HQDigital headquarters

JaideepI build intelligent systems and turn ideas into things you can run.

This is my digital headquarters: the projects I ship, the AI agents I build, and the product ideas I'm working through. Everything here is either real and inspectable, or labelled as what it is.

  • Developer
  • AI builder
  • Systems thinker
  • Entrepreneur
  • Developer
  • AI builder
  • Systems thinker
  • Entrepreneur
  • JavaScript
  • Python
  • CSS
  • TypeScript
  • 7 AI agents
  • 3 public repositories
  • 1 venture
  • 13 live online sessions
  • 35+ students, grades 6–12
  • 20+ final projects completed and submitted

01About

I build what I explore

Developer · AI builder · Systems thinker · Entrepreneur

I do more than write code. I explore ideas, build intelligent systems, automate workflows and develop products. Most of what I make starts as a question (could this be automated, explained better, or turned into a product?) and ends as something you can open and use.

My public work so far includes Researchora, an AI-assisted research community. More is in the workshop and will appear here when it's ready to share.

What I’m building toward

  • Build AI agents that do useful work with a human in the approval loop.
  • Turn the strongest experiments into products people rely on.
  • Keep everything inspectable: source, reasoning and limits.

How I work

  1. 01

    Real over simulated

    If something works, you can try it. If it doesn't yet, it says so. Demos are labelled as demos and prototypes as prototypes.

  2. 02

    Evidence you can open

    Numbers and claims should lead back to a source. Assumptions are fine as long as they are marked as assumptions.

  3. 03

    Software does the arithmetic

    Models are for language and judgement. Anything that can be calculated or checked deterministically is done in code.

  4. 04

    Humans approve consequences

    Agents can propose and prepare. Publishing, sending, spending and changing production systems wait for an explicit yes.

02Projects

Real code, straight from GitHub

Every repository here is fetched from my GitHub account, so stars, languages and dates are current. Download a ZIP, copy a clone command, or have the README explained first.

Researchora

Researchora

Source availableAI

A frontend-first research and knowledge-sharing platform: discovery, publishing, discussion, reading history, following and an AI assistant.

Language
JavaScript
Stars
1
Last push
Oct 13, 2026
License
None

Not open source. All rights reserved; use beyond personal evaluation needs written permission from the owner.

Download ZIPLive site

gaze-companion

gaze-companion

Source available

No description has been written for this repository yet.

Language
TypeScript
Stars
1
Last push
Oct 13, 2026
License
None

No license file. The code is public to read, but without a license it isn’t free to reuse.

Download ZIPLive site

The_food_app

The_food_app

Source available

No description has been written for this repository yet.

Stars
1
Last push
Jun 20, 2026
License
None

No license file. The code is public to read, but without a license it isn’t free to reuse.

Download ZIP

Live from the GitHub API · data as of Nov 5, 2026 · All repositories on GitHub

03AI Lab

Agents with a job, a status and a limit

Each agent has a profile: what it is for, what it can and cannot do, what it is built on and how a request moves through it. Some run on this site and can be tried below; others live inside my projects. Every one carries an honest status.

On-site AI runtime

Checking…

What the status labels mean
Live
Running for real users.
In Beta
Works end to end; still being hardened.
Prototype
Built, but not deployed or not verified in production.
Demo Only
Scripted or illustrative. No model is called.
Planned
Not built yet.
Temporarily Unavailable
Built, currently switched off or failing.
Requires configuration
Built and wired up, but this deployment has no model key, so it cannot run.

HQ Guide

ResearchRuns on this site

Checking status

Answers questions about this portfolio: the projects, agents and ventures in it.

Project Scout

ResearchRuns on this site

Checking status

Recommends the work most relevant to what a visitor says they care about.

README Explainer

CodingRuns on this site

Checking status

Reads a public repository's README and explains what the project is and how to run it.

Structured Extractor

AutomationRuns on this site

Checking status

Turns pasted free text into structured records that software can use.

Venture Analyst

Business intelligenceRuns on this site

Checking status

Walks a visitor through the reasoning behind one of the ventures on this site.

Idea Lens

Business intelligenceRuns on this site

Checking status

Breaks a product idea into the assumptions it depends on and how to test them.

Researchora Assistant

ResearchPart of another project

Prototype

The AI assistant inside Researchora, for asking research-related questions.

Agent console

Talk to the agents that run on this site. Replies stream from a real model call on the server.

HQ Guide

Answers questions about this portfolio: the projects, agents and ventures in it.

Checking status

HQ Guide

Ask me about anything in this headquarters. I answer from the site's own project data, so if something isn't listed here I'll tell you rather than guess.

Try asking

Answers are generated from this site’s own data and can still be wrong. Conversations aren’t stored.

