Wilbert O'Kon

Why this persona fits the audience

He is a Dublin-based growth engineer at a 9-person SaaS company, maintaining a production assistant that uses Claude for support drafts and Gemini for multilingual QA. He owns the integration code, API keys, and monthly model usage reports for the team.

• Age: 27
• Location: Dublin, Ireland
• Occupation: Growth engineer
• Income: €68k salary
• Education: Bachelor's in computer engineering
• Company size: 9
• Years in role: 2

“Efficiency isn't just about speed; it's about knowing exactly where every single cent and millisecond goes in your system.”

Wilbert O'Kon is a twenty-seven-year-old Growth Engineer navigating the volatile intersection of artificial intelligence and business operations in Dublin. Holding a Bachelor's in Computer Engineering from TU Dublin, he transitioned from traditional backend development to specialized AI integration roles three years ago, drawn by the rapid evolution of large language models. Currently, he serves as the de facto infrastructure architect for a lean nine-person B2B SaaS startup, a role that demands both high-level strategic thinking and granular coding proficiency. His daily reality revolves around the delicate balancing act of maintaining a production-grade assistant that leverages multiple AI providers. He personally manages the integration code, rotates sensitive API keys, and generates monthly usage reports that dictate the company's operational budget. This responsibility grants him significant ownership but also isolates him as the single point of failure for the team's AI capabilities. His professional philosophy is rooted in 'measurable outcomes' and 'responsiveness.' Wilbert believes that technology should serve the business logic, not the other way around. Consequently, he has spent the last six months rigorously auditing the company's reliance on external APIs, implementing caching layers to reduce latency and drafting new prompts to improve output consistency. He recently made the decision to migrate a portion of their customer support drafting workflow from a single-provider model to a hybrid setup involving Claude for creative tasks and Gemini for strict multilingual validation. This move was driven by his need to mitigate vendor lock-in and optimize costs, reflecting his pragmatic approach to resource allocation. Outside of work, Wilbert is a dedicated cyclist, viewing the sport as essential mental hygiene. He commutes by bike whenever weather permits, covering significant distances through Dublin's varied terrain. Financially, he is cautious, prioritizing savings and investments over luxury goods, a habit formed during his early career in a recessionary market. While he is technically proficient and confident in his ability to solve complex problems, he remains acutely aware of the fragility of the AI ecosystem, constantly monitoring news feeds for potential disruptions. His life is a study in controlled chaos, where meticulous planning meets the unpredictable nature of emerging technology.

Background & daily life

A day in their life

Wilbert starts his day with a cold brew coffee and a quick scan of system alerts before his 6:00 AM cycling ride. By 8:30 AM, he is logged into his terminal, reviewing overnight token usage reports and fixing a minor drift in the Gemini integration that caused a few failed multilingual queries. The morning stand-up is brief, focusing on blockers rather than status updates. Afternoon hours are dedicated to writing unit tests for a new routing algorithm designed to switch between Claude and GPT based on cost-efficiency thresholds. He takes a long lunch break to walk along the Royal Canal, clearing his head. Late afternoon involves a review of the support team's draft responses generated by the AI, tweaking the prompt engineering to reduce hallucinations. He finishes work at 6:00 PM, leaving the office to hit the gym or meet friends, ensuring he separates work stress from personal time.

Lifestyle

Wilbert lives in a modest but functional apartment in North Dublin, sharing rent with a fellow developer to keep overhead low. His routine is rigid; he wakes at 5:30 AM for a 15-kilometer road cycling session before the city traffic peaks, using this time to decompress from screen glare. He is financially prudent, having maxed out his pension contributions early despite his age, preferring cash savings over flashy consumption. Socially, he prefers small gatherings or one-on-one coffee chats over loud pubs, often discussing tech trends or local cycling routes. His weekends are split between maintenance chores and deep-dive projects on personal coding side-projects, ensuring his skills remain sharp outside his employer's scope.

Work life

As the sole technical owner of the AI layer in a nine-person team, Wilbert operates with significant autonomy but immense responsibility. His days are consumed by maintaining the fragile bridge between the startup's core product and third-party LLM providers. He spends hours optimizing latency, managing API key rotation schedules, and parsing JSON logs to ensure billing accuracy. The pressure comes from the expectation that he must be the first line of defense when models go down or tokens spike unexpectedly. He collaborates loosely with the marketing team on campaign copy but handles all technical integrations alone, often working late to refactor legacy scripts before the next sprint cycle begins.

Relationships

Wilbert maintains close ties with his parents in Cork, who visit monthly for dinner, providing emotional stability. His professional network consists mostly of other engineers on LinkedIn and Discord servers focused on AI infrastructure. He has a partner, Sarah, a graphic designer, whom he met through a mutual friend; they balance each other's introverted tendencies. He rarely seeks advice from management, preferring to solve problems independently before escalating issues, which sometimes leads to misunderstandings about timeline estimates.

How they decide

Wilbert employs a research-heavy, data-driven decision-making process. He rarely commits to a new tool or strategy without first running a small-scale pilot or reviewing extensive documentation and community feedback. He values transparency and reproducibility, preferring solutions that offer clear metrics and measurable ROI. Peer influence matters only if backed by concrete performance data; he is skeptical of hype cycles and tends to wait for the dust to settle before adopting new technologies.

How they sound

Wilbert speaks with a measured, precise cadence, typical of an engineer who values clarity over flowery language. He avoids jargon unless necessary, preferring plain English to explain complex systems to non-technical stakeholders. His tone is neutral and objective, rarely showing overt excitement or frustration, even when dealing with server outages. He uses short, declarative sentences and often pauses to verify facts before speaking. He avoids vague qualifiers like 'maybe' or 'sort of,' opting instead for 'likely,' 'probable,' or specific percentages based on his data.