M01-07 · AI-Assisted Software Development

Startup Engineering

Teaches the unique engineering practices required at early-stage startups (seed to Series A, 2-15 people). Covers shipping under extreme time pressure with explicit quality tradeoffs, wearing multiple hats (DevOps, customer support, hiring, product input), making rapid technology decisions without committee approval, interacting directly with customers, and influencing product direction through technical feasibility analysis. Students learn to be the kind of engineer a startup founder trusts.

25 Hours

8 Learning objectives

Evaluate Bloom's ceiling (?)

5 Competencies

What You'll Be Able To Do

Learning Objectives

Objectives

Depth

Ship features under time pressure by making explicit quality tradeoffs: identify which shortcuts are acceptable (skip tests on non-critical paths) vs. dangerous (skip tests on payments/auth) Evaluate
Operate across multiple roles simultaneously — developer, DevOps, customer support, interviewer, product thinker — with effective context-switching and time allocation Apply
Make rapid technology decisions (build vs. buy, vendor selection, stack choices) with incomplete information, documenting rationale and reversibility Evaluate
Interact directly with customers: reproduce reported bugs, respond personally, use support interactions to inform product decisions Apply
Influence product direction by translating technical feasibility into business terms: "We can do X in 2 weeks or Y in 4 — here's the tradeoff" Apply
Negotiate technical debt reduction with non-technical leadership using risk-based arguments: prioritize by blast radius (payments, auth, data integrity first) Apply
Prototype features rapidly using AI tools (V0/Bolt.new for UI, Claude Code for endpoints) with a higher acceptance threshold than big-company work, while maintaining critical-path quality Apply
Evaluate startup-specific infrastructure needs: monitoring before you need it, database backups, staging environments, and the minimum viable DevOps setup Analyze

Levels: Remember · Understand · Apply · Analyze · Evaluate · Create — highest demands most original thinking.

Core Competencies

What You'll Master

Speed-Quality Calibration

Making explicit quality tradeoffs under time pressure, knowing where shortcuts are acceptable and where they are catastrophic.

Multi-Hat Operations

Context-switching between development, DevOps, support, hiring, and product roles effectively.

Rapid Decision-Making

Technology choices, architecture decisions, and build-vs-buy evaluations made in hours instead of weeks.

Founder-Developer Dynamics

Building trust with founders, pushing back on unrealistic timelines constructively, influencing product direction.

Startup Infrastructure

Minimum viable monitoring, deployment, backup, and reliability for early-stage products handling real customers and money.

Portfolio Artifact

What You'll Build

Startup Sprint Simulation — Student works through a compressed 2-week startup simulation: Day 1 production bug fix in an unfamiliar codebase, rapid feature prototype for a customer demo, technology evaluation and recommendation (with decision made in under 2 hours), a customer support response that informs a product improvement, a tech debt proposal with risk-based prioritization, and a weekly CEO update summarizing technical progress in business terms.

Tools You'll Use

Industry Tools, Not Toy Projects

VS Code / Cursor

Code editors optimized for rapid development with AI-assisted coding capabilities.

Claude Code & GitHub Copilot

AI coding assistants for rapid prototyping, debugging, and accelerating feature development.

V0 / Bolt.new / Lovable

AI-powered scaffolding tools for rapid UI prototyping and feature demos.

Vercel / Railway

Fast deployment platforms for shipping quickly with minimal DevOps overhead.

Supabase

Backend-as-a-service with auth, database, and real-time capabilities for rapid startup development.

Stripe

Payment processing platform — the critical path that demands quality even when shipping fast.

Sentry & PostHog

Error tracking and product analytics for minimum viable monitoring in early-stage products.

Linear / Slack

Project management and team communication tools for fast-moving startup environments.