What Are the Best AI Skills for “prompt engineering”?

8 skills tagged “prompt engineering”, each forged from a YouTube creator's methodology.

Cloud Guru

Cloud Guru LLM Engineering Production Framework

Apply a complete, layered methodology to design, build, harden, and deploy production-grade LLM systems — from raw transformer mechanics through agents, RAG, security, cost control, and enterprise integration — without hand-waving or magic.

19 Sept 2026
Rajeev Kanth | BEPEC

Rajeev Kanth Agentic AI Architecture Stack

Design and build a production-ready AI agent by applying a structured 7-layer architecture that ensures autonomy, tool integration, memory, and safety guardrails.

12 Sept 2026
Nishant Chahar

Chahar Zero-to-80 AI Mastery Roadmap

Apply a structured 12-week progression to go from AI beginner to confident AI generalist who can automate work, build agents, and ship apps without writing code.

4 Sept 2026
The Neuron

Neuron 5-Level AI Proficiency Stack

Move from total AI beginner to effective daily user by building capability across five concrete levels — projects, prompting, skills, automations, and agents — in the right sequence.

29 Aug 2026
Nick Saraev

Saraev AI Agent Orchestration System

Deploy multi-agent architectures that parallelize work across specialized AI models, self-correct over time, and produce higher-quality outputs than any single-model approach.

22 Aug 2026
bri

Bri's Production Prompt Engineering Method

Eliminate inconsistent AI agent behavior by applying a systematic set of prompt design rules and audit practices that produce repeatable, predictable outputs in production.

7 Aug 2026
JavaScript Mastery

Adrian's Vibe Engineering Build Framework

Build any full-stack AI web app by having the AI write its own detailed implementation prompts, which you approve before a single line of code is written — eliminating back-and-forth and producing consistent, production-quality results.

7 Aug 2026
DataTalksClub ⬛

Grigorev RAG Application Build Framework

Build a working Retrieval Augmented Generation (RAG) application from scratch that answers domain-specific questions using a private knowledge base — without retraining any LLM.

17 July 2026