DEV Community: Haseeb Arshad

Vectoria: Speak Math, See Motion

Haseeb Arshad — Mon, 16 Feb 2026 05:27:29 +0000

This is a submission for the GitHub Copilot CLI Challenge

What I Built

Vectoria is a Python-based CLI tool designed to lower the barrier to creating high-quality mathematical animations. It leverages the power of the Manim (Community Edition) library—made famous by Grant Sanderson of 3Blue1Brown—and combines it with LLM-driven code generation.

With Vectoria, you don't need to know the Manim API by heart. You can simply describe a mathematical concept in plain English (e.g., "Draw a unit circle and transform it into a square with side length 2"), and the tool automatically:

Generates the corresponding Manim Python code.
Applies a curated "3Blue1Brown" visual style (palette and typography).
Renders the animation into a high-quality video file using a single command.

Demo

You can find the source code and installation instructions here:
👉 GitHub Repository: Haseeb-Arshad/Vectoria

How it works:

# Generate a real animation from a prompt
python -m src.main create "Draw a rotating yellow dodecahedron"

# Test it out instantly without an API key using Mock Mode
python -m src.main create "test" --mock

My Experience with GitHub Copilot CLI

Building Vectoria was a masterclass in AI-pair programming. GitHub Copilot was instrumental in several key areas:

Boilerplate Acceleration: It helped set up the Typer CLI structure and Rich console integrations in seconds.
Subprocess Management: Handling the nuances of running the manim CLI via Python's subprocess (capturing errors and managing temporary files) was simplified significantly with Copilot's suggestions.
Complex API integration: Implementing the LLM generation logic and ensuring the prompt engineering was strict enough to produce valid Manim code was a breeze thanks to Copilot's ability to reason about the Manim structure.

The GitHub Copilot CLI challenge pushed me to think about how we can make specialized tools like Manim more accessible to everyone, and I'm thrilled with the result!

Credits: Haseeb-Arshad

TraceCLI - The Terminal's Black Box for Your Digital Life

Haseeb Arshad — Mon, 16 Feb 2026 05:24:02 +0000

This is a submission for the GitHub Copilot CLI Challenge

What I Built

Open your task manager right now. You'll see 30+ processes running. Close it. Now answer this: how many hours did you actually spend coding today? How much of that "research" was really just Reddit? When did you silently drift from Stack Overflow to YouTube, and how long before you noticed?

You can't answer that. Nobody can. That's the problem.

TraceCLI is a local-only, always-on activity recorder that lives in your terminal. It polls your system every second, logs every application switch, every browser tab, every CPU spike — and stores it all in a local SQLite database that never leaves your machine. No accounts. No cloud. No telemetry. Just raw, honest data about where your time actually goes.

What It Actually Records

Every second, TraceCLI captures:

The active window — process name, full window title, and the category it falls into (Development, Research, Productivity, Communication, Browsing, or Distraction)
Browser context — not just "Chrome is open," but the actual URL, the page title, and the domain. It reads browser history databases directly from Chrome, Edge, Brave, Firefox, Opera, and Vivaldi
Search queries — extracts what you searched for on Google, Bing, DuckDuckGo, YouTube, GitHub, Stack Overflow, PyPI, and npm
System resources — per-process CPU and RAM usage, tied to whichever app is in the foreground. When your laptop fans spin up during a "focus session," TraceCLI tells you exactly which tab is responsible
Focus sessions — timed deep-work blocks with real-time distraction detection, context locking, and a scored history you can review later

All of this lands in ~/.tracecli/trace.db — a single SQLite file you own completely.

