▶ TINY RPG · COMPLETE 12 MISSIONS · BECOME JOB-READY

Missions RPG

Imagine this is you. A tech newbie with a laptop, wifi and a Sigmaschool enrollment. 12 missions stand between you and becoming job-ready. Each one you prove you can build + explain without leaning on AI. Mastery-based learning, not time-based learning. Have fun!

📖 Step 1 · Read the briefings

▶ NEW GAME

Missions RPG

A tiny RPG of the Sigmaschool 12-week pathway. First read the briefing (it’s short). Then a quick 4-question check unlocks the 12 missions.

Progress saves to your browser

▼ See all missions & checkpoints

▶ EVERY MISSION · WHAT YOU SHIP · WHAT PROVES IT

All 12 missions - what you ship, what proves it.

The same curriculum the cohort walks every week. Checkpoints are the chapters inside each mission; the lesson counts come from the full programme curriculum. Prefer it as plain reading? Browse the curriculum reference - one deep page per mission.

  1. MISSION 1Programming Foundations3 checkpoints

    Build an Interactive Personal Website

    “I can build an interactive web page with HTML, CSS and JavaScript, and explain how the browser runs my code.”

    Start from zero. Learn how browsers, websites and servers fit together, then build your own personal website with HTML and CSS and bring it to life with JavaScript - variables, conditionals, loops and functions. Run the same JavaScript in the browser and in Node.js.

    🧰 Tech stack
    HTML5HTML5CSS3CSS3JavaScriptJavaScriptNode.jsNode.jsChrome DevToolsChrome DevTools
    🤝 AI Companion
    Most guidance · you still write first
    🏁 What proves it
    Working interactive personal website + walkthrough explaining your JavaScript
    🪙 Reward
    🏆 First Ship Badge
    🚩 Checkpoints · 3▼
    • Structure and style your site with semantic HTML and CSS
      • How websites, browsers and servers work together when you open a page
      • Structure content with semantic HTML - headings, sections, images and links
      • Style it with CSS fundamentals - colours, spacing, the box model and simple layout
    • Add interactivity with variables, conditionals, loops and functions
      • Store and change data with variables, data types and operators
      • Make decisions with conditionals and repeat work with loops
      • Package logic into functions and wire them to clicks and inputs on the page
    • Run JavaScript in Node.js and debug it in Chrome DevTools
      • Run JavaScript outside the browser with Node.js and npm
      • Find your way around the terminal and VS Code
      • Inspect elements, read console errors and step through code in Chrome DevTools
    ▶ Read the full mission guide
  2. MISSION 2Programming Foundations3 checkpoints

    Build an Interactive Task Manager

    “I can build a CRUD app with the DOM, validate user input, persist data, and manage my code with Git and GitHub.”

    Model real data with arrays and objects, then build a task manager people can actually use: add, edit, complete and delete tasks, filter the list, validate the form, and keep everything after a refresh with localStorage. Write your first classes, and your first commits, branches and pull requests on GitHub.

    🧰 Tech stack
    JavaScriptJavaScriptHTML5HTML5CSS3CSS3GitGitGitHubGitHubChrome DevToolsChrome DevTools
    🤝 AI Companion
    Most guidance · you still write first
    🏁 What proves it
    GitHub repo with branches and a merged pull request + working task manager + walkthrough
    🪙 Reward
    🧠 +5 Reasoning · Version control unlocked
    🚩 Checkpoints · 3▼
    • Model tasks with arrays, objects and a simple class
      • Model a task as an object and the list as an array
      • Transform data with map, filter and find
      • Write your first class with a constructor and methods (basic OOP)
    • Create, update and delete tasks with DOM events and validated forms
      • Render the task list into the page with DOM manipulation
      • Handle clicks, submits and input with event listeners
      • Validate form input and show helpful error messages
    • Filter the list, persist it with localStorage, and ship it via a pull request
      • Filter tasks by status and handle the empty state
      • Persist the list with localStorage so it survives a refresh
      • Commit, branch and open a pull request on GitHub
    ▶ Read the full mission guide
  3. MISSION 3Programming Foundations3 checkpoints

    Build an API-Powered Search App

    “I can fetch and display live API data with async JavaScript, handle failures gracefully, and debug with DevTools instead of guessing.”

    Talk to the internet. Learn how HTTP, REST and JSON work, test real endpoints in Bruno, then build a search app on a public REST API with ES modules, async/await, loading states and proper error handling. The AI is off: you debug with breakpoints, stack traces and the Network tab.

