When Emrick Donadei first started working at Google, artificial intelligence was nowhere on his professional radar. Like countless other software engineers at the tech giant just a few years ago, his daily tasks did not involve large language models or the complexities of AI safety. He felt unqualified for the emerging field, lacking what he perceived as the necessary credentials.
The Turning Point: ChatGPT and Google's AI Pivot
The landscape shifted dramatically with the public release of ChatGPT. This event pushed Google to urgently accelerate its own focus on LLMs (Large Language Models). Internal opportunities for role changes began to surface. Donadei, now 32 and based in New York, was curious but filled with doubt about his eligibility for these new AI positions. He believed a high demand for talent might help, but knew it wouldn't be enough without his own initiative.
The key moment came when he decided to participate in Google's annual employee-only hackathon in 2024. This seven-day event became his gateway. He chose to compete on AI, calling it "the hottest topic in the industry." His goal wasn't to create something revolutionary but to gain crucial exposure. He built a small prototype, describing it as not "super useful," but an effective starting point that forced him to engage with unfamiliar tools and concepts like LLM infrastructure and model fine-tuning.
Beyond the Hackathon: Leveraging the Experience
Donadei emphasizes that simply participating in the hackathon was not the end of the journey. "You can't just do a hackathon and stop there," he stated. The critical next step was actively leveraging that experience. He and his team discussed their project extensively. Donadei proactively reached out to group technical leads across Google to present his work.
These 30-minute conversations served a dual purpose: they helped determine if his ideas aligned with team goals and, more importantly, allowed him to build connections outside his immediate circle. This networking and the need to clearly explain his work within Google's broader AI strategy were invaluable. The momentum carried into 2025, where a second hackathon participation eventually led to a public technical disclosure with the company.
Self-Directed Learning in the AI Era
Parallel to his internal projects, Donadei committed to intense self-education. He strategically uses a suite of AI tools to accelerate his learning. His toolkit includes Claude Code for understanding code, Gemini and ChatGPT Deep Research for case studies, and NotebookLM for processing large information sets.
He supplements this with YouTube lectures from experts like Andrej Karpathy and even co-runs a podcast focused on software engineering and AI, which he views as a proactive method to stay updated. This combination of formal internal exposure and informal, self-driven study created a powerful learning engine.
Reflecting on his path, Donadei doesn't attribute his success to mere luck. He sees it as evidence that timing must be paired with deliberate action. The hackathon provided him with unlimited access to frontier technologies and direct lines to key decision-makers, proving the gap between traditional engineering and AI work was bridgeable. His story offers a clear lesson for engineers: while credentials have value, active participation and showing up where the work is happening can be the true catalyst for a career shift into the AI revolution.