A Concrete Example

Say it's 6 PM. You feel like you worked hard today but can't point to what you accomplished. You open your terminal:

$ tracecli report

TraceCLI prints a structured breakdown of your entire day:

┌─────────────────────────────────────────────┐
│  📅 Monday, February 16, 2026              │
│  ⏱️  Total Tracked: 7h 42m                  │
│  🧠 Productive:     5h 18m (68.8%)          │
│  🎮 Distractions:   1h 23m (17.9%)          │
│  💬 Communication:  1h 01m (13.3%)          │
│  🏆 Top App:        VS Code (3h 47m)        │
│  🎯 Productivity Score: ████████████░░░░ 69% │
└─────────────────────────────────────────────┘

You see that 1h 23m of distractions? Drill deeper:

$ tracecli app chrome --date 2026-02-16

Now you see every Chrome session, broken down by domain — 47 minutes on github.com (categorized as Research), 22 minutes on youtube.com (Distraction), 14 minutes on reddit.com/r/programming (Distraction), and 8 minutes on docs.python.org (Research). The window titles show you exactly which YouTube videos pulled you off track and when.

Want a bird's-eye view of your consistency over the last few months?

$ tracecli heatmap

A GitHub-style contribution grid fills your terminal — green squares for productive days, red for distraction-heavy ones, dark gray for days you didn't track. Your current streak, your longest streak, and an immediate visual answer to "Am I getting better or worse?"

How Categorization Works

TraceCLI uses a priority-based rule engine to classify every window switch:

Process-level rules first — code.exe is always Development. spotify.exe is always Distraction. There are 50+ built-in process rules covering IDEs, terminals, office suites, creative tools, games, and streaming apps.
Browser windows get title analysis — if the active process is a browser, TraceCLI inspects the window title with regex patterns. Stack Overflow, GitHub, MDN, docs.* → Research. YouTube, Netflix, Reddit, Twitter → Distraction. Google Docs, Notion, Jira → Productivity.
User overrides — disagree with a classification? Edit ~/.tracecli/user_rules.json and add your own productive/distraction keywords or process names. Your rules take the highest priority.

The productivity score is straightforward: (time in Development + Research + Productivity) / total tracked time × 100. No black-box weighting. You can verify it yourself by querying the database directly.

Focus Mode: Context-Locked Deep Work

$ tracecli focus 45 --goal "Build authentication module"

This starts a 45-minute focus timer that does more than count down. TraceCLI locks onto your current work window. The moment you switch to a different application or an unrelated browser tab, the system detects it:

Same app as your locked context? Timer stays green. Focus score holds.
System utility (Explorer, Task Manager)? Neutral — doesn't count for or against you.
Different app or unrelated tab? Interruption logged. Focus score drops. If AI is configured, TraceCLI evaluates whether the new tab is relevant to your stated goal — switching from your auth module to a tab about "JWT token best practices" might pass the relevance check, while "Top 10 Netflix shows" won't.

When the timer ends, you get a session summary:

Focus Score: 87% (Excellent)
Focused Time: 39m 11s
Distracted Time: 5m 49s
Interruptions: 3

Every session is saved. Run tracecli focus-history to see your trajectory over days and weeks.

The Node.js version also includes a Pomodoro mode (tracecli pomodoro) that auto-cycles through 25-minute work / 5-minute break phases, with a 15-minute long break every fourth cycle — all with the same context-lock scoring.

Natural Language Queries

Configure an AI provider (Gemini, OpenAI, or Claude) and you can talk to your data:

$ tracecli ask "How much time did I spend on VS Code this week?"

Behind the scenes, TraceCLI sends your question to an LLM along with the database schema. The LLM generates a SQL query, TraceCLI executes it (read-only — only SELECT statements are allowed), and the LLM summarizes the results in plain language:

You spent 18 hours and 34 minutes in VS Code over the last 7 days.
Your most active day was Wednesday (4h 12m), and your least active
was Sunday (42m). Your average daily usage is about 2h 39m.

You can ask anything your data can answer: "What's my most-used app after 10 PM?", "Show me my distraction patterns on Mondays vs Fridays", "Export yesterday's focus sessions to CSV."

The tracecli insights command goes further — it analyzes your last 7 days and generates a coaching digest: your top achievement, your biggest distraction pattern, an actionable suggestion, and week-over-week trends.

