In the quiet of his childhood home in Roselle Park, New Jersey, Pratik Desai found himself drowning in 1,600 pages of medical notes. His mother, Smruti, had been diagnosed with stage 4 cancer in her small intestine, and the sheer volume of data—test results, physician notes, and medication schedules—was overwhelming. For Desai, a 34-year-old startup founder, the crisis was twofold: he was grieving the impending loss of his mother and struggling to navigate a healthcare system that often feels fragmented and opaque.
Desai did not have the time to learn a new programming language or hire a developer to build a custom health tracker. Instead, he turned to what is now being called “vibe coding”—the process of using natural-language prompts and AI platforms like Claude and NotebookLM to generate functional software without writing traditional code. By describing the tool he needed in plain English, Desai synthesized his mother’s medical records into a manageable workflow. The result was more than just an organizational tool; it became a critical part of her care.
In one pivotal moment, the AI flagged patterns suggesting his mother was suffering from complications of a pulmonary embolism. Desai did not rely on the AI alone; he ran the hypothesis by his cousin, a physician, and rushed Smruti to the hospital. Desai believes this workflow, which also helped him identify record mistakes and prepare targeted questions for appointments, saved his mother’s life three times. Smruti lived for 76 days following her diagnosis before passing away at age 67.
Desai’s experience is part of a growing movement of non-technical caregivers using AI tools for caregiving to solve hyper-specific problems that commercial software often ignores. From preventing financial scams to managing the repetitive behaviors of dementia, “vibe coders” are manifesting solutions in weeks—or even days—to ease the emotional and physical burden of elder care.
The Rise of the ‘Vibe Coder’ in Elder Care
Traditional software development requires years of study, but the emergence of Large Language Models (LLMs) and platforms like Cursor and Lovable has democratized the ability to create apps. For caregivers, this means the gap between identifying a need and deploying a solution has nearly vanished.
The applications are as varied as the challenges of aging. Hanna Miller, for example, developed a no-code Chrome extension to monitor her father’s online shopping; his dementia caused him to repeatedly order the same items, a common symptom of cognitive decline. Similarly, Ricardo Mota, a design head, created “Eterna,” a “memory vault” for his mother who lives with Alzheimer’s. The platform stores WhatsApp voice notes and chat histories, allowing the family to revisit memories and play songs that occasionally trigger a spark of recognition in his mother.
For some, the technology provides a voice where one was lost. Danesh Davar, 36, watched his mother lose her ability to type after suffering several hemorrhages in 2019. Unable to find affordable dictation tools, Davar took a short tutorial on vibe coding and built “Talkativ,” an app that allows his mother to dictate text across various platforms in over 50 languages. What began as a personal project has since grown, processing over 12,000 successful dictations for a small group of users.
Addressing the Vulnerabilities of Aging
Beyond medical management, caregivers are using AI to build defensive tools against the predatory nature of modern scams targeting seniors. Matt Sanner, a data manager in Tampa, witnessed his parents’ vulnerability firsthand after his mother-in-law nearly wired $5,000 to a scammer posing as a grandson.
Sanner used basic Python knowledge and AI prompts to create “ScamSkeptic,” an educational app tailored for his parents, Sue and Bob. By incorporating accessible design elements—such as oversized buttons and simplified lessons—Sanner provided his parents with a safe environment to learn how to identify fraudulent links and calls. His father, Bob, now frequently checks in with his son to verify his reactions to suspicious messages, creating a layer of human-AI collaboration that enhances his safety.
These efforts represent a shift toward “personalized AgeTech.” As Rick Robinson, vice president and general manager of the AgeTech Collaborative from AARP, notes, the hurdles to creating these tools were previously too high for the average person. Now, AI-fueled platforms allow “normies” to move quickly from a desperate idea to a working product.
The Clinical Risk: When AI Hallucinates
As a physician, I must emphasize a critical caveat: AI is not a doctor. While the stories of “vibe coding” are inspiring, the medical risks of relying on unverified AI output are significant. AI models are prone to “hallucinations”—confident but entirely false assertions—which can be lethal in a clinical setting.
A study published in Nature Medicine found that health advice from chatbots is frequently riddled with inaccuracies. In the most extreme cases, patients who trusted AI over their licensed physicians have suffered fatal outcomes. The danger is magnified for “vibe coders” who may lack the technical acumen to detect errors in the generated code or the medical training to spot a hallucinated diagnosis.
The success of Pratik Desai’s tool was not due to the AI alone, but because he used it as a hypothesis generator, which he then validated with a board-certified physician. The most effective use of these tools is as a supplement to, not a replacement for, professional medical judgment. No-code tools can introduce security vulnerabilities, potentially exposing sensitive health data to the public if not properly encrypted.
The Future of Personalized Care
Despite the risks, the demand for customized care tools is undeniable. Amanda Lazar, director of The Health, Aging, and Technology Lab at the University of Maryland, suggests that the rise of these home-grown apps highlights a systemic failure in the commercial market to provide the level of personalization that complex caregiving requires.
Some caregivers are already scaling their solutions. Srdjan Stakic, a cancer survivor, developed a system called Alvis using the Lovable platform. After integrating cameras and training the AI on nursing videos, he created a system capable of detecting falls and sending clipped footage and health summaries to EMS workers. What began as a way to monitor his own parents has evolved into a startup.
The trajectory of these tools suggests a future where caregiving is supported by a hybrid of professional medical care and bespoke, AI-generated support systems. For Pratik Desai, the mission continues; he is currently developing a free version of his medical synthesis tool to help other families navigate the terror of a terminal diagnosis.
Disclaimer: This article is for informational purposes only and does not constitute medical advice. Always seek the advice of your physician or other qualified health provider with any questions you may have regarding a medical condition.
As the legal and ethical frameworks for AI-generated healthcare tools continue to evolve, the next major checkpoint will be the integration of these “vibe-coded” solutions into formal clinical trials to determine their safety and efficacy at scale.
Do you use AI to help care for aging loved ones? Share your experiences and the tools you’ve found helpful in the comments below.
