AI Coding Workflows

AI coding without being a developer: building tools in Cursor and Claude Code

Non-developers can now build real software with AI. A practical guide to using Cursor and Claude Code as a non-engineer — what's realistic, what's not, and the discipline that separates useful tools from broken ones.

Intermediate

9 min read

AI-native IDEs and repository-aware coding workflows

Cursor, Copilot, Claude Code, and repository-aware agents change software work only when teams add boundaries. A practical workflow for codebase context, planning, tests, review, secrets, and production safety.

More in this topic

12 min read

Make Codex, Claude Code, and Cursor work as one CLI team

Use AGENTS.md, CLAUDE.md, Cursor rules, and CLI print modes so Codex designs, Claude reviews, and Cursor implements—without a custom orchestration platform.

15 min read

Multi-agent project management with Linear: Claude, Cursor, and Codex on one backlog

Run Claude Code, Cursor, and Codex against the same Linear project like a real engineering team: claim work, mark progress, hand off review, fix findings, and close issues without stepping on each other.

17 minutes

Conductor CEO Charlie Holtz Walks Us Through His AI Coding Setup

Y Combinator. A concrete senior-engineering walkthrough rather than a panel: Holtz compares Claude Code and Codex, orchestrates several coding agents in parallel, and marks "slop-free zones" where generated code is not allowed to land unreviewed. The setup embodies the article's rules — repository context, small reviewable patches, and the human staying architect while the agents do the typing.

14 min read

MCP from scratch: build a production-ready server in TypeScript

Building a production Model Context Protocol server requires more than wiring up a few tools. The patterns for schema design, auth, error handling, streaming, observability, and the production realities that make MCP servers useful at scale.

12 min read

Designing MCP tools that LLMs actually use correctly

Most MCP tools we see are technically correct and practically useless. LLMs ignore them, misuse them, or call them in unhelpful ways. The principles for designing tools LLMs adopt naturally, with examples of common failures and their fixes.

66 minutes

Cursor Vibe Coding Tutorial - For COMPLETE Beginners (No Experience Needed)

Tech With Tim. Tim is one of the steadier educators in this space, and this is the most complete "open Cursor, build something, ship it" walkthrough for a non-developer audience — setup, prompting, debugging, basic Git and even a touch of MCPs. Watch it once and you'll know what the article means by "build a small internal tool."

Intermediate

5 minutes

The "vibe coding" mind virus explained…

Fireship. Fireship's three rules — pick a boring popular stack, get good at Git, treat yourself as the product manager — are the same guardrails the article is trying to install. Five minutes well spent before you let an AI write to your repo unsupervised.

Intermediate

104 minutes

Building Agents with Model Context Protocol - Full Workshop with Mahesh Murag of Anthropic

AI Engineer. Anthropic's Mahesh Murag walking through MCP's design — why tools, resources, and prompts are separated, how clients negotiate capabilities, what production hosts actually do with the protocol. Watch it after the build to understand the parts of MCP the SDK quietly hides and to calibrate the article's "production-ready" checklist against the spec authors' intent.

75 minutes

The Ultimate MCP Crash Course - Build From Scratch

Web Dev Simplified. A full, code-along build of both an MCP server and a client in TypeScript — tool definitions, schemas, prompts and resources, stdio transport, inspector debugging. It's the closest video on YouTube to actually doing what the article asks you to do, at a pace where you can pause and follow along in your own editor.

19 minutes

Building more effective AI agents

Anthropic. Anthropic engineers walking through what they actually changed when their multi-agent systems were misusing tools — collapsing endpoints, returning names instead of IDs, leaning on MCPs and Agent Skills instead of stuffing more tools into the system prompt. Maps point-for-point onto the article's checklist for tool descriptions and return-shape design.

29 minutes

Prompting for Agents | Code w/ Claude

Anthropic. Hannah Moran and Jeremy Hadfield from Applied AI walking through how to phrase tool calls and agent prompts on a real Pokemon-playing agent — when to push behavior into the system prompt versus the tool description, what the model needs to know about each tool's preconditions. Useful immediately after you write your first MCP server and find Claude calling it in unexpected ways.