    🧰 Tech stack
    JavaScriptJavaScriptBrunoBrunoChrome DevToolsChrome DevToolsGitHubGitHub
    🤝 AI Companion
    AI OFF · you debug on your own
    🏁 What proves it
    Working search app + Bruno collection + notes on the bugs you found and fixed
    🪙 Reward
    🐛 Debugger title earned
    🚩 Checkpoints · 3▼
    • Explore a public REST API in Bruno and read real HTTP requests and responses
      • How HTTP, REST and JSON fit together in a client-server app
      • Send requests and read responses, status codes and headers in Bruno
      • Read an API’s documentation and the shape of the JSON it returns
    • Fetch data with async/await across ES modules and render the results
      • Split code into ES modules with import and export
      • Work with promises and async/await
      • Call the API with the Fetch API and render the search results
    • Handle loading, empty and error states, and debug with breakpoints
      • Show loading, empty and error states with try/catch
      • Debug with breakpoints, stack traces and the Network tab - no AI
      • Write a short note on every bug you found and how you fixed it
    ▶ Read the full mission guide
  4. MISSION 4Full-Stack Engineering3 checkpoints

    Build a Job Board Frontend in React

    “I can build a component-based React app with state, forms and data fetched from an API.”

    Meet the project you will grow for the rest of the programme: a recruitment platform. Build its frontend in React with Vite - functional components, props and state, controlled forms, lists, conditional rendering, and job data fetched from an API.

    🧰 Tech stack
    ReactReactViteViteJavaScriptJavaScriptCSS3CSS3GitHubGitHub
    🤝 AI Companion
    You write the code · AI reviews it
    🏁 What proves it
    React job-board frontend on GitHub + component map + walkthrough
    🪙 Reward
    ⚛️ Frontend Mage class unlocked
    🚩 Checkpoints · 3▼
    • Set up React with Vite and break the job board into components
      • Create a React project with Vite and npm
      • Write functional components in JSX and compose them into pages
      • Pass data down with props and inspect it in React DevTools
    • Manage state, render lists and handle events
      • Hold and update UI data with useState
      • Handle events and render lists of jobs with keys
      • Show and hide UI with conditional rendering
    • Build controlled forms and fetch job data from an API
      • Build controlled forms for searching and posting jobs
      • Fetch job data from an API with an introductory useEffect
      • Handle loading and error states in React
    ▶ Read the full mission guide
  5. MISSION 5Full-Stack Engineering3 checkpoints

    Build a Recruitment API with Express & PostgreSQL

    “I can design a database-backed REST API with SQL, validation, error handling and a clean structure.”

    Go backend. Design a REST API for candidates, jobs and applications with Node.js and Express, store it in PostgreSQL with real tables, keys and joins, validate every request with Zod, and organise the code into routes, services and data access.

    🧰 Tech stack
    Node.jsNode.jsExpressExpressPostgreSQLPostgreSQLZodZodBrunoBruno
    🤝 AI Companion
    You write the code · AI reviews it
    🏁 What proves it
    Recruitment API repo + SQL schema + Bruno collection covering every endpoint
    🪙 Reward
    🗄️ Backend Engineer rank
    🚩 Checkpoints · 3▼
    • Design tables, keys and relationships, and write SQL with JOINs
      • Design tables for candidates, jobs and applications with primary keys and relationships
      • Write SQL: SELECT, INSERT, UPDATE, DELETE and JOIN
      • Query PostgreSQL from Node.js with the pg client
    • Build Express routes and middleware for full CRUD over PostgreSQL
      • Set up an Express server with routing and middleware
      • Design clean REST endpoints for full CRUD
      • Test every endpoint in Bruno and use basic Bash in the terminal
    • Validate with Zod, handle errors, and split routes, services and data access
      • Validate request data with Zod schemas
      • Return proper status codes and handle errors consistently
      • Separate routes, services and data access - your first real architecture
    ▶ Read the full mission guide
  6. MISSION 6Full-Stack Engineering3 checkpoints

    Build an Authenticated Full-Stack Recruitment Platform

    “I can build secure login, sessions and permissions across a full-stack React, Express and PostgreSQL app.”

    Connect your React frontend to your Express API and lock it down. Add signup, login and logout with argon2 password hashing and server-side sessions stored in PostgreSQL, protect your API endpoints, and manage auth state in React with protected routes.

