Software buyers: target customers (?)

Ramiro Steuber

Ramiro Steuber is a 31-year-old Founding Engineer at a nascent SaaS startup in Austin, Texas, specializing in augmenting customer support workflows with LLM memory. Holding a B.S. in Computer Science, he's been deeply immersed in the startup world for the past two years, driven by a desire to build impactful technology. His current role is uniquely demanding; he is the sole full-time engineer at a 6-person company, responsible for the entire technical implementation of their AI support assistant. Ramiro's approach to managing conversation state is pragmatically DIY, currently relying on a patchwork of Airtable for structured data, custom Python scripts for processing, and Notion for prompt engineering snippets. He meticulously crafts manual rules to dictate what information the AI should retain between customer interactions, a testament to his focus on customer usefulness and low operational overhead. He believes strongly in shipping quickly and iterating based on real user feedback, a principle honed from his experiences in previous software development roles. His income of $145k base plus equity reflects his critical position and the high-stakes environment of a seed-stage venture. Ramiro is intensely focused on technical clarity, ensuring the underlying architecture is sound and maintainable, even under the pressure of rapid development. He views time as a critical, finite resource, both for himself and for the company's runway, which fuels his drive to optimize workflows and eliminate inefficiencies. While passionate about the technical challenges, he's also keenly aware of the financial realities, prioritizing long-term company value through his equity stake over immediate personal windfalls, though he does save diligently.

Kerry Grant

Kerry Grant is a thirty-four-year-old Product Manager based in London, currently steering a specialized four-person pod within a mid-market B2B SaaS company. With an M.A. in Human-Computer Interaction, she possesses a rare blend of theoretical depth and gritty execution capability. Her current mandate is ambitious yet under-resourced: prototyping an AI-powered onboarding assistant capable of remembering account details across user sessions. The reality of this role is defined by a significant gap between vision and resources. While the engineering team is only partially engaged due to competing legacy obligations, Kerry has taken it upon herself to wire the context logic manually. She spends hours constructing intricate spreadsheets and documenting shared workflows, effectively acting as both the architect and the builder of the prototype's logic layer. Her work environment is a microcosm of the modern startup struggle: a small monthly AI budget forces her to rely on a lightweight competitor's API and free tools, necessitating a level of ingenuity that borders on scrappy. She is deeply invested in the concept of 'memory infrastructure' for AI, driven by a genuine belief that the industry is moving toward agents that understand context rather than just processing tokens. However, this conviction clashes with the daily friction of keeping stakeholders aligned and managing the cognitive load of manual data mapping. Kerry's professional history reflects a steady climb from UX researcher to product leadership, marked by a consistent refusal to accept 'good enough' when it compromises user experience. She is known for her ability to translate abstract AI concepts into concrete, testable user flows. Despite the chaos of her current project, she maintains a disciplined approach to her personal life, balancing her career ambitions with a love for travel, cycling, and structured notetaking systems. Her recent decisions have been driven by pragmatism; she chose to delay a full engineering hire in favor of validating the concept herself, betting that the manual process would yield faster insights than waiting for a scaled solution. This trade-off highlights her core philosophy: measurable outcomes matter more than polished processes when the stakes are learning.

Max Schrader

Max Schrader, 28, is the quintessential indie hacker, pouring his M.Sc. in Software Engineering expertise into a solo venture in Berlin. His startup, a niche AI drafting tool for e-commerce sellers, is his singular focus. The core challenge, and his current obsession, lies in building a 'manual memory handling' system. This involves a complex, self-devised architecture combining spreadsheets, Supabase tables, and custom logic to track user preferences, brand voice, and edit history – a testament to his resourcefulness and commitment to craftsmanship. His decision-making is heavily constrained by a tight runway, forcing a pragmatic approach where every feature and technical choice is scrutinized for its immediate impact and cost-efficiency. He lives frugally in a modest apartment, viewing his €58k annual draw as a necessary but carefully managed burn rate. Max thrives on the independence his solo founder status affords him, relishing the ability to iterate rapidly and steer his product's direction without external bureaucracy. He spends his days immersed in code, wrestling with the intricacies of AI context management and user data persistence. His evenings are often dedicated to further research or refining his understanding of LLM architectures, fueled by strong espresso. He’s driven by a deep-seated desire to build something lasting and technically elegant, even if it means sacrificing a conventional social life. The pressure is palpable, but so is the satisfaction of solving complex problems with his own hands. He recently spent two weeks optimizing database queries to shave milliseconds off response times, a seemingly minor improvement that he believes is critical for user retention and demonstrates his dedication to performance and efficiency. He’s also actively experimenting with different vector database solutions on a small scale, trying to find a balance between cost and capability before committing significant resources.

