Working with AI

Build with AI

Prompting your way to working software. Vibe coding, code review, working on existing codebases.

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01

Vibe coding: prompting your way to a working app

The describe to generate to test to refine loop. What "vibe coding" actually means in practice. Where it breaks.

6 min read
02

Pick your build environment: Lovable vs Bolt vs Cursor vs Claude Code

When each shines. Browser-only no-code, IDE pair programmer, terminal agent. Decision matrix included.

7 min read
03

Catching AI-generated bugs before they ship

Hallucinated APIs, missing edge cases, security holes. How to review AI code without being a senior engineer.

7 min read
04

Working with AI on a codebase you didn't write

CLAUDE.md, context files, repo conventions. How to teach an agent your codebase so it stops hallucinating its way through your patterns.

7 min read
05

Prompts vs Skills vs Workflows vs Agents — when to use which

Four ways to use AI: a one-shot prompt, an installable skill, a step-by-step workflow, or a multi-step agent. What each one does well, where each breaks, and how to choose.

8 min read
06

How RAG works, and when to use it

The pattern that grounds an LLM in your data: how each step works (chunking, embedding, retrieval, reranking, generation), when RAG wins over fine-tuning and long context, and the failure patterns most beginner systems hit. With a modern 2026 stack.

11 min read
07

Prompt, skill, RAG, knowledge base, or fine-tune? A decision guide

The five ways to get an AI to do what you want — a better prompt, a reusable skill, retrieval over your data, an indexed knowledge base, or fine-tuning. A decision order that starts with the cheapest and only escalates when you hit a real wall.

8 min read
08

RAG vs an indexed knowledge base: what is the difference?

They sound like the same thing and the terms get used interchangeably. The practical distinction — what each actually retrieves, when keyword/index search beats vector RAG, and why most real systems end up using both.

7 min read
09

How to create an AI agent

The three honest ways to build one (no-code, a coding framework, or from scratch), with a first build for each, the failures to design for, and the resources worth your time. It starts with the question most people skip: do you even need an agent?

10 min read
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Take your build from prototype to production. Real deploy, real monitoring, real ownership.