Auto-Start: The "Flight Recorder" Setup

On Windows, run:

$ tracecli autostart --enable

TraceCLI registers itself in HKCU\Software\Microsoft\Windows\CurrentVersion\Run and creates a VBScript launcher at ~/.tracecli/silent_start.vbs that starts the tracker with no visible console window. From that point on, every time you log into Windows, TraceCLI begins recording silently. A shutdown guard intercepts Windows close signals to flush any buffered data to the database before the system powers off.

No admin rights required. No services to manage. Disable it anytime with tracecli autostart --disable.

Other Commands Worth Mentioning

Command	What It Does
`tracecli live`	Real-time feed of window switches as they happen — useful for debugging or just watching yourself work
`tracecli timeline`	Hourly breakdown of your day — see exactly when you were productive vs. distracted
`tracecli week`	Weekly summary with daily totals and category distributions
`tracecli stats`	7-day trend of productivity scores
`tracecli urls`	Full browser URL history with domain-level grouping
`tracecli searches`	Every search query you made, organized by search engine
`tracecli system`	Top processes by CPU and RAM consumption, with current system load
`tracecli export`	Dump any day's data to CSV or JSON

Why Two Versions?

TraceCLI ships as two packages because each runtime has genuine strengths:

Python version (pip install tracecli) — the feature-complete edition. Rich terminal UI with full-color dashboards, heatmaps rendered with box-drawing characters, and the deepest browser integration. Uses the Rich library for terminal rendering and psutil for system monitoring. If you want every feature, this is the one.

Node.js version (npm install -g tracecli) — the modern, TypeScript-built edition. Uses active-win for reliable window detection and better-sqlite3 for fast synchronous database operations. Includes the full Pomodoro mode, the AI agent with interactive setup wizard, and a leaner dependency tree. If you prefer the npm ecosystem, start here.

Both versions share the same database schema, the same ~/.tracecli/ directory structure, and the same command interface. You can switch between them or even use both — they write to the same database.

Demo

1. The Daily Dashboard (`tracecli` or `tracecli report`)

A full-width terminal screenshot showing the day's summary panel — total time, productive time, top app, productivity score bar, and the category breakdown table.

![Daily Dashboard]

2. Consistency Heatmap (`tracecli heatmap`)

Track your digital engagement over months with a GitHub-style grid. Green squares represent productive days, red squares flag distraction-heavy ones.

![Heatmap]

3. Smart Focus Mode (`tracecli focus`)

Active monitoring that locks to your work window. The moment you switch to a distraction, TraceCLI catches it and your focus score drops in real time.

![Focus Mode]

My Experience with GitHub Copilot CLI

TraceCLI has 2,000+ lines of logic across categorization, database management, browser history extraction, system monitoring, and terminal rendering. Copilot CLI was a constant collaborator throughout.

Building the Categorization Engine

The rule engine in categorizer.py (and categorizer.ts) contains 50+ process rules, 30+ regex patterns for browser title analysis, and a priority system that resolves conflicts between them. Copilot helped me rapidly scaffold these pattern lists — I'd describe a category like "research tools," and Copilot would suggest process names and URL patterns I hadn't considered (like arxiv.org, crates.io, or GeeksforGeeks). It turned what would have been hours of manual research into minutes of iterative refinement.

SQLite Schema and Query Optimization

The database has 7 tables with 15 indexes. Copilot was instrumental in designing efficient queries — particularly the aggregation queries behind tracecli stats and tracecli heatmap, which need to join daily_stats with activity_log across date ranges while staying performant on months of data. It also suggested the WAL journal mode and the UNIQUE constraint on daily_stats(date) for upsert operations, which I wouldn't have reached for instinctively.

Terminal UI Layout

I wanted the output to feel like a dashboard, not a wall of text. Copilot helped me structure the Rich panels, tables, and progress bars in the Python version — getting the padding, alignment, and color thresholds right so that a productivity score of 72% renders as a satisfying green bar while 38% shows an urgent red. It also helped generate the ASCII art banner and the box-drawing characters for the heatmap grid.

