DayFlow

DayFlow

Gamifying Personal Productivity & Energy Tracking

Rashi Gupta  ·  January 2026  ·  dayflow.rashigupta.cloud

Next.js React Firebase Google Gemini n8n TypeScript

The Problem

Traditional Tracking Fails Because Logging Feels Like Work

"I'm exhausted at the end of every day, but my to-do list never ends."

⚠
High Friction

Dropdowns and forms feel like a chore. Users quit after 2-3 days.

📦
Data Silos

Data sits in the app without feedback. No insights, no action.

🔍
Missing Context

"I worked 8 hours" means nothing without knowing your energy state.

Old Approach
"Tracking time"
→
DayFlow Approach
"Optimizing energy"
👤 The "Exhausted Achiever"
Who Professional (PM/Dev), 24-35, ambitious but prone to burnout
Behavior Ends day exhausted but feels "unproductive." Uses lists but abandons them.
Pain "I don't know where my time goes." / "Logging takes too much effort."
Goal Feel accomplished, not just busy. Identify "time leaks".

Market Context

Mood Tracker Market
$1.5B → $5.7B by 2033 (16.5% CAGR)
Productivity Apps
$9.65B → $18B by 2030
Digital Journaling 1-Month Retention
72% for digital apps (vs 30% manual)

Market Analysis

No App Combines All Five Elements

Competitor
Strength
Critical Gap
DayFlow Advantage
Daylio
Fast icon-based input, 50M+ downloads
No AI summaries or coaching
Speed + AI intelligence
Reflectly
AI journaling, $59.99/yr premium
Manual text input, no activity tracking
Swipe input + activity data
Journey
Cross-platform, 60%+ retention
No mood/goal tracking
Unified all-in-one
planwith.ai
Goal tracking & planning
No mood or energy correlation
Goals + mood + activity
Toggl / Todoist
Established time tracking
Pure utility — no energy context, no AI
Context-aware coaching

Zero direct competitors offer: swipe-card input + mood tracking + goal alignment + AI daily summaries + calendar sync — all in one app.

Pricing Landscape
Freemium dominant. Premium tiers:
Daylio$35.99/yr
Reflectly$59.99/yr
Journey$39.99/yr
planwith.aiFree (beta)

My Approach

Validate Before Building — The 3-Phase Journey

Phase 1 — MVP

No-Code Validation

Airtable database + n8n automation + daily summary email at 11pm

Result: Failed

Process was boring and high-friction. "It didn't excite me as a user."

Airtable n8n
→
Phase 2 — Research

Tool Selection

Brainstormed with Gemini on features. Tested multiple AI platforms.

Base44Limited flexibility LovableGood, but constraints Firebase Studio✓ Selected
→
Phase 3 — Build

Native Web App

Full-featured PWA with gamified inputs and AI coaching pipeline.

Result: Still using it daily

Swipe cards made logging fun. AI coaching kept engagement.

Next.js Firebase Gemini

Key Learning: Validated the need with Phase 1, but proved UX is critical for retention. The no-code MVP saved weeks of wasted effort and showed that "delight" — not just functionality — is what keeps users coming back.

Feature Prioritization (ICE Framework)
Feature Impact Confidence Effort Score Status
Swipe UI 9 9 5 16.2 Live
AI Summary 8 8 4 16.0 Live
Voice Logging 7 5 8 4.3 Backlog
Social Sharing 4 3 6 2.0 Rejected

The Solution

Gamified Inputs — "Delight" Over "Utility"

Swipe Cards

Tinder-Style Swipe Cards

No forms. Activities appear as cards. Swipe right to log, left to skip. Reduces logging from a chore to a 30-second game.

Activity Log

Activity Dashboard + AI Gap Filler

Tap any activity to log time. Unlogged hours? AI suggests what you might have been doing with "Fill in the Gaps."

How are you feeling?
Rate your energy, productivity, and happiness
Energy 7
Productivity 5
Happiness 8

Mood & Energy Tracking

Energy, Productivity, Happiness — logged alongside activities. AI correlates: "You focus better in mornings when energy is above 7."

Intelligence Layer

From Raw Data to Active Coaching

1
Data Ingestion

Activity logs + mood scores from Firestore

↓
2
Orchestration (n8n)

Aggregates streams, sorts by time, triggers at 11 PM

↓
3
Google Gemini

System prompt: "You are a compassionate Life Coach. Analyze patterns."

↓
4
Coaching Insight

Personalized HTML email sent each night — not stats, coaching

Layer Technology
Frontend Next.js, React, TypeScript, Tailwind CSS, Framer Motion
Backend Firebase / Firestore (NoSQL)
AI Google Gemini (Life Coach prompt)
Orchestration n8n (workflow automation)
Example AI Insight

"Social media usage spiked when your energy dropped at 3 PM. Your focus peaks between 9-11 AM — that's your golden window for deep work."

Not stats — coaching
Proactive, not reactive
Sent automatically
Technical Challenges Solved
✗ Goals card off-screen → Removed fixed viewport height, native scrolling
✗ Swipe cards broken → Connected onDragEnd to state handlers
✗ Firestore queries failing → Created missing composite indexes
✗ Case sensitivity bugs → Character-by-character collection name audit

Product Tour

The Full Flow — Plan, Log, Analyze

Calendar View

Calendar — Plan ahead or look back

Swipe Logging

Swipe Cards — Log in 30 seconds

Activity Dashboard

Activity Log — Tap to track, AI fills gaps

Impact & Takeaways

What Changed & What I Learned

V1 — Airtable MVP
4/10

High friction. Quit after 3 days.

→
V2 — Native App
9/10

Swipe input. Still using it.

Success Metrics
North Star
Log Completion Rate
% days with evening reflection
Engagement
Bubble Cloud Time
Interaction depth
Retention
D30 Survival
Past the 2-3 day drop
1

Validate before building — No-code MVP saved weeks of wasted effort

2

UX beats features — The swipe interface isn't complex, but it's why users actually use the app

3

Context matters — Activity + Energy tracking is more valuable than activity alone

4

AI as coach, not reporter — Proactive insights beat passive data dumps

Roadmap

Phase 1 — Current

Baseline Audit

Gathering user feedback. Refining empty states and notification timing based on actual usage patterns.

Current Status
✓ Version 2 shipped
✓ Gathering feedback from network
✓ Iterating based on user pain points
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