DEV Community: Redwan Shahriar Shubho

Turing's Light — A Narrative Puzzle Game About Logic, Pride & Legacy

Redwan Shahriar Shubho — Fri, 12 Jun 2026 19:17:28 +0000

🎮 Play the Game

🔗 Live: https://turings-light.vercel.app
💻 Code: https://github.com/redwanshahriarshubho/turings-light

📹 Demo Video

What I Built

Turing's Light is a browser-based narrative puzzle game honouring Alan Mathison Turing (1912–1954) — mathematician, codebreaker, father of computer science, and gay man persecuted by the government he helped save.

The game spans four acts of his real life across five puzzle levels — every mechanic drawn directly from his actual work. No frameworks. No libraries. Pure HTML, CSS, and JavaScript.

The Story

Act	Setting	Level
Act I	Cambridge, 1930 — Young Alan discovers logic	Logic Gates
Act II	Bletchley Park, 1940 — Breaking enemy codes	Caesar Cipher + Binary Decode
Act III	Manchester, 1952 — Persecution and darkness	Light & Dark + Enigma Machine
Act IV	The present day — His legacy lives on	The Turing Test

The Five Levels

🔌 Level 1 — Logic Gates

Toggle AND, OR, and NOT switches to unlock a door. This is the boolean algebra Turing formalised in 1936 — the foundation of every computer ever built.

📡 Level 2A — Caesar Cipher

An intercepted enemy message. Find the shift key hidden in a historical clue about Turing himself, decode the message. This is the cryptanalysis Turing performed daily at Bletchley Park.

💻 Level 2B — Binary Decode

Eight binary bytes on screen. Convert each to its ASCII letter, spell the hidden word. Turing proved all information reduces to ones and zeros.

🌑 Level 3 — Light & Darkness

A completely dark grid. Click cells to illuminate them — light reveals hidden symbols. Enter the sequence. This level is the emotional core: a metaphor for 1952, when the British government tried to suppress who Turing was.

⚙️ Level 4 — Enigma Machine

Six rotors, each cycling A to Z. Dial every rotor to zero — mirroring how Turing's Bombe machine cracked Nazi Enigma codes. The world's first programmable computing device.

🧠 Level 5 — The Turing Test

Read two responses to a question — one human, one machine. Decide which is which. Score 4 out of 5 to pass. This is Turing's 1950 paper "Computing Machinery and Intelligence" made playable.

How I Built It

Tech stack: Pure HTML + CSS + JavaScript. Zero frameworks. Zero dependencies. Opens in any browser.

Two canvas layers:

Background canvas — animated star field, solstice day↔night sky, aurora effects, floating binary fragments
Game canvas — all puzzle rendering and UI state

Visual design:

WW2 terminal aesthetic — VT323 monospace font, amber phosphor glow, green CRT colours, scanline overlay
Pride rainbow runs through the title gradient, HUD, particle effects, and ending aurora
Solstice day↔night cycle animates continuously in the game background

Story: Four acts of historically accurate narrative with typewriter effect — real dates, real events, real consequences.

Solstice Connection

The background canvas cycles a solsticeAngle variable, shifting the sky from deep night to pre-dawn and back — a living metaphor for the longest day.

The light mechanic in Level 3 makes this literal: your ability to see depends entirely on how much light you bring to the darkness. This is the June solstice theme made interactive.

🏆 Best Ode to Alan Turing

Every level mechanic comes directly from Turing's real work:

Level	Real Turing Connection
Logic Gates	His 1936 Turing Machine paper — boolean logic
Caesar Cipher	Bletchley Park cryptanalysis operations
Binary Decode	Digital information theory
Enigma Machine	The Bombe — mechanical Enigma decryption
Turing Test	"Computing Machinery and Intelligence" (1950)

The Pride rainbow runs through every screen — not as decoration, but as argument. His identity and his work are inseparable. Honouring one without the other would be dishonest.

The ending screen states plainly: he was chemically castrated, he died at 41, he was pardoned 59 years later. The computer you are reading this on exists because of him.

Closing

Alan Turing asked whether machines could think. He never got to see the answer.

The June solstice — the longest day — is a moment of maximum light. For Turing, the light came too late. But it came. His face is on the £50 note. His test names the benchmark for every AI system on earth.

"The light of truth can be obscured, but never extinguished."

🎮 Play: https://turings-light.vercel.app
💻 Code: https://github.com/redwanshahriarshubho/turings-light

🪙 CoinFlow — I Built a Full-Stack Micro-Tasking Platform with GitHub Copilot.

Redwan Shahriar Shubho — Fri, 05 Jun 2026 18:19:01 +0000

💡 What I Built

CoinFlow is a full-stack MERN micro-tasking platform with a real coin economy, Stripe payments, Firebase authentication, and a three-role system for Workers, Buyers, and Admins.

Live Demo: coin-flow-peach.vercel.app
GitHub Repo: github.com/redwanshahriarshubho/CoinFlow

📸 Before & After

❌ Before — No Backend At All

The entire server/ folder had no index.js. Every API call failed with network errors. The frontend looked beautiful but nothing worked.

✅ After — Fully Working Live App

🛠️ Tech Stack

Frontend: React 19, Vite 8, React Router 7, TanStack Query v5, Firebase v12, Stripe.js, Swiper, React Hook Form

Backend: Node.js, Express 5, MongoDB (native driver), JWT, Stripe SDK

Infrastructure: Vercel (frontend), Render (backend), MongoDB Atlas, imgBB

🧩 How It Works — The Three Roles

👷 Worker

Workers join the platform and get 10 free coins on signup. They browse available tasks, submit completed work, and get paid instantly when approved. Once they hit 200 coins ($10), they can withdraw via bKash, Nagad, Rocket, or Bank Transfer.