Cross-Browser History Extraction

Reading browser history from locked SQLite databases (Chrome, Edge, Brave, Firefox — each with slightly different schemas and file paths) was one of the trickiest parts. Copilot provided the platform-specific paths (Local State, History, places.sqlite), the SQL queries for each browser's schema, and the approach of copying the locked database to a temp file before reading — a pattern I hadn't seen before but that works reliably even when the browser is running.

Windows System Integration

The auto-start mechanism required three coordinated pieces: a registry key, a VBScript launcher to suppress the console window, and a shutdown guard that intercepts WM_ENDSESSION messages to flush data before power-off. Copilot helped me navigate the winreg module, the VBScript syntax, and the ctypes calls for the Windows message pump — areas where I would have spent significant time reading Microsoft documentation.

Repositories & Installation

Python (Full-Featured Version)

pip install tracecli

📦 github.com/Haseeb-Arshad/trace-cli

Node.js (Modern TypeScript Edition)

npm install -g tracecli

📦 github.com/Haseeb-Arshad/tracecli-npm

Both versions are optimized for Windows. Start with tracecli start, let it run for a few hours, then explore your data with tracecli report. Enable tracecli autostart and forget about it — your terminal's black box will handle the rest.

TraceCLI turns the terminal into a mirror for your digital habits. GitHub Copilot CLI helped build every layer of it — from the database schema to the UI polish to the system-level integrations that make it invisible until you need it.

Synapse

Haseeb Arshad — Mon, 28 Jul 2025 00:29:30 +0000

This is a submission for the Algolia MCP Server Challenge

What I Built

Demo

TO BE UPDATED

How I Utilized the Algolia MCP Server

Key Takeaways

FrontDesk AI

Haseeb Arshad — Mon, 28 Jul 2025 00:23:14 +0000

This is a submission for the AssemblyAI Voice Agents Challenge

What I Built

Demo

To be UPLOADED

GitHub Repository

Technical Implementation & AssemblyAI Integration

Work from Office: A Studio Ghibli-Inspired Digital Workspace for a More Human Way of Working

Haseeb Arshad — Mon, 28 Jul 2025 00:05:15 +0000

This is a submission for Frontend Challenge: Office Edition sponsored by Axero, Holistic Webdev: Office Space

What I Built

I built Work from Office, a dream intranet homepage that reimagines the digital workspace through the whimsical and heartwarming lens of a Studio Ghibli film. My goal was to create an intranet that wasn't just a tool, but a destination—a place that fosters community, creativity, and a genuine sense of belonging. It’s a direct response to the challenge of creating the “perfect digital workspace,” one that not only enhances productivity but also enriches company culture.

This project directly answers the challenge prompts by delivering:

A Holistic Intranet Homepage: A fully functional and responsive intranet built with Next.js, React, and TypeScript. It features a rich set of widgets that are all beautifully integrated into the Ghibli-inspired design.
CSS Art as Office Culture: Instead of a single piece of art, the entire user interface is a love letter to a positive office culture. The Ghibli-inspired aesthetic, with its warm colors, gentle animations, and handcrafted feel, is my interpretation of a workplace that values warmth, nature, and personality over cold corporate efficiency. The entire UI is a piece of CSS art that brings the office to life.

Demo

Site Link:workfromoffice

GITHUB REPO: workfromoffice

TO BE UPLOADED SOON

Journey

The inspiration for this project came from a simple idea: what if the software we used every day sparked joy? I was tired of the cold, impersonal nature of most corporate tools and wanted to build something with a soul. The works of Studio Ghibli, with their emphasis on nature, community, and the quiet magic of everyday life, felt like the perfect antidote.

The Build Process:

I’ve structured the project to be modular and scalable, using a modern tech stack to deliver a robust and maintainable application.

Project Structure:

The project is organized into the following key directories:

app/: This is the heart of the Next.js application, containing all the pages and components. Each feature is a self-contained module within this directory.
application/: This directory holds the core application logic, including state management with Jotai, custom hooks, and type definitions.
infrastructure/: This directory contains configuration files and utility functions that support the application, such as the web worker for the timer and local storage utilities.
public/: This directory contains all the static assets for the project, such as images, fonts, and the timer web worker.

