artificial Intelligence is everywhere. It’s in the news, it’s on our phones and it’s knocking on the door of every business. The pressure is mounting for companies to create AI applications, fast. But here’s the thing—it seems like everyone is slapping “AI” on their tools and products, whether or not GenAI plays a pivotal role in their offerings.
As developers in enterprise companies rush to create real GenAI applications, they’re faced with a daunting task: figuring out how to make this emerging tech work for their audience, get to market quickly, and do it in a way that is still going to be relevant this time next year. That’s tricky enough, but there might be a more fundamental problem. There are a ton of decisions to be made about infrastructure tools, but the landscape is shifting at an incredible speed. No one wants to get locked into something they’ll need to replace in six months.
If your company is creating tools and infrastructure for the GenAI stack, your marketing strategy needs to address these challenges. While the basic principles of developer marketing remain the same, there are three areas that developer marketers should approach differently in this AI-centric environment.
Before we dive in, let me add a disclaimer: this is how we see things today, but everything is changing rapidly. So, read fast.
Education: More than just product features.
Education has always been a key part of any developer campaign. It’s crucial to have a solid body of content for developers available in a developer hub and promoted on the channels they frequent.
But when you’re marketing GenAI, there are two key differences:
First, category education is paramount. To make decisions in this noisy environment, developers don’t just need information about your solution. They need to understand your specific niche in the toolset landscape—where you fit in the stack, not just the overarching category of GenAI. Developers need to be able to see the exact role you’ll play—and exactly what problem you’ll solve for them.
Here’s a word of caution: some companies may be overinvesting in product information to establish themselves in the community. But without category education and proof (more on that in a moment), information alone isn’t going to move the needle.
Second, data security is a huge issue. Developers need to be confident—for themselves and for their legal teams—that using your tool won’t put their sensitive information at risk. Educating potential customers on how you’re keeping their data safe isn’t just a priority—it’s critical.
Proof and trust: Enabling quick decisions.
Before signing off on a tool, developers need to be absolutely confident it will work and deliver ROI. They also need to trust the company—especially if it’s a startup. Will you have their back? Are you in it for the long haul? Are you future-proofing your solution to make sure their decision still feels smart a year from now?
Typically, developer marketers can build this trust over time, but in the current AI boom, that luxury is gone. You need to gain that trust in 3-6 months, rather than 6-12.
One of the most common ways to build trust—tapping into the developer community—isn’t available for these new AI tools. There simply isn’t an established community yet. And let’s face it, once-trustworthy destinations like StackOverflow are now overrun by bots.
So, with the traditional go-tos looking less effective, what should you focus on?
- Use cases and success stories/case studies. These show potential customers how your tool is used and prove that it works. Getting these out quickly should be a top priority. If you need to, pull stories from beta tests and other areas you might not use normally. You should replace these once additional narratives become available.
- Conferences and events. Finding the right conference can give you a huge ROI. They offer an incredibly high density of people learning, connecting and expanding their networks. It’s where the decision-makers who hope to be on the bleeding edge go to ensure they’re not making the wrong choice. How do you find the right conference? Don’t be too proud to search out the conferences your target audience went to last year. (You’re paying for that LinkedIn Premium membership—put it to use!)
- Social proof. Rather than waiting for this to happen organically in the developer community, you need to work with respected industry influencers. Their stamp of approval can fast-track your credibility. When you engage with them, don’t just ask for a rubber stamp. Seek out their real opinions and use them to make your product better.
Plan ahead for scaling to other audiences.
Because of the pressure coming from the C-Suite to build GenAI applications fast, the rest of the buying group is going to get involved sooner than you might expect. There’s a good chance this is everyone’s top priority right now. That means you should be thinking about how you’re going to activate the rest of the buying team ASAP.
For example, when creating case studies, consider two lenses: the technical “how it worked” story for the developers, and the business impact for the C-suite. Thinking about both audiences now will help you choose the right case studies and get the right information, even if you build the business-focused content later.
Having said that, don’t forget that everyone’s working at high-speed. You may want to prioritize talking to developers, but be ready to create that additional content quickly and have a plan to turn interested developers into internal champions once the C-suite gets interested.
The Iron Horse insight.
Over the next several months, this rapidly-evolving AI landscape will start to resemble more traditional markets with “best-in-class” leaders emerging. Companies who want to earn their spot in the GenAI stack need to move fast. Not everything your company puts out is going to be perfect. That’s totally okay.
Focus on these three areas and you’ll have a solid chance at becoming your category leader. Not every solution will succeed, but those who approach it strategically stand to gain the most. Remember, in the world of AI, the real value isn’t in the hype—it’s in solving real business problems. So, keep your focus on delivering genuine value, and may the best (and most useful) AI win.
