AI continues to make inroads into companies of all sizes, types, and industries, with the enterprise tech industry being one of the most active in embracing AI. I’ve already spoken with developers about how they’re adopting AI tools and creatively using them in their own workflows. We’ve also discussed the advent of AI agents and how AI is impacting DevOps, but an angle that hasn’t seen as much discussion is how companies are using AI tools and platforms internally.
Curious to learn more, I reached out to a number of dev platform companies, and those that agreed to go on the record were fairly consistent about their approaches to using AI, reporting that nearly all departments across their respective companies were adopting AI in some form.
Using AI in Engineering and Product Development
All of the dev platform executives I spoke with mentioned that they’re using (or exploring the use of) AI in product development and engineering in some capacity. Dana Lawson, Chief Technology Officer at Netlify, said that Netlify’s research and development teams are using AI internally within development cycles and leveraging AI to power some product features.
“We’re using OpenAI for our ‘how did it fail feature’ and Kapa.ai for the ‘ask Netlify’ doc feature,” she said. “We’re also using Anthropic, Langbase and OpenAI for some of our feature development…[and we’re] using Codemod for internal code changes — like React updates and other systematic upgrades — and we’re using Github Copilot for software development.”
How Aggressively Are Companies Adopting AI?
“All of the departments in Netlify from Finance to Engineering have embraced some form of AI,” said Lawson. “We are currently using Gemini with our Google suite for business tools. Marketing uses various tools from ChatGPT and Claude to Perplexity, MidJourney, Otter.ai and more.”
“Vercel is an AI-first company, so all of our departments are using AI to iterate and ship faster.”
– Jenny Molyneaux, VP of People at Vercel
“Vercel is an AI-first company, so all of our departments are using AI to iterate and ship faster, from People to Marketing to Engineering to Customer Support,” said Jenny Molyneaux, VP of People at Vercel. “Our Customer Support team decreased tickets by 31% when we developed an AI-powered agent to seamlessly integrate with our existing support workflows, [and] our People and IT teams equip our staff with tools like Notion Q&A AI and Glean AI Assistant to enable generative answers across Notion, Slack, Docs, and beyond.”
Molyneaux said that the Vercel People team uses Brighthire to summarize notes from interviews her team has with applicants, and she and her team are “…trialing a variety of AI tools across coaching, application filtering, and learning and development.”
AI in Marketing: Ghostwriters and UI Generators
While development and engineering might arguably be seeing the widest experimentation and trial usage of AI at the moment, dev platform companies are also turning to AI to help empower their marketing teams, with a rapidly-expanding assortment of AI tools and platforms aimed at marketing professionals hitting the market over the last year or so. Morgane Palomares, VP of Marketing at Vercel, explained how the Vercel marketing team has taken advantage of AI tools to improve efficiency and help drive results.
“Our Marketing org uses AI to quickly break down deeply technical concepts, inspect the tools a frontend is using to help with prospecting and refine human-written copy to better follow our company style guide,” said Palomares.
Expanding on the use of AI to create a company style guide, Palomares explained that they used their Enterprise ChatGPT license to create a “Ghost” (i.e. ghostwriter) that “…helps Vercel marketers go from idea to copy fast, and ensures we’re aligned with one tone and voice across many team members.”
Palomares also described how the marketing team leverages their v0 product, a generative user interface system powered by natural language and AI. “v0 is like an always-on pair programmer for developers, but it’s also a powerful UI generator for non-developers,” said Palomares. “Our Marketing team creates everything from dashboards to landing pages with v0, including Google Slide decks.”
AI in Operations and Customer Support
Many organizations have begun using AI in their operations and customer support efforts, and dev platform companies are no exception. According to Netlify’s Lawson, AI is beginning to be used widely across those departments.
“…our development teams use AI from code creation to service integrations for our customers.”
– Dana Lawson, Chief Technology Officer at Netlify
“Our Customer Success team uses AI to understand our enterprise customer health, our development teams use AI from code creation to service integrations for our customers, and our support team uses AI-driven chatbots to help customers self-serve,” explains Lawson. “Our technical documentation team has also incorporated AI to better assist users looking for product education.”