    🧰 Tech stack
    ReactReactReact RouterReact RouterNode.jsNode.jsExpressExpressPostgreSQLPostgreSQL
    🤝 AI Companion
    You write the code · AI reviews it
    🏁 What proves it
    Authenticated full-stack platform + auth-flow explanation + walkthrough
    🪙 Reward
    🔐 Gatekeeper title earned
    🚩 Checkpoints · 3▼
    • Hash passwords with argon2 and build signup, login and logout
      • Understand authentication vs authorization
      • Hash and verify passwords with argon2
      • Build signup, login and logout endpoints
    • Store sessions in PostgreSQL and protect your API endpoints
      • Keep users signed in with sessions and cookies (express-session)
      • Store sessions in PostgreSQL with connect-pg-simple
      • Protect endpoints and check permissions, with secure cookies and secrets
    • Connect React to the API with auth state and protected routes
      • Connect your React frontend to the Express API with fetch
      • Hold auth state in React and add protected routes with React Router
      • Test the full flow end to end: sign up, log in, act, log out
    ▶ Read the full mission guide
  7. MISSION 7Full-Stack Engineering3 checkpoints

    Test, Review & Deploy the Recruitment Platform

    “I can independently modify, debug, test and deploy an authenticated React, Node.js and PostgreSQL app.”

    Make it production-grade. Write automated tests with Vitest, Supertest and React Testing Library, keep the code clean with ESLint and Prettier, run everything in GitHub Actions on every pull request with AI code review from CodeRabbit and Qodo, then deploy the frontend, backend and PostgreSQL on Railway with proper environment variables and secrets.

    🧰 Tech stack
    VitestVitestReact Testing LibraryReact Testing LibraryGitHub ActionsGitHub ActionsESLintESLintPrettierPrettierCodeRabbitCodeRabbitQodoQodoRailwayRailway
    🤝 AI Companion
    You write the code · AI reviews it
    🏁 What proves it
    Live Railway deployment + passing tests + green CI pipeline + reviewed pull requests
    🪙 Reward
    🚦 Competency gate cleared
    🚩 Checkpoints · 3▼
    • Write API and unit tests with Vitest and Supertest, plus one UI test
      • Write unit tests with Vitest
      • Test API endpoints with Supertest
      • Write one basic UI test with React Testing Library
    • Run linting, formatting, tests and AI code review in CI on every pull request
      • Enforce code style with ESLint and Prettier
      • Run lint and tests automatically in GitHub Actions on every pull request
      • Review pull requests with CodeRabbit and Qodo, and decide what to accept
    • Configure environments and secrets, then deploy everything on Railway
      • Understand development vs production and manage environment variables and secrets
      • Deploy the React frontend, Express backend and managed PostgreSQL on Railway
      • Verify the live app and fix anything that only breaks in production
    ▶ Read the full mission guide
  8. MISSION 8Applied AI & Agents3 checkpoints

    Build an AI Recruitment Assistant with RAG

    “I can build a reliable LLM feature with prompt and context engineering, structured output, basic RAG and tracing.”

    Put an LLM inside your product. Call the OpenAI Responses API from Express, engineer prompts with instructions, examples and constraints, validate structured JSON with Zod, answer questions from a document collection with embeddings-based RAG, and trace every model call in Langfuse. You also start directing Codex CLI as your coding agent, with an AGENTS.md that sets the rules.

    🧰 Tech stack
    OpenAIOpenAINode.jsNode.jsExpressExpressZodZodLangfuseLangfuseCodex CLICodex CLI
    🤝 AI Companion
    AI runs inside what you build
    🏁 What proves it
    Working AI assistant + validated JSON output + basic RAG + five repeatable test cases + a Langfuse trace
    🪙 Reward
    ✨ AI Product Builder rank
    🚩 Checkpoints · 3▼
    • Call the OpenAI Responses API and engineer reliable prompts
      • How LLM APIs work: inputs, outputs, tokens and context windows
      • Call the OpenAI Responses API from your Express backend
      • Prompt engineering: instructions, examples and constraints
    • Return validated structured output and answer from retrieved documents (RAG)
      • Get structured JSON from the model and validate it with Zod
      • Context engineering: select and supply only the information the model needs
      • Build basic RAG with the OpenAI Embeddings API over a small document collection
    • Trace calls in Langfuse, write repeatable test cases, and direct a coding agent
      • Trace model calls, latency, token usage and cost in Langfuse
      • Write at least five repeatable test cases for your LLM output
      • Direct Codex CLI as a coding agent, with an AGENTS.md for instructions, context and checks
    ▶ Read the full mission guide
  9. MISSION 9Applied AI & Agents3 checkpoints

    Build an AI Recruitment Agent with Tools & MCP

    “I can build a bounded, controllable AI agent with tool calling, MCP and human approval, and explain exactly how the loop works.”