Technology Stack:

Framework: Next.js with React and TypeScript
Styling: Tailwind CSS with custom theming
State Management: Jotai
Rich Text Editing: Lexical
Drag and Drop: @dnd-kit/core
Charting: Recharts

Core Features:

“Work from Office” is packed with features designed to enhance both productivity and company culture. Here are some of the key highlights:

For Productivity:

My Day: A personalizable dashboard that gives you a quick overview of your schedule, tasks, and important announcements.
To-Do List: A drag-and-drop task manager that makes it easy to organize your work and stay on track.
Notepad: A rich-text editor for taking notes, brainstorming ideas, and drafting documents.
Timer & Session Log: A Pomodoro timer to help you focus, and a session log to track your work patterns and improve your productivity.
Bookmark: A tool to save and organize your favorite links.

For Culture & Collaboration:

The Teahouse & Village Well: These are dedicated spaces for non-work-related conversations, encouraging the kind of spontaneous social interactions that build strong teams.
The Kudos Board: A place for peer-to-peer recognition, fostering a culture of appreciation and positive reinforcement.
The Traveler’s Directory: This isn’t just a list of employees; it’s a vibrant, interactive passport that showcases each person’s unique skills, interests, and personality, helping to build connections across the organization.
Resource Center: A central hub for all your company resources, including a Company Wiki, HR Portal, IT Helpdesk, and Design System.
Announcements: A place to share company-wide news and updates.

For Personalization & Fun:

Ambience & Music Player: Create your perfect work environment with a selection of ambient sounds and your favorite music.
Settings: Customize the look and feel of your intranet with different backgrounds and sound themes.
Changelog: See what’s new and improved in the latest version of “Work from Office.”

What I'm Proud Of:

I'm incredibly proud of how the final product captures the feeling I was aiming for. It's more than just a collection of features; it's a cohesive experience that I hope will make users smile. I'm also proud of the technical challenges I overcame, like implementing the background timer with a web worker, building a rich text editor with Lexical, and creating a robust theming system with pure CSS.

This project was a joy to build, and I hope it inspires others to think differently about the tools we use to work and connect.

Q-Guardian: The AI-Powered Secure Code & Infra Auditor

Haseeb Arshad — Mon, 12 May 2025 07:01:42 +0000

This is a submission for the Amazon Q Developer "Quack The Code" Challenge: That's Entertainment!

What I Built

-- TO BE UPDATED SOON ---

Demo

Code Repository

How I Used Amazon Q Developer

Real-time Collaboration Platform with Contextual Permissions

Haseeb Arshad — Mon, 05 May 2025 07:52:54 +0000

This is a submission for the Permit.io Authorization Challenge: API-First Authorization Reimagined

-- soon to be updated --

Dynamic Access for Federated Learning System

Haseeb Arshad — Mon, 05 May 2025 07:52:18 +0000

This is a submission for the Permit.io Authorization Challenge: AI Access Control

--- Soon to be updated ---

AuthPilot: AI-Powered Authorization Policy Generation & Enforcement Platform

Haseeb Arshad — Mon, 05 May 2025 07:50:32 +0000

This is a submission for the Permit.io Authorization Challenge: Permissions Redefined

--- Soon to be updated ---

Snap-eye

Haseeb Arshad — Mon, 24 Mar 2025 07:00:41 +0000

This is a submission for the KendoReact Free Components Challenge.

DETAILS COMING SOON!

Introducing CodingCam: An IDE Extension and Dashboard to Track and Visualize Your Coding Activity

Haseeb Arshad — Mon, 24 Mar 2025 06:59:39 +0000

This is a submission for the KendoReact Free Components Challenge.

What I Built

As developers, we pour hours into coding—writing lines, debugging, and building projects—but how often do we step back to see our progress? That’s where CodingCam comes in. It’s a passion project I’ve been intensively crafting to help developers track their coding journey with precision and flair. Think of it as a personal coach for your coding life, capturing every keystroke and turning it into meaningful insights.

