I lost 10kg in 6 months by logging every meal to ChatGPT. then i had a kid, gained it back, and now im doing it again
By Holidays in Europe / April 28, 2026 / No Comments / Uncategorized
Transforming Diet Management: How AI-Assisted Meal Logging Led to Successful Weight Loss and a New Approach to Nutrition Tracking
Over the past few years, many individuals have struggled to find sustainable ways to monitor their dietary habits and achieve their health goals. A recent personal experience illustrates how leveraging artificial intelligence can revolutionize food logging, making it both more engaging and effective. This article explores one individual’s journey of losing 10 kilograms over six months through AI-powered meal logging, the challenges faced during life changes, and a new innovative solution designed to fit into a busy, evolving lifestyle.
The Power of AI in Food Logging
Approximately a year ago, I embarked on a journey to better understand my eating patterns by utilizing ChatGPT for meal logging. Instead of conventional apps that often felt cumbersome, I simply typed descriptions like “two slices of pepperoni pizza, a beer, and a handful of olives,” and asked for calorie estimates. I then recorded daily totals into a notes app. Over six months, this method helped me shed about 10 kilograms.
This approach was a stark contrast to previous attempts using traditional food tracking apps like MyFitnessPal. The latter often felt tedious—barcodes, scanning, and database navigation quickly grew tiresome. ChatGPT, with its conversational interface, offered a more natural and less burdensome experience.
Key Lessons from the Experience
1. Precision Isn’t Everything
While ChatGPT’s calorie estimates aren’t perfectly accurate—probably off by 10-20%—this small margin doesn’t detract from their utility. What’s crucial is the consistency. If the AI tends to overestimate pizza calories by a similar margin each time, it creates a reliable trend line. This allows users to gauge whether today’s intake is higher or lower than previous days, fostering meaningful insights despite minor inaccuracies.
2. Interactivity Enhances Engagement
A significant advantage was the interactive nature of the process. When an estimate seemed off, I simply responded with a correction—”the portion was smaller, perhaps half that”—and ChatGPT adjusted its calculations accordingly. This back-and-forth mimicked a personalized coaching experience that no traditional database-based app could easily replicate.
3. Photos as a Valuable Tool
Taking photos of my meals proved surprisingly effective. Asking ChatGPT to analyze images for food items consistently yielded accurate identifications, with portion sizes being the main challenge. Correcting those in real time further refined the estimates. Visual data enhanced my understanding and engagement without adding complexity.
4. Workflow Limitations
Despite its strengths, the process was not without frustrations. I lacked a history of previous meals, making repetitive logging cumbersome; there was no straightforward way to recall or duplicate past entries. Conversations could become long and unwieldy, requiring resets and re-explanations of my preferences. Additionally, minor discrepancies in total calculations sometimes appeared. Still, the overall value kept me committed.
The Impact of Lifestyle Changes
Over the course of six months, this logging approach helped me lose 10 kg. Interestingly, the act of regular logging increased my awareness about food, prompting healthier choices. The process itself created a form of accountability, with focused attention on eating habits.
However, life threw a curveball—the birth of my second child. Stress, sleep deprivation, and unpredictable schedules led me to abandon tracking altogether. Naturally, I gained about half of my lost weight back within a few months. It became clear that the existing workflow’s overhead—manual entry, resetting conversations—was incompatible with the demands of a hectic family life.
Reimagining Food Logging for the Modern Lifestyle
Recognizing the limitations, I decided to develop a more streamlined solution. This new system builds upon the same AI foundations but offers an interface tailored to everyday life. Users can:
- Input meals by typing descriptions or capturing photos
- Receive instant calorie estimates
- Correct estimates quickly if needed
- Access a searchable meal history
- Duplicate meal entries effortlessly, such as repeating yesterday’s lunch with a single tap
Designed with ergonomic simplicity and minimal friction, this approach ensures consistency even during stressful periods. I’ve named it Excaloricate—a playful nod to the phrase “excommunicate calories,” symbolizing a more liberated and engaging way to manage dietary habits.
Practical Takeaways for Enthusiasts and Developers
For those interested in recreating or customizing such tools, it’s worth noting that building a similar application is achievable over a weekend. The OpenAI API simplifies integration, allowing developers to craft interfaces aligned with personal workflows. This makes AI-assisted health tracking accessible, customizable, and more sustainable.
In Conclusion
The integration of AI into personal health routines signifies a promising frontier. By reducing friction and personalizing the experience, individuals can achieve meaningful progress without feeling overwhelmed. Whether you’re seeking to lose weight, develop better eating habits, or just understand your food intake more deeply, AI-powered tools like ChatGPT offer flexible, engaging solutions adaptable to real-life challenges.
If you’re curious about the project I built—Excaloricate—feel free to explore or develop your version. The future of health tracking is digital, interactive, and entirely customizable.