More Tips From the Trenches
While adopting AI tools and platforms is still in the ”let’s try it and see” phase for many companies, executives I spoke with also encouraged companies in the early phases of AI tool adoption to think carefully about how they’re embracing AI.
“Ultimately, we are accountable for the code that we write, or the code that we direct AI to write on our behalf,” said Randy Reddig, Vice President of Technology Research and Incubation at Fastly. “[You should] always ask: What are we trying to accomplish? Will this replace or supercharge our human capital? And will this be used to make decisions, or inform better, more optimal decisions (or faster decisions)?”
That deliberate approach is echoed by Netlify’s Lawson, who encourages AI tool and platform adopters to set aside the time needed to learn about these tools and practice using them. “If you aren’t using them at your current job, the likelihood is incredibly high that you may need those skills in your next one,” said Lawson. “Don’t overly worry that using these tools will take away your job. Instead, think of them as empowering you to do your job better. Start small by using suggestive AI in your IDE; and once you get comfortable, then you can begin to branch out and incorporate these platforms into the features and tools you are building.”
The encouragement to test and experiment with AI is echoed by Vercel’s Palomares. “Investing in a new tool requires an investment of time, money, and a bit of courage. But when you take the leap, you can understand what an AI tool does for your workflows,” said Palomares. “Then look at the data and go from there.”
“Humans still need to drive the systems to complete the last mile of software development — refining code, aligning with specific business contexts, and addressing edge cases.”
– Dana Lawson, Netlify
For those organizations looking at easy entry points for the use of AI, Lawson stresses that tackling repetitive, mundane tasks can be a good starting point.
“In terms of what AI does well, it’s really powerful for repetitive tasks, structuring data and content, or scaffolding workflows. When it comes to high-quality, nuanced outputs, AI still has a long way to go on the creation side of content,” said Lawson. “Humans still need to drive the systems to complete the last mile of software development — refining code, aligning with specific business contexts, and addressing edge cases. AI is a powerful assistant, but not a replacement for developer expertise.”
What’s Next For AI and Developer Platform Providers?
In addition to using external AI tools and platforms, companies are also starting to incorporate AI in new products, and continue to drive awareness and experimentation of AI among employees.
Operating large language models can be power-hungry and expensive, so Reddig points to Fastly’s new Fastly AI Accelerator product, which focuses on helping developers combat the aforementioned challenges with using LLMs extensively.
“Fastly AI Accelerator offloads requests from the origin, reduces our customers’ overall costs, and delivers content faster by serving previous responses from Fastly’s global edge cache,” said Reddig. “The key difference is the use of a semantic cache — allowing AI Accelerator to serve responses from similar (not but identical) queries. The result is faster, more responsive LLM-based experiences, enabling our customers to serve more of their customers, in less time, at lower overall cost.”
“Everyone can cook — which means we’re leveraging AI to make good developers great and to invite more people into the process of building.”
– Morgane Palomares, VP of Marketing at Vercel
According to Palomares, Vercel’s v0 product has inspired a company philosophy shift at Vercel. “Everyone can cook — which means we’re leveraging AI to make good developers great and to invite more people into the process of building,” said Palomares. “We encourage all developers to embrace AI and use it to expand their skill set into new realms. And get cooking.”
The advent and increasing ubiquity of AI is continuing to impact businesses of all types, as well as society at large. “AI will be common across all facets of business, whether you’re a consumer or building software, so we will continue to embrace these concepts,” said Lawson. “As AI technology advances, more emphasis will be placed on the value and consumption of these services, and data will become more ephemeral. In the context of web development, AI is set to transform how teams collaborate and bring experiences to life, enabling faster iteration, more flexible composition of services, and personalized and impactful digital experiences. The broader challenge for the industry is ensuring these tools enhance creativity and efficiency versus adding complexity and friction.”
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