CodingCam consists of two key pieces:

CodingCam Extension: A custom-built extension for IDEs like VS Code that monitors your coding activity in real-time. It tracks metrics like time spent coding, languages used, projects worked on, and detailed progress—all stored securely in a backend database.
Interactive Dashboard: A React-powered frontend that brings your data to life with visualizations, leaderboards, and a stunning 3D global map showing where you (and others) code from.

This isn’t just about numbers—it’s about celebrating your growth, spotting patterns, and connecting with a global coding community. Whether you’re a solo coder or part of a team, CodingCam makes your coding story visible, actionable, and downright fun.

Key Features:

Real-Time Tracking: Captures your coding activity as it happens.
Detailed Analytics: Breaks down time spent by project, language, and day.
Leaderboard: See how your coding stacks up against others.
3D Global Map: Visualizes coding activity worldwide with an interactive twist.
User-Friendly Dashboard: A one-stop hub for progress and insights.

After months of refinement, CodingCam is ready to shine—and KendoReact made it possible.

Demo

The live demo and code repository are still in the works, but trust me, it’s worth the wait! Links coming soon:

Live App: [Coming Soon]
GitHub Repository:

Frontend: https://github.com/Haseeb-Arshad/CodingCam
Backend: https://github.com/Haseeb-Arshad/codingcam-backend
Extension: https://github.com/Haseeb-Arshad/codingcam-extension

Front Page: The landing page welcomes users with a clean, inviting design, showcasing the core concept of CodingCam and its benefits.

Login/Signup: Secure authentication pages using KendoReact's Input and Button components for a smooth user experience.

** Dashboard: ** The heart of CodingCam, displaying key metrics like total coding time, active projects, and recent activity. KendoReact's Chart components are used extensively here to visualize data.

Leaderboard: A gamified view of coding activity, ranking users based on their coding time. Badge components highlight top performers.

Reports: Detailed breakdowns of coding activity, filterable by date range (using DatePicker), project (DropDownList), and language.

Insights/Projects: Provides personalized recommendations and observations based on the user's coding patterns with a dedicated section to manage and track individual projects, with details on time spent and progress made.

Goals/Teams/Global Progress: (Future Feature) Allows users to set coding goals, track their progress towards them, functionality to collaborate and track coding activity within teams, and a visually stunning 3D map displaying coding activity across the globe.

Settings: Allows users to customize their profile, preferences, and notification settings.

How I Built It

CodingCam is built on a modern tech stack, combining the power of frontend and backend technologies:

Frontend: The interactive dashboard is built using React and Vite.js for a fast and efficient development experience. I chose TypeScript for type safety and improved code maintainability. The routing is handled by react-router-dom, providing a seamless navigation experience between different sections of the application (as seen in the code snippet you provided, with routes for Dashboard, Reports, Settings, etc.).
Backend: A Node.js server handles data storage, retrieval, and user authentication.
Extension: The core of CodingCam is the custom-built extension (for IDEs like VS Code). This extension is responsible for tracking coding activity in real-time. It meticulously monitors every keystroke and active coding session, detecting breaks after 7 minutes of inactivity. This ensures accurate tracking of both coding time and focused work periods.
Data Storage: User data is securely stored in a MongoDB database, managed using Mongoose. This NoSQL database is well-suited for handling the flexible and evolving data structure of coding activity.
Image Storage: User avatar images are uploaded and stored using Pinata Cloud, a service designed for storing content on the IPFS (InterPlanetary File System).
Authentication: Secure user authentication is implemented to protect user data and ensure privacy.