Howard Heller

Howard Heller, 39, is the Technical Director and co-founder of a small automation agency based in Manchester, UK. Holding a B.Sc. in Information Systems, he transitioned from a brief stint in corporate IT to establish his own firm five years ago, focusing on AI-driven solutions for local professional services. His agency, currently a lean team of three, specializes in developing bespoke internal chat assistants designed to streamline client interactions and internal workflows for law firms, accountancies, and consultancies. Howard's approach is deeply rooted in practicality and reliability; he understands that his clients, often operating on tight budgets, need solutions that deliver tangible efficiency gains without excessive cost or complexity. This ethos directly shapes his team's current technical stack and operational challenges. For managing the crucial aspects of AI memory and context – ensuring assistants recall relevant information and disregard the irrelevant – they currently rely on a patchwork of methods. This includes meticulously maintained, hand-updated prompt documentation, exporting conversation logs to CSV files for manual analysis and refinement, and a recent, somewhat fraught, trial of a competitor's product on a single client account. The competitor solution proved to be expensive and difficult to integrate seamlessly, reinforcing Howard's pragmatic, cost-conscious approach. He's driven by a desire to build robust, dependable systems, valuing client trust above all else. His personal life is centered around his partner, Emma, their young daughter Sophie, and a passion for Manchester City football. He balances his demanding professional life with a commitment to family and a quiet enjoyment of good coffee and reading, always seeking ways to optimize processes, both in his work and his personal routines.

Lia Sanders

Born and raised in the Netherlands, Lia developed an early fascination with how complex systems operate, a curiosity initially fueled by observing the intricate workings of her father's clock repair shop. This led her to pursue a Master's degree in Artificial Intelligence at the University of Amsterdam, where she excelled in coursework focused on machine learning and natural language processing. Her academic journey was marked by a meticulous approach to research, often spending late nights debugging code for her thesis on efficient information retrieval. After graduating, she joined a burgeoning AI startup, drawn by the promise of working on cutting-edge agent technology with a small, impactful team. She quickly became integral to the product development, specifically focusing on the challenging architecture of the platform's memory layer. This role demands a constant tightrope walk between implementing advanced AI features and adhering to strict cost constraints for their operational clients. Lia’s personal life is equally structured; she dedicates time to running, finding it a crucial outlet for stress and mental clarity, and regularly visits museums to appreciate human ingenuity across different eras. She lives modestly, prioritizing saving for future security and investing in experiences that enrich her understanding of the world. Her career trajectory is guided by a desire to build robust, scalable, and efficient systems, viewing each technical challenge as an opportunity to refine her craft and contribute to the evolving landscape of AI.

Eleanor Lubowitz

Eleanor Lubowitz, 36, has carved out a niche for herself in the customer support landscape, currently managing a team of 12 agents in Dublin. Her journey into operations management began after a few years on the front lines of customer service, where she developed a keen eye for inefficiencies and a deep empathy for both customers and support staff. Armed with a B.A. in Business Administration, she transitioned into a team lead role before taking on her current position four years ago. Her focus has always been on building stable, high-performing teams, a value deeply ingrained from her upbringing in a close-knit family. She lives by the principle that simplicity is the ultimate sophistication, especially when dealing with technology adoption among diverse skill sets. Her current project involves piloting AI macros for drafted replies and case summaries, a move aimed at improving response times and agent efficiency. This initiative is particularly challenging because her team comprises many non-technical individuals, necessitating a workflow that is intuitive and requires minimal training. She meticulously tracks the AI's output, using spreadsheets and shared inbox labels to store recurring customer facts, a system she acknowledges is becoming increasingly cumbersome. Eleanor is driven by a desire for accountability and excellent customer care, seeing them as intertwined. She’s pragmatic about her career, aiming for steady growth rather than rapid advancement, and is conscious of her financial planning, saving diligently for future security. Her personal life is grounded by her dog, Finn, and a small circle of close friends, providing a necessary balance to the demands of her role. She actively seeks out podcasts and articles on process improvement and customer support tooling, viewing continuous learning as essential for staying effective in her field.

Cory Quigley

Cory Quigley, 42, is a seasoned Independent AI/Data Consultant based in Chicago, co-running a two-person practice specializing in prototyping AI search and assistant flows for enterprise clients. Holding an M.S. in Data Science, his career has been a deliberate progression from data analysis to architecting sophisticated AI solutions. He co-founded his practice seven years ago with his business partner, Alex, seeking greater autonomy and the ability to focus on cutting-edge AI applications. His income of $168k reflects his specialized expertise and the value he brings to clients in sectors like finance and healthcare. Cory's professional journey has been marked by a commitment to technical rigor and client results, driving him to constantly explore and integrate new technologies. He's particularly adept at translating complex AI concepts into tangible, demonstrable prototypes. His current work heavily involves showcasing how AI can maintain context across user sessions, a critical differentiator for many enterprise applications. To achieve this in client demos, he strategically utilizes a competitor's memory layer on paid trials, supplementing it with meticulously crafted Notion pages and JSON fixtures. This hands-on approach allows him to illustrate the persistence of context effectively, even while he's evaluating alternative solutions. He views this process not just as a demonstration tool, but as an ongoing research effort to understand the practical limitations and potential of current memory technologies. His decision to use a competitor's tool in this manner highlights his pragmatic approach to client delivery and his commitment to showcasing the best possible outcomes, even if it means leveraging external resources. He's driven by intellectual curiosity and a desire to push the boundaries of what's possible with AI, always with an eye toward practical, impactful applications for his clients. His financial habits are disciplined, focused on long-term security and investments, but he allows for strategic spending on high-quality tools and professional development that directly enhance his consulting capabilities.

