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DevScroll — AI Engineering Learning Platform

A curated learning platform for AI and Quantum Computing engineers. Structured tracks, lesson pages, roadmaps, and resources for the future-ready developer.

Pages

Page Description
index.html Landing page
tracks.html AI Engineering + Quantum Computing learning tracks
lessons/ 22 individual lesson pages (12 AI + 10 Quantum)
resources.html Curated resources from Anthropic, NVIDIA, Google, Microsoft
roadmap.html AI Engineering Roadmap — 10-step learning path
video-paths.html AI Mastery Videos — Zero to Hero curated playlist
harness-roadmap.html Harness Engineer Roadmap — 14-skill checklist with videos
university.html Academy — Harvard, Stanford, MIT course audits
agents.html AI Agents hub
auth.html Sign up
login.html Login

Stack

  • Vanilla HTML/CSS/JS — no framework
  • Deployed on Netlify (see netlify.toml)
  • API proxy → Railway backend (https://devscroll-web-production.up.railway.app)

Tracks

AI Engineering for Devs (12 lessons)

Module Lessons
M1: LLM Orchestration Prompt Engineering & Tuning · Function Calling & Tool Use
M2: RAG & Vector Data Vector Embeddings · Semantic Search Strategies
M3: Agentic Systems LangChain vs LangGraph · Auto-GPT Architectures
M4: Fine-tuning & Evaluation LoRA & QLoRA · LLM Evaluation Metrics · RLHF & DPO
M5: Production Deployment API Integration · Self-hosted LLMs (vLLM) · Cost Optimization

Quantum Computing for Devs (10 lessons)

Module Lessons
M1: Quantum Fundamentals Qubits, Superposition & Entanglement · Quantum Gates & Circuits
M2: Quantum Algorithms Grover's Search · Shor's Factoring
M3: Quantum ML Variational Quantum Circuits · Quantum Neural Networks
M4: Noise & Error Correction Quantum Error Correction · NISQ Algorithms & Mitigation
M5: Real Hardware IBM Quantum & Qiskit Runtime · Amazon Braket & Azure Quantum

Each lesson page includes concept cards, runnable code examples, curated resources, and prev/next navigation.

Harness Engineer Roadmap

Skill checklist across 5 sections:

  • Foundation
  • Context Engineering
  • Guide Design (Feedforward)
  • Sensor Design (Feedback)
  • Production & Iteration

Progress persisted in localStorage. Each skill links to a curated YouTube video.

Security

  • CSP headers configured in netlify.toml
  • Open redirect protection on auth flows (?next= param validated)
  • No secrets in codebase — .env and all variants gitignored

Deploy

Netlify auto-deploys from main branch. Publish directory is . (root).

# netlify.toml
[build]
  publish = "."

[[redirects]]
  from = "/api/*"
  to = "https://devscroll-web-production.up.railway.app/api/:splat"
  status = 200
  force = true

Local Dev

# No build step needed
python3 -m http.server 8080
# then open http://localhost:8080

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