KendoReact Integration:

KendoReact Free Components were instrumental in building a polished and functional UI. Here's a deeper dive into how I used specific components:

Button: Used throughout the application for primary actions, such as submitting forms, triggering updates, and navigating between sections.
DropDownList: Enables users to filter data by selecting from predefined options, like projects or programming languages.
Input & TextBox: Used for various input fields, including search bars, form inputs, and settings configurations.
DatePicker: Allows users to select specific dates or date ranges for viewing historical coding data.
Dialog & DialogActionBar: Provides structured modal windows for displaying information, confirming actions, or presenting forms.
Popup: Used for displaying contextual information or menus.
Menu: offer a way to display hierarchical navigation options.
Avatar, AvatarFallBack, AvatarImage: Used to display user profile pictures, with fallback options for a consistent user experience.
Badge & BadgeContainer: Used to highlight user rankings on the leaderboard and to indicate activity streaks or achievements.
Loader: Provides visual feedback to the user during data loading, ensuring a smooth and responsive experience.
Chart, ChartSeries, ChartSeriesItem: These components are crucial for visualizing coding data, displaying trends, and providing insights into user activity. They transform raw data into easily understandable graphs and charts.
Slider: For adjusting the time range and checking the analytics.
Textarea: For jot notes and coding sessions.

The KendoReact components provided a consistent look and feel, excellent performance, and saved me a significant amount of development time. The extensive documentation and readily available examples made integration straightforward.

Benefits and Outcomes

CodingCam offers several benefits to developers:

Increased Awareness: By tracking coding activity, developers gain a better understanding of their work habits, identifying peak productivity times and areas for improvement.
Improved Productivity: The insights provided by CodingCam can help developers optimize their workflow, set realistic goals, and stay motivated.
Gamification: The leaderboard and badge system add a fun, competitive element to coding, encouraging developers to stay engaged and productive.
Community Building: The global progress map fosters a sense of community, allowing developers to see where others are coding and connect with fellow coders.
Data-Driven Insights: CodingCam provides data-backed insights into coding habits, helping developers make informed decisions about their projects and career development.

Challenge Qualification

This project qualifies for both prompts of the KendoReact Free Components Challenge:

Meet KendoReact: CodingCam utilizes more than 10 KendoReact Free components, showcasing their versatility and power in building a real-world application.
Delightfully Designed: The UI is designed to be both functional and aesthetically pleasing. The use of components of KendoReact and the combination of colors and styles gives an amazing look to the interface.

I'm incredibly excited about CodingCam and its potential to help developers worldwide track, understand, and improve their coding journey. I believe KendoReact played a vital role in bringing this vision to life.

DialogFlow-Form

Haseeb Arshad — Mon, 24 Mar 2025 06:39:31 +0000

This is a submission for the KendoReact Free Components Challenge.

What I Built

In a world dominated by rigid, impersonal forms, I’ve created an innovative solution that takes form-filling to the next level with AI-powered conversational interactions. DialogFlow is an AI-native platform that allows you to create dynamic, conversational forms and surveys. Instead of dealing with checkbox-filled forms, users can now engage in natural, human-like conversations while filling out forms, much like chatting with a real person. With a user-friendly dashboard and powerful AI integrations, this platform is designed to improve both the creation and submission process of forms.

Why does this matter? Because people are more likely to engage with a form that feels human. Instead of clicking “Other” and typing into a tiny textbox, respondents can just talk—and the AI listens, adapts, and even asks follow-ups. It comes with a sleek dashboard to track analytics, manage forms, and dive into responses—all designed to make your data collection smarter and more enjoyable.

Key Features:

Conversational UI: A chat interface that asks questions naturally, one at a time.
AI-Powered Interaction: Adapts to answers, asks follow-ups, and keeps the tone friendly.
Prompt-Based Creation: Write simple prompts, and let the AI handle the rest.
Analytics Dashboard: Monitor views, responses, and completion rates with ease.
This isn’t just a tool—it’s a new way to connect with your audience.

Demo

Ready to see it in action? Check out the live demo here:
https://dialogflow-form.vercel.app/

Want to peek under the hood? The source code is available on GitHub: https://github.com/Haseeb-Arshad/dialogflow-form

Here are some screenshots to give you a taste of the experience:

The hero section of DialogFlow-Form, sparking curiosity and action

Crafting a form is as easy as writing a few prompts—AI does the heavy lifting.

