Jana Casper

Why this persona fits the audience

She splits her week across three small client teams in the UK, each with 2 to 6 engineers building chat, search, or voice features. She standardizes how they review model failures, compare prompts, and track evaluation results using spreadsheets, notebooks, and shared dashboards. Her role is part hands-on engineering, part advisory.

• Age: 45
• Location: Manchester, UK
• Occupation: Fractional Head of AI
• Income: £90k
• Education: MEng in Software Engineering
• Company size: Clients range from 3 to 10 people.
• Years in role: 3

““It’s not enough for the AI to *seem* right; it has to demonstrably *be* right, and we need a solid, repeatable way to prove it, even with limited resources.””

Jana Casper's journey into the heart of AI fractional leadership began with a solid foundation in Software Engineering, culminating in an MEng from a respected UK university. She spent her early career in more traditional software development roles, gradually specialising in machine learning and natural language processing. The shift towards fractional work three years ago was a deliberate choice, driven by a desire for greater autonomy and the challenge of applying her expertise across diverse, early-stage ventures. She thrives on the 'puzzle-solving' aspect of optimizing AI models for specific business needs, particularly in chat, search, and voice applications. Her current role involves splitting her week across three small UK-based client teams, where she acts as their de facto Head of AI. This means she's deeply involved in the nitty-gritty: standardizing how they review model failures, meticulously comparing prompt effectiveness, and establishing clear, trackable evaluation metrics using a combination of spreadsheets, Jupyter notebooks, and shared data dashboards. This hands-on approach is balanced with advisory responsibilities, guiding these nascent companies on best practices and strategic AI development. Jana is driven by a strong sense of practicality and a genuine passion for teaching, aiming to empower her clients' engineering teams with robust evaluation methodologies. Her income of £90k reflects her specialized skills and the high demand for experienced AI fractional leaders. She lives in Manchester, where she balances her demanding work schedule with personal interests like hiking in the nearby Peak District and urban sketching, valuing efficiency and tangible outcomes in both her professional and personal life.

Background & daily life

A day in their life

Jana’s typical Tuesday begins around 7:30 AM with coffee and a quick scan of industry news. By 8:30 AM, she's logged into her work accounts, starting with Client B. Her morning involves a stand-up meeting with their two engineers, followed by a deep dive into their latest prompt iteration results, meticulously logging failures in a shared spreadsheet. She spends an hour refining their evaluation dashboard, ensuring it accurately reflects performance trends. After a quick lunch, she dedicates time to developing new test cases for a specific search query type before attending a brief sync with Client C’s lead engineer to discuss their voice model’s error rate. The late afternoon involves documenting her findings and recommendations for Client B, preparing them for a handover.

Lifestyle

Jana lives in a comfortable but not ostentatious Victorian terrace house in Didsbury, Manchester. Her mornings start with a strong cup of coffee and reviewing her task list, followed by a brisk walk or a quick yoga session. Her partner’s freelance schedule means they often eat dinner together, discussing their respective projects. Weekends are for longer hikes in the Peak District or catching up on reading, interspersed with urban sketching in local parks. She's mindful of her spending, preferring quality over quantity and focusing on experiences, like the occasional trip to a music festival, rather than accumulating possessions.

Work life

Her week is a carefully orchestrated juggling act. Mondays and Fridays are typically dedicated to client A (chat interface optimisation), Tuesdays to client B (search relevance tuning), and Wednesdays/Thursdays to client C (voice command accuracy). She spends a significant portion of her time developing and refining the evaluation frameworks – standardising prompt engineering best practices, creating robust failure analysis spreadsheets, and building shared dashboards to visualize performance metrics. She collaborates closely with small, often rapidly evolving engineering teams, acting as both a technical lead and a mentor, helping them navigate the complexities of AI model deployment and improvement.

Relationships

Jana has a close, supportive relationship with her partner, who understands the demands of freelance and fractional work. Her core group of friends consists of a few long-term university mates, also in tech, with whom she shares industry insights and commiserates about project challenges. She values their honest opinions and often bounces ideas off them.

How they decide

Jana is highly analytical and research-driven in her decision-making. She weighs evidence meticulously, often building small proofs-of-concept or running comparative tests before committing to a specific approach. She seeks out data, examines trade-offs carefully, and prioritizes solutions that offer clear, practical benefits and can be implemented efficiently within resource-constrained environments. Peer validation from trusted colleagues also plays a role, but only after her own rigorous assessment.

How they sound

Speaks with a clear, measured cadence. Her vocabulary is precise, favouring technical terms when appropriate but explaining complex concepts plainly. She avoids hyperbole and overly casual slang, preferring a professional yet approachable tone. Often uses phrases like 'Essentially,' 'The core issue is,' or 'From a practical standpoint.' She might pause thoughtfully before answering complex questions.