    Go from one LLM call to an agent. Write your own JavaScript agent harness - a bounded loop of model, tool, result, model - with a tool registry, conversation state, execution limits, allowlists and human approval before anything consequential. Then connect it to an MCP server and trace every step in Langfuse.

    🧰 Tech stack
    OpenAIOpenAINode.jsNode.jsZodZodMCPMCPExpressExpressPostgreSQLPostgreSQLLangfuseLangfuse
    🤝 AI Companion
    AI runs inside what you build
    🏁 What proves it
    Working agent with 2+ tools, an MCP integration, a human-approval gate and Langfuse traces
    🪙 Reward
    🎛️ Harness Engineer rank
    🚩 Checkpoints · 3▼
    • Define tools with Zod schemas and run a bounded agent loop
      • The difference between LLM calls, workflows and agents
      • Define tools with Zod input schemas and use OpenAI tool calling
      • Write the agent loop yourself: model, tool, result, model, with a hard stop
    • Add state, limits, allowlists, retries and human approval
      • Harness engineering: a tool registry, conversation state and execution limits
      • Tool permissions and allowlists, plus human approval before consequential actions
      • Handle tool errors with retries and clear stopping conditions
    • Connect an MCP server and trace the whole agent in Langfuse
      • MCP fundamentals: clients, servers, tools and transports
      • Connect your agent to an MCP server over Streamable HTTP and debug it with MCP Inspector
      • Trace the agent and every tool call in Langfuse
    ▶ Read the full mission guide
  10. MISSION 10Applied AI & Agents3 checkpoints

    Make the Agent Reliable: Tracing, Evals & Safety

    “I can find why an AI agent misbehaves, fix it, and prove the fix with repeatable evaluations.”

    Agents fail quietly. Trace your Mission 9 agent end to end, find at least two distinct failure scenarios, build a 10 to 15 case evaluation dataset in Langfuse, run experiments, fix what breaks and prove the improvement. Measure latency and cost, and defend against prompt injection and unauthorised tool use.

    🧰 Tech stack
    LangfuseLangfuseOpenTelemetryOpenTelemetryVitestVitestOpenAIOpenAINode.jsNode.js
    🤝 AI Companion
    AI runs inside what you build
    🏁 What proves it
    Before-and-after eval results + failure analysis + latency and cost notes + prompt-injection defence demo
    🪙 Reward
    🔬 Reliability Engineer rank
    🚩 Checkpoints · 3▼
    • Trace full agent runs and find the root cause of failures
      • Observability vs evaluation - and why you need both
      • Add custom spans for tools, retrieval and agent steps with Langfuse and OpenTelemetry
      • Read a trace to find the root cause of wrong agent behaviour
    • Build an evaluation dataset and run repeatable experiments
      • Build an evaluation dataset of 10 to 15 test cases
      • Run experiments in Langfuse and deterministic checks in Vitest
      • Score pass/fail outcomes and run regression tests after every change
    • Fix, re-evaluate, measure cost and defend against prompt injection
      • Fix the failures you found and re-run the evals to prove it
      • Measure and document latency, token usage and cost
      • Defend against prompt injection, unauthorised tool use and sensitive-data leaks
    ▶ Read the full mission guide
  11. MISSION 11AI-Native Capstone3 checkpoints

    Build Your AI-Native Capstone

    “I can scope and build a full-stack, AI-native application end to end, using coding agents responsibly.”

    Two weeks, your product. Scope a real AI-native application - a recruitment platform, customer-support assistant, sales research agent, productivity agent or document processor - then build it end to end: frontend, backend, database and one genuinely useful AI capability, with tools where they fit, tests and Langfuse traces. Extending your recruitment project is allowed if the new work is substantial and yours.