Personalization of the forms

Scheduling of the Forms

Integrating AI into forms

The dashboard: your hub for insights and control.

These visuals showcase a user-friendly, modern app that’s as delightful to use as it is to build.

KendoReact Experience

Building DialogFlow-Form was a breeze thanks to KendoReact Free Components. I integrated at least 10 of these powerful UI tools to create a seamless, professional experience. Here’s how they brought the project to life:

DropDownList: Simplified selecting response types (e.g., text, yes/no) in the form creator.
Button: Powered actions like saving forms, adding questions, and toggling statuses with a polished look.
Input: Made text entry (like form titles) intuitive and accessible.
Textarea: Perfect for multi-line inputs, such as prompts and AI instructions.
Slider: Added an interactive way to tweak AI settings like temperature and max tokens.
DatePicker: Enabled scheduling forms with start and end dates effortlessly.
Badge: Displayed form statuses (active, paused, expired) with clear visual cues.
Loader: Provided feedback during actions like copying share links, enhancing UX.
Chart, ChartSeries, ChartSeriesItem: Visualized response trends in the dashboard, turning data into insights.
KendoReact’s components didn’t just save time—they elevated the app’s usability and aesthetics. The Slider, for instance, made AI configuration feel playful yet precise, while the Chart components turned raw analytics into actionable visuals. The documentation was a lifesaver, ensuring smooth integration and customization. With these tools, DialogFlow-Form feels both robust and approachable—a win for both developers and users.

AIm to Impress

What sets DialogFlow-Form apart is its GenAI integration, making it a standout for the AIm to Impress category. The AI isn’t just a gimmick—it’s the heart of the conversational experience. Using a model like GPT-4o or o3-mini, the app takes user-written prompts and spins them into dynamic, human-like dialogues.

Here’s how it works:

Prompt-to-Conversation: Write a prompt like “How was your day?” and the AI crafts a chat flow, asking follow-ups like “What made it great?” based on the response.
Adaptive Interaction: The AI adjusts its questions and tone in real-time, ensuring a natural exchange.
Customizable Behavior: Users can tweak the AI’s model, temperature (creativity), and max tokens (response length) via an intuitive settings panel.
In the form creator, I built an AI configuration section where users can fine-tune these parameters. A higher temperature might spark more creative responses, while a lower one keeps things concise—perfect for surveys needing focus. This flexibility ensures the AI aligns with each form’s unique goals, whether it’s casual feedback or detailed research.

The result? Respondents enjoy a form that feels like a conversation with a friend, boosting engagement and completion rates. Behind the scenes, the AI’s seamless integration (nod to a clean React setup!) makes DialogFlow-Form a powerful blend of technology and human connection. Moreover, I will add the audio, visuals, polls to make it more interactive and engaging.

DialogFlow-Form isn’t just a project—it’s a solution. It tackles a real problem (form fatigue) with a creative twist (AI-driven conversations), all while showcasing KendoReact’s versatility. The app’s usability shines through its intuitive design, the AI integration pushes boundaries, and the 10+ KendoReact components ensure a polished, accessible experience. Whether you’re a developer looking to streamline form-building or a user tired of clunky surveys, DialogFlow-Form delivers.

DEV Community: Haseeb Arshad

Vectoria: Speak Math, See Motion

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Demo

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My Experience with GitHub Copilot CLI

TraceCLI - The Terminal's Black Box for Your Digital Life

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Auto-Start: The "Flight Recorder" Setup

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2. Consistency Heatmap (tracecli heatmap)

3. Smart Focus Mode (tracecli focus)

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Synapse

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FrontDesk AI

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Work from Office: A Studio Ghibli-Inspired Digital Workspace for a More Human Way of Working

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Real-time Collaboration Platform with Contextual Permissions

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DialogFlow-Form

What I Built

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AIm to Impress

1. The Daily Dashboard (`tracecli` or `tracecli report`)

2. Consistency Heatmap (`tracecli heatmap`)

3. Smart Focus Mode (`tracecli focus`)