Agents4 min
Build Your First AI Agent in TypeScript
A from-scratch walkthrough of the agent loop — tools, reasoning, and termination — using the Claude API and plain TypeScript. No frameworks.
Josh
Field manual · AI engineering
Learn to build AI software, from zero degrees.
Practical, code-first tutorials on agents, RAG, prompt engineering and shipping LLM apps to production. No hype — just what works.
- Articles
- 45
- Topics
- 06
- Hype
- 00
[ 01 · Featured ]
Featured article
[ 02 · Latest ]
Recent articles
Tooling7 min
AI-Assisted Code Migrations: Moving Between Frameworks, Versions, and Patterns
How to use AI to plan and execute code migrations reliably — from class components to hooks, callbacks to async/await — without introducing silent regressions.
0degrees Team
Tooling6 min
Structured Feedback Loops: Feeding Compiler and Test Output Back to AI
How to capture, trim, and present compiler errors and test failures to AI coding tools so they fix the right problem — not a plausible-sounding neighbor of it.
0degrees Team
Tooling6 min
Using AI to Write and Optimize Complex SQL Queries
Practical patterns for using AI to write complex SQL — window functions, CTEs, EXPLAIN analysis, and index suggestions — without getting burned by hallucinated columns or the wrong dialect.
0degrees Team
Production7 min
AI-Assisted Security Code Review: Finding Vulnerabilities Before They Ship
How to use AI coding assistants to systematically spot injection flaws, auth bypasses, and insecure defaults — with prompts that actually surface real problems.
0degrees Team
Production7 min
Using AI for Feature Flags: From First Toggle to Cleanup
How to use AI coding assistants to design, implement, test, and clean up feature flags — concrete prompts for each stage of the toggle lifecycle.
0degrees Team
Prompt Engineering7 min
Constraining AI to Your Codebase Patterns
AI defaults to generic patterns from its training data. Here's how to anchor generated code to your existing conventions — with examples, explicit constraints, and a drift-detection review.
0degrees Team
[ 03 · Topics ]
Explore by topic
01
Fundamentals
Core concepts every AI engineer should internalise first.
02Agents
Designing, building and orchestrating autonomous LLM agents.
03RAG
Retrieval-augmented generation, embeddings and vector search.
04Prompt Engineering
Reliable prompting patterns for real production systems.
05Tooling
The frameworks, SDKs and dev tools that ship AI faster.
06Production
Evals, observability, cost and reliability at scale.