Generative AI and what it means for developers
Before we dive into the nuts and bolts of a solid developer marketing program, let’s explore the state of the generative AI boom. This overview will help demystify some of the buzz around generative AI and explain where this evolving technology is coming from, where it currently is, and where it’s headed.
Generative AI can broadly be defined as a tool that uses deep-learning models to generate various types of content, such as text, images, and anything else developed from the data it was trained on. These deep-learning models perform predictive modeling to generate output that reflects a comprehensive response to a user-entered prompt. This ability has made generative AI platforms, like ChatGPT, increasingly popular across industries as a multi-functional workflow solution.
In fact, according to the most recent Stack Overflow developer survey, 83% of developers reported using generative AI in the past year, primarily OpenAI’s ChatGPT or GitHub’s Copilot. Although AI and automation aren’t entirely new to developers, the new wave of generative AI has the potential to improve their workflows dramatically. These predictive solutions can provide coding solutions, new approaches to their work, new concepts for them to explore, and even open up projects that may not have previously been available to them. In general, it’s making a huge (and growing) impact on developers and their work.
Companies need to seriously consider the message they want to send to developers in this highly saturated market. Developers are using many of the well-known names; however, this can pose a challenge for anyone else who wants to reach developers with generative AI products or services. Also, generative AI isn’t only impacting developers but also the marketing landscape around them. Developer marketing practices are changing in many different ways due to the adoption of AI-based solutions, and this dynamic is posing new challenges as companies try to reach developer audiences.
Developer marketing challenges posed by generative AI
Generative AI has become a charged topic in marketing because of the various ways companies use it and engage with it. For marketers, it now commonly helps with tasks such as content creation, creative production, and dynamic creative optimization for ads, which uses customer data to help adjust various ad iterations to tailor them to specific audiences. It’s also used to generate chatbots, predictive analytics, anomaly detection, machine translation, and audience segmentation. Marketers who use generative AI as a tool have used its benefits to optimize performance and adjust initiatives, ads, and campaigns based on real-time analysis and customer data. However, these practices can create serious problems, especially in developer marketing, where establishing trust and credibility is crucial in facilitating product adoption.
Relying on generative AI is risky for several reasons. To name a few: lack of human touch or influence, factual fallacies or incorrect data, homogeneous content, loss of SEO and customization to reach a target audience, legal issues around data privacy violations, and algorithms trained (often unintentionally) with biases ingrained in the data. Studies have already noted many other problematic characteristics of generative AI, and the implication is that its use, particularly in common applications like content creation, can pose many risks to a brand’s image or a product’s success in the long run. There are many potential threats to be aware of, and some of its benefits may bring potential for even greater harm.
It’s clear that generative AI is an attractive tool for developers, allowing them to accelerate their development, search documentation more effectively, or learn new coding languages. However, the inherent risks associated with disproportionately using it in a developer marketing context mean it’s unlikely to replace the core principles and strategies that lead to measurable success.
Developer marketing principles for emerging technologies
Ultimately, any developer marketing program aims to increase awareness, facilitate consideration, and drive adoption for your product or service. That’s true across the largest names in tech, traditional Fortune 500 companies, and scale-ups in emerging tech, including those in generative AI. The market may be crowded, but our foundational developer marketing principles still apply, allowing our clients to cut through the noise and drive results.
Each project begins with our team's technical knowledge and deep understanding of the developer landscape, particularly in the case of something new, like generative AI. We then leverage this knowledge base to apply our developer marketing approach, typically using three phases to inform the strategic direction of our work. Here’s a brief overview of each phase and how it applies in the context of the generative AI boom.
Discovery
In the discovery phase, we take our time defining the problem space for our clients and how we can tackle those challenges together. We conduct comprehensive research, stakeholder interviews, audits, and analyses across the developer experience, product details, and the broader market. These insights help us evaluate the best path forward and narrow down the appropriate audience we want to engage. The landscape we find during this phase may be undergoing change or transition, as is the case with generative AI. The discovery phase exists as part of a flywheel, so it’s important to revisit it regularly.
Consulting
In the consulting phase, we work closely with our clients to determine their strategic goals and develop a roadmap for their developer program. We are deliberate in developing a strategy that aligns with the client’s current go-to-market initiatives and marketing objectives. One of the most important tools we use is our Developer Signal Hub, which gathers insights on developer sentiment and broader market conditions. These insights were particularly useful for our work with a client in the generative AI space, allowing us to focus their messaging and positioning in the chaotic early days of the boom when new platforms were working their way into the mainstream. In the consulting phase, our team uses what we’ve learned to create a comprehensive strategy optimized for a specific audience and achievable in the production phase.
Production
In the production phase, we work our marketing magic and execute the go-to-market strategies we develop with our clients. Our team has over 13 years of experience bringing emerging technologies (like generative AI) to developers. Our full-service model drives measurable results through creative production, content management, performance marketing, and strategic iteration. The work produced always depends on the objectives of the client. For example, for a client in the generative AI space, we’ve done everything from mascot creation to the standup of a full-scale influencer marketing program.
Build a winning developer marketing program with us
With popular new technologies like generative AI, it can feel impossible to set achievable objectives, stand out, and win over an audience of skeptical developers. Catchy has you covered, with experience in marketing emerging technologies and skill in reaching the right audience with your product or service. Our core developer marketing principles have stood the test of time and apply to our full range of clients, even those on the frontier of tech.
Get in touch with us today to learn what we can accomplish together.
