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This blog is where I break down how I think about products, users, and problem-solving from reimagining everyday tools to brainstorming new features for apps we use daily. I like to ask “what if?” and turn that curiosity into structured, user-centric thinking.

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SmartMeal, an AI that finally Understands My Eating Habits

  • Writer: Indu Arimilli
    Indu Arimilli
  • Jul 5
  • 2 min read

Updated: Oct 6

July 2025 | by Indu Arimilli


The Problem: I was meal-prepping for a version of me that doesn’t exist

Every Sunday, I’d confidently prep chickpea salad like the nutritionist I aspire to be.By Wednesday, I was eating cereal at 10 p.m.

Turns out, I was building meal plans for “Optimistic Indu,” not “Realistic Indu.”

So I came up with SmartMeal — an AI meal planner that adapts to your real-time cravings, not your Pinterest goals.


User Research

I ran a “food reflection study” (read: asked 6 friends what ruined their meal plans).Answers included: “vibe changes,” “no time,” “forgot the avocado,” and “my brain wanted chaos.”

After reading a TechCrunch piece on AI-driven nutrition startups, I saw a gap where everything was calorie-focused, not context-aware.


MVP — SmartMeal

Core Idea:A context-aware meal planner that adjusts your food recs based on mood, energy, and schedule — not just macros.

Features List:

  1. Mood detection — uses sentiment from journal/logs to infer comfort cravings.

  2. Context-aware planning — syncs with calendar to suggest realistic cook times.

  3. Dynamic swaps — auto-replaces recipes when ingredients are missing.

  4. Smart reminders — “You have 15 minutes and low energy. Make the tomato pasta.”

User Stories:

  • As a busy student, I want flexible meals so I don’t waste groceries or energy.

  • As an person with complex emotions, I want my AI to learn the difference between “I’m lazy” and “I’m tired.”


The Prompt

“Build a lightweight Python app that recommends meals based on time, energy, and emotion inputs. Use a simple CSV of recipes with metadata (time, complexity, vibe). Connect to Google Calendar for context and return one optimal meal per input set.”


The Visual

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Conclusion

  • Behavioral data is emotional data. What you eat reflects how you feel.

  • Personalization isn’t just about preference, it’s about permission to adapt.

My fridge has never been happier. And neither have I!

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