Building Susan AI: My Journey of Creating a Personal AI Assistant

Susankar Karmakar — Thu, 08 Oct 2026 16:53:44 +0000

I built Susan AI as an experiment to explore what a practical, personal AI assistant could look like when it is designed around real-world workflows rather than just conversation.

🔗 Live Demo: https://susan-ai.vercel.app/

💻 GitHub: https://github.com/susankarkarmakar-pixel

Why I Started Building Susan AI

The easiest way to use AI today is to open a chatbot, type a question, and get an answer.

But while using AI for different tasks, I kept asking myself a different question:

What if an AI assistant could become a practical workspace instead of simply being a chatbot?

I wanted something that could help me with:

Learning and research
Writing and editing
Programming
Understanding documents
Summarizing information
Brainstorming ideas
Working with structured data
Exploring the web
Building AI-assisted workflows

That idea eventually became Susan AI.

Susan AI is my personal AI assistant project and an ongoing experiment in combining generative AI, web development, productivity tools and agent-style workflows.

What Is Susan AI?

Susan AI is a web-based AI assistant designed to provide a unified environment for interacting with AI.

The project is accessible directly from a browser:

👉 https://susan-ai.vercel.app/

Instead of thinking of it as another ChatGPT clone, I am developing Susan AI as a personal AI workspace.

The long-term goal is to make the assistant useful across multiple categories of work:

                    Susan AI
                       │
       ┌───────────────┼────────────────┐
       │               │                │
    Learning        Creating         Building
       │               │                │
   Research         Writing          Coding
   Study            Content          Debugging
   Analysis         Reports          Development
       │               │                │
       └───────────────┼────────────────┘
                       │
                 AI Workflows
                       │
              Personal Productivity

The Core Idea

Most AI assistants begin with:

Question → Answer

I am interested in exploring something broader:

Goal → Context → AI reasoning → Tools → Output → Workflow

For example, instead of asking an AI only:

"What is climate change?"

a more useful assistant could help a user:

Understand the topic
Research relevant information
Summarize documents
Organize notes
Generate a report
Create study material
Continue working with the result

That shift—from conversation to workflow—is one of the main ideas behind Susan AI.

Current Capabilities

Susan AI is being developed around several practical use cases.

1. AI Chat

The foundation is an AI conversation interface.

Users can ask questions, brainstorm ideas, explore concepts and receive AI-generated responses.

This provides the basic conversational layer on which the other capabilities can be built.

2. Learning and Research

One of the areas I care about most is using AI as a learning companion.

Susan AI can be used to:

Explain difficult concepts
Break complex topics into simpler sections
Generate study material
Brainstorm research ideas
Summarize information
Compare concepts
Ask follow-up questions

The objective is not simply to provide an answer, but to help users understand why the answer makes sense.

3. Writing Assistance

Generative AI is extremely useful as a writing partner.

Susan AI can assist with:

Articles
Reports
Emails
Documentation
Ideas
Rewriting
Summaries
Content planning

One of my goals is to make AI-generated content more useful by keeping the human author in control.

AI should assist the writer—not replace the writer.

4. Coding Assistance

Another major area is software development.

I use AI extensively while exploring and building web applications, so coding assistance naturally became part of Susan AI.

Potential workflows include:

Problem
   ↓
Explain the problem
   ↓
Generate an approach
   ↓
Write code
   ↓
Review code
   ↓
Find errors
   ↓
Improve implementation

This makes the assistant useful not only for experienced developers but also for people who are learning programming.

5. Document and Knowledge Work

Real-world work rarely happens only inside a chat box.

Important information is often stored in:

PDF files
Text files
CSV files
JSON data
Reports
Notes
Documents

A useful AI assistant therefore needs to work with information supplied by the user.

This is an important direction for Susan AI: moving from general AI knowledge toward context-aware assistance.

6. AI + Web Research

Another area I am exploring is combining AI with web-based research.

The basic concept is:

User Question
      ↓
Research
      ↓
Relevant Information
      ↓
AI Processing
      ↓
Structured Answer

The challenge is not simply retrieving information.

The real challenge is turning scattered information into something understandable, useful and actionable.

7. Agent-Style Workflows

One of the most interesting directions for Susan AI is AI agents.

A conventional chatbot waits for a user message and returns a response.

An agent-style system can potentially:

Understand Goal
      ↓
Plan
      ↓
Use Tools
      ↓
Process Information
      ↓
Take Actions
      ↓
Return Result

I am experimenting with this direction because I believe the next generation of AI applications will increasingly focus on task completion rather than text generation alone.

Technology

Susan AI is a modern web application deployed on Vercel.

