Craig Hagenes

Why this persona fits the audience

Operating a B2B SaaS startup in Austin, TX, currently manually drafting and refining prompts for customer support automation and content generation across multiple LLMs. Uses free tiers of ChatGPT and Claude daily but spends significant time iterating on prompt structure to reduce hallucinations.

• Age: 31
• Location: Austin, Texas, USA
• Occupation: Software Engineer & Founder
• Income: $85,000 - $120,000
• Education: Bachelor's Degree
• Company size: 1
• Years in role: 2

““Every hour spent manually tweaking a prompt is an hour I'm not building the next big thing. The real trick is making the AI do the heavy lifting, reliably.””

Craig Hagenes, 31, is a quintessential indie hacker operating out of Austin, Texas. Armed with a Bachelor's degree in Computer Science, he transitioned from a traditional software engineering path two years ago to launch his own B2B SaaS venture. His company, currently a solo operation, focuses on AI-driven automation for customer support and content generation. Craig’s daily grind is deeply intertwined with the evolving landscape of large language models. He spends a considerable amount of his workday meticulously crafting, testing, and refining prompts for platforms like ChatGPT and Claude, aiming to minimize their tendency for factual inaccuracies – the infamous 'hallucinations.' This hands-on, iterative process is crucial as he leverages free tiers of these powerful AI tools to keep operational costs lean, aligning with his core value of cost-effectiveness. His income fluctuates, currently in the $85k-$120k range, reflecting the bootstrapping phase of his startup. He’s driven by a strong desire for autonomy and continuous learning, constantly seeking out new prompt engineering techniques and SaaS metrics to optimize his product. His approach to work is deeply analytical and pragmatic, viewing time as his most valuable, and limited, resource. He recently decided to prioritize enhancing the prompt quality for his customer support module over developing a new feature, believing that a more reliable AI foundation will ultimately accelerate customer satisfaction and reduce churn, a critical metric he closely monitors.

Background & daily life

A day in their life

Craig’s day typically begins around 6:30 AM with a quick review of overnight system logs and urgent emails. He then dedicates a solid two-hour block to his core task: refining LLM prompts for a new customer support automation feature. This involves writing, testing in ChatGPT and Claude, analyzing the output for inaccuracies, and iterating. Lunch is usually a quick, pre-prepped meal eaten at his desk. The afternoon is a mix of coding new features, responding to any customer inquiries, and researching emerging AI techniques or prompt engineering strategies. He often wraps up his 'official' workday around 7 PM, but frequently returns to his computer for another hour or two of focused work or learning in the evening.

Lifestyle

Craig lives in a moderately sized apartment in South Austin, preferring to optimize his living space for productivity rather than luxury. He wakes early, often before 7 AM, to get a head start on his work before the day's inevitable interruptions. His diet is functional, relying on meal prep and quick, healthy options to avoid losing precious work time. While he enjoys the occasional craft beer at a local brewery with a small circle of tech-minded friends, social events are often secondary to project deadlines. He’s mindful of his spending, prioritizing investments in tools that directly boost his startup’s output over discretionary purchases.

Work life

As the sole founder and engineer of his B2B SaaS, Craig's workday is a relentless cycle of development, customer interaction, and strategic thinking. He spends a significant portion of his time wrestling with LLMs, meticulously crafting and testing prompts for customer support bots and content generation tools. This involves deep dives into prompt engineering forums and experimenting with different LLM APIs. The pressure to deliver a polished product with limited resources means he’s constantly juggling feature development, bug fixes, and learning new AI techniques, often working late into the night.

Relationships

Craig's closest relationships are with a small group of fellow indie hackers and software developers he connected with online and occasionally meets up with in Austin. His family is supportive but doesn't fully grasp the nuances of his startup. He values their encouragement but seeks technical validation and brainstorming from his peer network.

How they decide

Craig approaches decisions methodically. He researches extensively, often comparing multiple options and reading user reviews or technical documentation. He prioritizes solutions that offer clear, measurable improvements in efficiency or cost-effectiveness, and he's willing to invest time in learning a new tool if the long-term benefits are significant. He’s not afraid to experiment, but he’ll rigorously test before fully committing.

How they sound

Speaks with a measured, often slightly technical cadence. Uses precise language, especially when discussing software or AI concepts. Avoids excessive slang, but may occasionally use industry jargon like 'hallucinations' or 'prompt engineering' naturally. Tends to be direct and to the point, especially when discussing work, but can become more expansive when explaining a complex technical idea.