Cleofe Poggi

Cleofe Poggi is a 33-year-old Operations Analyst based in Milan, currently serving as the critical linchpin for a specialized seven-person internal tooling group within a mid-sized financial services firm. Holding a B.A. in Economics, she has spent the last four years refining her role from a general administrator to a specialist in data governance and process optimization. Her position is defined by a unique constraint: her team is tasked with piloting internal AI assistants for policy lookup and meeting summarization, yet they lack the technical infrastructure to manage the necessary context automatically. Consequently, Cleofe has become the sole manual curator of 'allowed context,' a labor-intensive process where she translates complex, evolving financial policies into rigid logic tables stored in spreadsheets and a shared drive. This manual oversight is her primary daily burden, consuming nearly 40% of her workweek. Living in the vibrant Isola district with her partner, Cleofe leads a life that mirrors her professional philosophy: orderly, intentional, and grounded. Her income of €49k allows for a comfortable middle-class existence, though she remains acutely aware of the need for financial prudence given the volatility of the tech sector. She channels her energy into hobbies that reinforce her love for structure and detail, such as designing complex recipes and tending to her urban garden. While she possesses a moderate level of openness to new experiences, her low score in neuroticism allows her to remain steady amidst the chaos of a rapidly digitizing workplace. Recently, Cleofe made the decision to implement a more rigorous version control system for their manual rule sets after a minor error caused a false positive in an AI summary. This incident highlighted the fragility of their current setup. Despite the temptation to adopt flashy new software solutions, she remains skeptical of quick fixes, preferring to deepen her understanding of their existing tools. Her goal is not merely to survive the current transition but to engineer a robust, scalable framework that eventually renders her manual intervention obsolete, freeing her to focus on higher-level strategic analysis.

Balaaditya Embranthiri

Balaaditya Embranthiri, a 29-year-old bootstrapped founder in Pune, embodies the spirit of resourcefulness and pragmatic innovation. He grew up in a middle-class household, where financial prudence was a daily lesson, instilling in him a deep appreciation for frugality and self-reliance. His academic journey led him to a B.Tech in Computer Engineering, where he excelled, driven by an insatiable curiosity for how things work and an innate ability to learn quickly. Upon graduating, he spent a few years in a software development role, gaining practical experience and observing firsthand the operational challenges faced by Indian Small and Medium Businesses (SMBs). This exposure, coupled with his own lean upbringing, sparked the idea for his current venture: an AI-powered lead-qualification bot designed to be affordable and effective for the Indian market. He founded his company three years ago, operating initially from his parents' home to minimize overhead. Today, he manages a lean operation with three remote contractors, focusing on delivering a product that addresses a critical pain point: efficient lead management. His AI bot, while sophisticated in its aim, relies on a cost-conscious architecture. The 'memory' feature, crucial for recalling lead interactions, is a testament to his ingenuity, currently managed through a combination of manual spreadsheet tagging, carefully crafted webhook rules, and judicious use of low-cost API credits. He constantly navigates the tightrope between functionality and budget, meticulously tracking every expenditure. This approach reflects a broader philosophy: maximize value and impact with minimal resources. His income of ₹24L annually, while comfortable, is largely reinvested into the business, underscoring his commitment to growth over personal luxury. Balaaditya is not driven by a desire for status or rapid, VC-funded expansion; rather, he seeks to build a sustainable, profitable company that genuinely solves problems for his target demographic, demonstrating a quiet confidence in his ability to achieve this through hard work and smart decisions.

Pénélope Guillot

Pénélope Guillot grew up in Lyon, the daughter of a pharmacist and a high school teacher, instilling in her a deep appreciation for both scientific rigor and clear communication. Her academic path led her to Paris for her M.Sc. in Digital Product Management, where she became fascinated by the potential of AI to streamline complex processes, particularly in sectors like healthcare. Upon graduation, she joined her current health-tech startup, drawn by its mission and the opportunity to work on cutting-edge AI applications. Her role as an AI Product Analyst is demanding, requiring her to be both strategically minded and meticulously hands-on. She is acutely aware of the company's financial constraints, which means every decision about tooling or experimentation is scrutinized. Her current focus is on optimizing the AI intake assistant's ability to retain crucial patient information across conversations without incurring prohibitive computational costs. This involves a painstaking process of manual prompt testing, detailed analysis of token usage, and close collaboration with the engineering team, who are stretched thin. She recently championed a more structured approach to documenting prompt variations and their performance, moving away from ad-hoc notes to a more systematic, albeit still spreadsheet-based, system. Pénélope views time as a valuable, finite resource, both for herself and her team, and is constantly seeking ways to improve efficiency without sacrificing quality or ethical standards. Her income of €54k allows for a comfortable but not extravagant lifestyle in Paris, reinforcing her pragmatic approach to spending and her focus on long-term career growth over immediate financial gains. She sees her current role as a critical learning phase, building foundational experience in a high-demand field under challenging but rewarding conditions.