The project uses a web-based architecture designed to keep the interface accessible directly from the browser.

The AI layer currently uses Google Gemini Flash-Lite.

The overall architecture is evolving as I experiment with new capabilities.

A simplified conceptual architecture looks like this:

                 ┌─────────────────┐
                 │      User       │
                 └────────┬────────┘
                          │
                          ▼
                 ┌─────────────────┐
                 │   Susan AI UI   │
                 └────────┬────────┘
                          │
                          ▼
                 ┌─────────────────┐
                 │  AI Application │
                 │      Layer      │
                 └────────┬────────┘
                          │
             ┌────────────┼────────────┐
             ▼            ▼            ▼
        AI Model       Tools       User Data
             │            │            │
             └────────────┼────────────┘
                          ▼
                 ┌─────────────────┐
                 │    AI Output    │
                 └─────────────────┘

The architecture is intentionally being kept flexible because I expect the project to evolve considerably.

Why I Chose to Build It Myself

There are already many excellent AI assistants.

So why build another one?

Because building something yourself teaches you things that simply using a product cannot.

While developing Susan AI, I get to explore:

AI API integration
Prompt engineering
AI UX
Web application architecture
Authentication concepts
State management
API design
Error handling
AI response streaming
File processing
Agent workflows
Deployment
Performance
Product design

The project is therefore both a product experiment and a learning laboratory.

What I Have Learned

One of the biggest lessons has been that building an AI application is not simply about connecting an LLM API.

The model is only one component.

A useful AI product also needs:

1. Good UX

Users should understand what the AI can do without reading a manual.

2. Good Context

The AI needs the right information at the right time.

3. Good Prompts

Poor instructions can produce poor results even with a powerful model.

4. Good Error Handling

AI systems can fail in unexpected ways.

Applications therefore need graceful handling of:

API failures
Invalid input
Rate limits
Network problems
Unexpected responses

5. Trust

AI applications should clearly communicate limitations.

A confident answer is not necessarily a correct answer.

That is especially important when AI is used for research, government work, education or decision support.

The Bigger Vision

Susan AI is not finished.

In fact, I consider the current version the beginning.

My long-term vision is to explore a personal AI environment where different capabilities can work together.

For example:

              Susan AI
                  │
      ┌───────────┼───────────┐
      │           │           │
   Research    Writing      Coding
      │           │           │
      └───────────┼───────────┘
                  │
              Documents
                  │
                  ▼
             AI Agents
                  │
                  ▼
          Automated Workflows

The ultimate question I want to explore is:

Can a personal AI assistant become a useful digital workspace for an individual's everyday intellectual work?

I don't know the final answer yet.

That's exactly why I am building it.

What's Next?

Some of the areas I want to explore further include:

Better AI memory and context
More reliable document understanding
Advanced AI agents
Tool calling
Multi-step workflows
Better web research
Improved coding assistance
Personal knowledge management
More structured outputs
Voice interaction
Better mobile experience
AI-powered productivity workflows

The roadmap will evolve as I continue experimenting.

Building in Public

I am sharing Susan AI because I believe the process of building AI applications is as interesting as the final product.

There will be experiments that work.

There will also be experiments that fail.

Both are useful.

I plan to continue documenting the development process, technical experiments, design decisions and lessons learned.

If you are a developer, student, researcher, AI enthusiast or someone experimenting with AI applications, I would genuinely appreciate your feedback.

Try Susan AI

🌐 Live Demo:

https://susan-ai.vercel.app/

💻 GitHub:

https://github.com/susankarkarmakar-pixel

If you try it, I'd love to know:

What would you want your personal AI assistant to do that current AI chatbots don't do well?

That question may shape the next version of Susan AI.

Final Thought

We are moving from an era where software simply waits for instructions toward an era where software can increasingly understand goals, reason about tasks and assist with execution.

Susan AI is my small experiment in that direction.

It started with a simple question:

What would I build if I wanted my own AI assistant?

I am still exploring the answer.

And that's the most interesting part.

Built by Susankar Karmakar

AI #ArtificialIntelligence #GenerativeAI #AIAssistant #AIAgents #GoogleGemini #Gemini #WebDevelopment #SoftwareDevelopment #JavaScript #OpenSource #BuildInPublic #Developer #Productivity #AIEngineering

How I Built a Cross-Platform Browser Using Electron, React & TypeScript This project became Probaho Browser. https://github.com/susankarkarmakar-pixel/probaho-browser

Susankar Karmakar — Sun, 19 Jul 2026 05:06:58 +0000

GitHub - susankarkarmakar-pixel/probaho-browser · GitHub

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