    🧰 Tech stack
    ReactReactViteViteExpressExpressPostgreSQLPostgreSQLOpenAIOpenAIZodZodMCPMCPLangfuseLangfuseCodex CLICodex CLIGitHubGitHub
    🤝 AI Companion
    You direct the coding agent
    🏁 What proves it
    Working capstone (frontend + backend + database + AI) with tests and Langfuse traces
    🪙 Reward
    🏰 Founder badge earned
    🚩 Checkpoints · 3▼
    • Scope the product, plan the architecture and set up the skeleton
      • Scope the product and define the smallest version that is genuinely useful
      • Plan the architecture with clear separation of concerns
      • Set up the full-stack skeleton: React, Express, PostgreSQL
    • Build the core features, data model and one genuinely useful AI capability
      • Implement the core features and data model
      • Design and build one genuinely useful AI capability
      • Manage context and tools so the AI gets exactly what it needs
    • Add tools where they fit, error handling, tests and Langfuse traces
      • Integrate tools or MCP where the product needs them
      • Test and debug incrementally, with basic error handling throughout
      • Use coding agents responsibly - you review, you understand, you own the code
    ▶ Read the full mission guide
  12. MISSION 12AI-Native CapstoneFINAL BOSS3 checkpoints

    Ship, Document & Defend Your Capstone

    “I can build, understand, modify, debug and maintain conventional software and AI-powered features, and defend my decisions live.”

    The final mission. Ship your capstone to production, back it with passing tests, a small AI evaluation suite and Langfuse evidence, run a security review and document the architecture. Then defend it live - including an unseen modification or debugging task - and get your portfolio and interviews ready.

    🧰 Tech stack
    RailwayRailwayGitHub ActionsGitHub ActionsVitestVitestLangfuseLangfuseGitHubGitHubLinkedInLinkedIn
    🤝 AI Companion
    AI drafts · you edit & own it
    🏁 What proves it
    Public deployed app + documented repo + passing tests + AI eval suite + Langfuse evidence + live technical defence
    🪙 Reward
    👑 JOB-READY - game complete
    🚩 Checkpoints · 3▼
    • Release to production with tests, regression evals and a security review
      • Configure and deploy the app to production
      • Run end-to-end tests, CI and a small AI regression eval suite
      • Do a security review and capture Langfuse tracing evidence
    • Document the README and architecture, and explain your tradeoffs
      • Write a clear GitHub README and an architecture diagram
      • Explain your architecture decisions and their tradeoffs
      • Debug and maintain your code like someone else will inherit it
    • Pass a live technical defence and prepare your portfolio and interviews
      • Defend your app live, including an unseen modification or debugging task
      • Prepare your portfolio, GitHub and LinkedIn
      • Practise technical interviews
    ▶ Read the full mission guide

▶ HOW IT REALLY WORKS

You move on when you’ve mastered it, not when a clock runs out.

Every mission ships something real - working code, one clear standard to pass, and a Loom where you explain what you built. The rule is simple: if you can’t explain it, you can’t submit it. You learn at your own pace, with live Buildrooms every evening, Unblock Hours in the afternoon, and Discord 24/7. Finish all 12 missions with proof you can defend and you’re Job-Ready - plan for 30+ hours a week over 12 weeks, or 14 hours a week over ~24 weeks.

▶ THE ARC · 4 PHASES · UPDATED NOVEMBER 2026

12 missions, in 4 phases.

PHASE 1 · Missions 1–3

Programming Foundations

JavaScript, the DOM, Git and APIs from zero. Build, debug and explain real web apps, including one with the AI switched off.

PHASE 2 · Missions 4–7

Full-Stack Engineering

React, Express and PostgreSQL with real auth, then tests, CI, AI code review and a live deployment.

PHASE 3 · Missions 8–10

Applied AI & Agents

LLMs, prompt and context engineering, RAG, a hand-built agent harness with MCP, and the tracing and evals that make AI reliable.

PHASE 4 · Missions 11–12

AI-Native Capstone

Two weeks to build your own AI-native app, then ship it to production and defend it live.

The stack you'll ship with

JavaScriptJavaScript
Node.jsNode.js
ReactReact
ViteVite
ExpressExpress
PostgreSQLPostgreSQL
ZodZod
OpenAIOpenAI
MCPMCP
LangfuseLangfuse
Codex CLICodex CLI
VitestVitest
GitHub ActionsGitHub Actions
RailwayRailway
GitHubGitHub

Same tools your future team is already using, standardised for the November 2026 curriculum - each one introduced once and reused through to the capstone.

▶ READY?

The game is a preview. The cohort is the real thing.

Same 12 missions, same proof, same Job-Ready outcome - but with a live cohort, daily Buildroom, Unblock Hours, and a mentor watching your back.

Apply for the next cohort →See the full programme