- How did you transition from video production and data analysis into Developer Relations for AI? And, what made you realize that creative storytelling and technical advocacy belonged together?
My story actually starts in software engineering. I have a computer science background and I genuinely loved to code. But on weekends I started recording videos for DJs, traveling, and it was just super fun. Even though I loved software, I started growing in video production and getting very well paid for it. So I made the call to go full-time as a videographer.
From there I became a video agency owner, built a team, and in 2017 I founded my own video production company in Brazil called Destaquei Filmes. Over the years I produced 1,500 plus videos across all kinds of industries.
In 2021 I moved to the US to do my MBA. I really wanted global impact and a broader stage. Right around graduation in 2023, I saw the OpenAI GPT release and immediately thought about how this could be applied to video production. I decided to stay in the US and explore it. But first I wanted to understand the fundamentals, so I went into data analysis because I believe you need to understand data before you can really build on top of AI.
The transition into DevRel happened through a friend who worked at an unstructured data company doing data pipelines, Aparavi. He got me in. The manager basically said: “If they ask if you can code, say yes. If you can talk to people and speak publicly, say yes.” They had seen my AI podcast and they saw something in that combination. The role didn’t even have a name yet. After a couple of months I found out it was called Developer Relations and I had zero idea how big it was. But I got excited fast because it brought me back to creating videos, which is what I always wanted. It combined video production, technical work, public speaking, and community building all in one. That’s exactly where I want to be.
- For readers unfamiliar with developer relations, what does this role actually entail in the context of enterprise AI adoption?
Developer Relations, or DevRel is the bridge between a technical product and the developers who use it. In the context of enterprise AI, that means you are writing technical documentation, building demo projects, running hackathons and workshops, creating content that shows developers how to actually implement AI solutions, and doing all of this while keeping the trust of a community that has zero patience for BS or sales speak.
At Aparavi, which is an enterprise unstructured data company focused on data pipelines, I built the Discord community from zero to 700 plus members and grew website traffic from 1,000 to 9,000 monthly users using technical content and SEO. That did not happen through marketing tactics. It happened because I showed up consistently with content that was genuinely useful.
Right now at GMI Cloud I work with bare metal NVIDIA GPU infrastructure, model as a service with pay per token and pay per hour options, and GMI Studio, which is a visual AI workflow platform where you can build full generative media and video pipelines. My job is to help developers understand how to use all of that and build with it confidently.
- Through hosting “AI Inside San Francisco” and your work at Aparavi and beyond, you’re constantly exposed to how companies are implementing generative AI. What’s the gap between how AI tools are marketed versus how developers are actually using them in production environments?
The agent ecosystem is the clearest example right now. The marketing makes agents sound plug and play. In production it is a completely different story. New protocols like MCP are emerging, agent frameworks are evolving fast, and the real challenge is not any single tool but the communication and interoperability between all of them. There is still a big disconnect. There is no standardized layer yet that lets these systems talk to each other reliably at scale.
Developers are not doing anything wrong. Things changed very fast and we need to think much more about how systems communicate with each other. The tooling is still catching up to the expectations being set externally. That gap is real and any developer who has tried to build a multi-agent workflow in production has felt it.
- You’ve produced over 1,500 videos and now create technical content for developer audiences. How has your production background changed the way you approach developer education and community building in the AI space?
It is honestly my biggest superpower in this role. At a hackathon I can produce polished technical content with animations in a matter of hours. For another DevRel person that same content might take days. If it is outsourced it could take weeks. That speed and quality changes everything because in developer communities timing and authenticity matter more than perfection.
That is something I bring to GMI every day. Being able to show developers exactly how to run frontier LLMs or build a video pipeline on GMI Studio through a well produced video, done quickly and authentically, hits differently than a written doc alone. Video production is what makes my technical education land in a way that sticks.
- You’re building developer communities around AI technology at scale. What’s working right now to engage developers authentically, and where do you see companies getting developer relations wrong, especially during the AI hype cycle?
Three pillars. Logic, empathy, and authenticity.
Logic means everything you say has to make sense. Developers will immediately catch anything that does not add up. Empathy means you meet developers where they are, understand their real frustrations, and ensure you are aligned before trying to teach anything. Authenticity is probably the most important one. Developers have a very sharp radar for sales speak. The moment they feel like they are being pitched instead of educated, you lose them, and it is very hard to get that trust back.
The biggest mistake I see companies make is going full sales mode at technical events or injecting promotional messaging into technical content. I learned this firsthand. The moment a developer community starts to feel like a sales funnel, engagement drops fast. The companies winning in DevRel right now are treating their developer communities as partners in building, not audiences to convert.
- You have a unique vantage point working for an enterprise AI company while interviewing founders building the next generation of AI tools. Where do you see the biggest opportunities for developers who want to build meaningful careers in AI, beyond just prompt engineering?
Start by testing everything. Go in the direction your curiosity is pointing. If you are drawn to data infrastructure, go deep on data tools that use AI. If you want to work on generative systems, experiment with agent frameworks and automation pipelines. If your background is in creative fields like video or design, explore image models and video generation models. The tools are more accessible right now than they have ever been.
The second thing is to document your journey and share it publicly. Put your projects in a portfolio. Write about what worked and what did not. Talk to people in the space and ask about their careers. The developers I have seen grow fastest are not always the most technically advanced. They are the ones who combine competence with communication and show their work consistently.
One thing that shifted my thinking came from an interview on my podcast with Enrique Lopez, formerly of Freepik and now at Majestic. He pointed out how the messaging around AI has evolved. Two years ago everyone was saying AI is not here to replace you. That was the reassurance the world needed. Today the conversation has shifted to how AI can enhance you. That is a much more productive frame and it reflects a real maturation in how both builders and users are relating to these tools.
- What skills or mindsets from your background have proven most valuable in developer relations that other professionals transitioning into AI-adjacent roles might overlook?
The ability to make complex things easy to understand. It sounds simple but it is rare. Most technical people default to technical language with technical audiences and assume that is the right move. But even developers benefit from clarity, good pacing, and narrative. That is something video production trained in me over thousands of hours of editing. If you lose the audience it does not matter how good the content is.
The other thing I would say is own being cross-disciplinary. My path went from software engineering to video production to data analysis to developer relations and at every step someone implied I should pick a lane. What I found is that the combination is the value. The professionals who will have the most impact in the AI era are the ones who can build, communicate, create, and connect and who see those as one skill set rather than separate careers.
My goal right now is to be the voice for video professionals and creative agencies navigating this AI transition. That community deserves someone who has lived on both sides, who understands the craft deeply and also understands the frontier of AI, and who can translate between those two worlds honestly. That is the work I am most excited about.