🏢 Buyer

Buyers post tasks with a coin reward per worker — the total cost is deducted when the task goes live. They review submissions through a dashboard and approve or reject each one. Unused coins are refunded automatically if a task is deleted.

🔐 Admin

Admins see platform-wide stats, manage all users, moderate any task, and approve worker withdrawal requests.

💰 The Coin Economy

Action	Coins
Register as Worker	+10 free
Register as Buyer	+50 free
Post a task	-(workers × coins_per_worker)
Submission approved	+payable_amount to worker
Delete task (unused slots)	+refund to buyer
Withdrawal minimum	200 coins ($10)
Exchange rate	20 coins = $1 USD

One design decision I'm proud of: when a submission is rejected, the task's required_workers count is incremented back by 1 so another worker can claim that slot. Without this, a single rejection would permanently block an open position.

app.patch("/submissions/:id/reject", verifyToken, verifyBuyer, async (req, res) => {
  await submissions.updateOne(
    { _id: new ObjectId(req.params.id) },
    { $set: { status: "rejected" } }
  );
  await tasks.updateOne(
    { _id: new ObjectId(sub.task_id) },
    { $inc: { required_workers: 1 } }
  );
  await notifications.insertOne({
    recipient_email: sub.worker_email,
    message: `Your submission for "${sub.task_title}" was rejected. Keep going!`,
    actionRoute: "/dashboard/task-list",
    time: new Date(), read: false,
  });
});

🤖 How GitHub Copilot Helped

Architectural Review

I used Copilot as a sounding board throughout. Describing the coin economy rules in plain English and asking "what could go wrong here?" surfaced edge cases before they became bugs.

Security Hardening

Copilot flagged an IDOR vulnerability — I wasn't verifying that the buyer making a request actually owned the task. It suggested adding buyer_email: req.user.email to every MongoDB mutation query:

await tasks.updateOne(
  { _id: new ObjectId(req.params.id), buyer_email: req.user.email },
  { $set: { task_title, task_detail, submission_info } }
);

MongoDB Index Design

Copilot reviewed my schema and recommended the full index set:

await users.createIndex({ email: 1 }, { unique: true });
await tasks.createIndex({ buyer_email: 1 });
await submissions.createIndex({ worker_email: 1 });
await notifications.createIndex({ recipient_email: 1, time: -1 });

Duplicate Submission Guard

const dup = await submissions.findOne({ task_id, worker_email });
if (dup) return res.status(400).json({ message: "You already submitted this task" });

✨ Features Shipped

Worker: Browse tasks, full detail page, submit work, paginated history, real-time notifications, withdrawal form

Buyer: Post tasks with live cost preview, review submissions via modal, approve/reject with instant worker payout, edit/delete with refund, purchase coins via Stripe, payment history

Admin: Platform stats, user management, task moderation, withdrawal approval queue

System: JWT + Firebase auth (Email + Google OAuth), role-based route guards, imgBB image upload, fully responsive UI

🚀 Try It Live

coin-flow-peach.vercel.app

Register as a Worker to browse and complete tasks, or as a Buyer to post tasks and review submissions.
Test Stripe with card 4242 4242 4242 4242 / any future date / any CVC.

Built with React, Node.js, MongoDB, Stripe, and Firebase. GitHub Copilot helped me think through security, edge cases, and performance throughout the build.

Nexus

Redwan Shahriar Shubho — Sun, 31 May 2026 04:57:14 +0000

This is a submission for the Hermes Agent Challenge

What I Built

Nexus is an autonomous research digest agent powered by Hermes.
In a single command, Nexus plans a search strategy, searches the web, reads the top sources, clusters findings into themes, and generates a clean HTML digest with citations and a what to read next queue. No hand holding. No prompting for each step.

Demo

$ python main.py AI safety and alignment

Nexus Research Digest
Topic: AI safety and alignment
Date: 2026-05-30
Model : openrouter/auto

[step 1] Thinking... Tool: search_web
[step 2] Thinking... Tool: search_web
[step 3] Thinking... Tool: fetch_url
[step 4] Thinking... Tool: cluster_findings
[step 5] Thinking... Tool: save_digest

Digest saved
Done. Check the output/ folder.

Code
GitHub: https://github.com/redwanshahriarshubho/Nexus
My Tech Stack
• Python 3.10+
• Hermes Agent via OpenRouter API
• scikit-learn (TF-IDF clustering)
• urllib (web search + fetching)
• Custom HTML renderer (no frameworks)

How I Used Hermes Agent

Nexus uses three core Hermes agentic capabilities:

Multi-step planning: Hermes doesn't just answer one prompt. It plans which search queries to run, decides which URLs to fetch, and sequences its own actions autonomously.

Tool use: Four custom tools are registered: search_web, fetch_url, cluster_findings, and save_digest. Hermes decides when to call each one and with what arguments — no hardcoded flow.

Autonomous completion: The agent runs for up to 20 steps, self-corrects when tools return errors or results are sparse, and always finishes by saving the digest.

The result is a clean HTML report with a summary, key findings, themed sections, citations, and a what to read next queue generated entirely by Hermes reasoning through the problem step by step.