Orchestration

How I structure work across several specialised agents: narrow roles, explicit hand-offs, and a human gate before anything consequential. Select a component to inspect it, or step through the flow.

Interactive simulation

Interactive simulation of an architecture. No model is called and no tool is executed; the walkthrough below is scripted example data.

Five specialised agents take a question from open-ended research to a reviewed, approved action. It shows how I structure agent work: narrow roles, explicit hand-offs, and a human gate before anything consequential.

Example task: “Find out why setup is confusing for new users of a repository, and propose a fix.”

sourced findingsstructured summaryplan + proposed actionsaction resultsissues to fixResearch Agentcurrent stepAnalysis Agentno toolsPlanning Agentno toolsExecution Agent2 toolsReview Agent1 tool

Step 1 of 6scripted walkthrough

Research gathers material

Reads the README, the open issues and the setup scripts. Each finding is stored with the file or issue it came from.

Inspecting

Research Agent

Gathers relevant information

Receives
The task and its scope
Produces
Findings, each with a source
Tools
Read-only search · Document fetch
  • Collect source material for the question
  • Record where each finding came from
  • Treat everything retrieved as untrusted data

Guardrail. Retrieved content can inform the answer but can never change the agent's instructions.

AI Playground

A few focused tools rather than many shallow ones. Each states what it accepts, what it returns, what powers it and where it stops.

Explain it for

04Venture Studio

From a problem to a product, one stage at a time

Where technical work meets a real problem. Each venture has a profile covering the problem, who has it, the proposed solution and what still needs to be proven.

  1. IdeaNo ventures at this stage
  2. ResearchNo ventures at this stage
  3. ValidationNo ventures at this stage
  4. PrototypeNo ventures at this stage
  5. MVPResearchora
  6. LaunchNo ventures at this stage
  7. GrowthNo ventures at this stage

Each venture sits at the stage I’ve set for it by hand. Nothing here is launched until it says “Launched”, and no traction is claimed unless it is real.

SaaS product

Researchora

CompletedConcept

An AI-assisted research community: discover, publish, discuss and follow research in one place.

Problem
Research work is spread across separate tools for finding papers, keeping track of reading, discussing ideas and sharing results. Switching between them costs time and context.
For
Researchers and students who read and share papers; Communities built around a research topic
Open concept page

05Teaching

Teaching Python and AI to younger students

Building things is half of it. The other half is helping other people get started. In summer 2026 I founded and taught a live online program for middle and high school students.

Summer 2026 Live online

Young Innovators AI Academy

Founder and lead instructor

A live online program I founded to teach Python programming and artificial intelligence to middle and high school students. I designed the curriculum and taught every session myself.

  • 13live online sessions
  • 35+students, grades 6–12
  • 20+final projects completed and submitted

What I did

  • Founded the program and served as lead instructor
  • Designed the curriculum, covering Python programming and artificial intelligence
  • Taught all 13 live sessions
  • Created session homework and end-of-course feedback forms in Google Forms
  • Ran student sign-ups through a Google Form
Who it was for
Middle and high school students, grades 6–12
What we covered
Python programming · Artificial intelligence

Sharing student work responsibly

After the program I set up a parent media-permission process, so student projects could be showcased on Instagram, TikTok, YouTube, Facebook and LinkedIn while protecting students’ privacy.

  • First names only
  • No schools or contact information
  • Parents choose exactly what is shared

06Progress

What has actually shipped

Small, true numbers. Each one names its source.

Public repositories

3

Source: GitHub API

GitHub stars

3

Across public repositories

Source: GitHub API

AI agents documented

7

6 run on this site

Source: maintained by hand

Ventures

1

1 completed

Source: maintained by hand

Launched products

0

Nothing has launched yet

Source: maintained by hand

Site visits

–

Counting…

Source: this site’s counter

Languages in public code

Share of bytes across 3 public repositories

  • TypeScript71%
  • JavaScript25%
  • CSS2%
  • Python1%

Source: GitHub API

Agents by status

The status I assert for each agent in the AI Lab

  • In Beta6
  • Prototype1

Ventures by stage

  • MVP1

Source: maintained by hand

Build log

Dated events, newest first

  1. Latest push to gaze-companionGitHub
  2. Latest push to ResearchoraGitHub
  3. Published gaze-companionGitHub
  4. Published ResearchoraGitHub
  5. Published The_food_appGitHub
  6. Joined GitHubGitHub

GitHub figures are live as of Nov 5, 2026. Agent and venture figures count the entries published on this site. A visit is one browser session; bots are left out, and no cookies or IP addresses are stored. This dashboard shows no revenue, customer or funding numbers because none are tracked here.

07Contact

Start a conversation

Building something in AI, want to talk through one of these projects, or have a problem worth solving? I’d like to hear about it.