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Pragmatic AI Coding: Cursor, Local Models & SDLC
Rating: 5.0 out of 5(7 ratings)
48 students

Pragmatic AI Coding: Cursor, Local Models & SDLC

Ditch the 10x hype. Learn to write durable code, review AI outputs and run private local agents.
Created byDávid Ondruš
Last updated 5/2026
English
English [Auto],

What you'll learn

  • Adopt a mindful approach to AI coding to avoid career-damaging overuse, misuse, and blind reliance on AI outputs.
  • Differentiate between durable and disposable code to know exactly when to leverage AI and when strict manual oversight is needed.
  • Master the critical skill of rigorously reviewing and auditing AI-generated code to guarantee production-level quality.
  • Adapt AI strategies safely to your seniority level (Junior, Mid, Senior) to accelerate your career instead of ruining it.
  • Master Cursor IDE and local AI tools to safely write, refactor, and debug code without compromising security or code integrity.
  • Deploy 100% private, local AI models using LM Studio for secure, agentic coding without compromising data privacy.

Course content

5 sections • 32 lectures • 2h 59m total length

  • 10x Productivity With AI - Myth or Reality?3:21
  • How Junior, Medior, Senior Use AI4:48
  • Focusing On AI Good, Mitigating the Misuse6:54
  • Types of AI Help in Software Development4:36

    Divide ai tools into three types: chatbots, code editors, and ai software engineers. For developers, code editors offer project context and direct editing, while chatbots serve learning and brainstorming.

  • AI IDEs (Code Editors)2:50
  • Where AI Saves Time - Create Use Case3:39
  • Where AI Saves Time - Read, Refactor, Update, Delete4:33
  • SDLC Phases With AI Help1:46

Requirements

  • A Critical Mindset: You must be willing to learn how to evaluate code. This course is not about using AI as a powerful assistant, not a replacement for your own thinking.
  • No Prior AI Experience Needed: You don’t need to be an AI expert. We will teach you how to properly integrate AI into your workflow from the ground up.
  • Basic Programming Knowledge: You should have a foundational understanding of programming and software architecture so you can effectively review the code the AI generates.

Description

Are you tired of the toxic "10x Productivity" AI hype?

Everywhere you look, they are promising that AI will write your entire application for you with a single click. But in the real world of professional software development, blind reliance on AI is causing a crisis.

Junior developers are slowing down their growth by copying and pasting code they don’t understand, ruining their foundational skills from the start. Senior developers and Tech Leads are drowning in hardly maintainable "spaghetti code." Careers are being negatively impacted because people are jumping on the AI without a critical, pragmatic and mindful approach.

It’s time to stop misusing AI and start using it like a professional.

Welcome to Pragmatic AI Coding: Cursor, Local Models & SDLC. This course is the ultimate antidote to AI hype. It is designed to teach you how to integrate AI into the Software Development Life Cycle (SDLC) safely and securely. I don't just teach you how to generate code; I teach you when you should, and more importantly, when you shouldn't accept suggestions from AI.

What makes this course different?
Here, you will learn the critical difference between durable code (core architecture that should last and be maintainable long-term) and disposable code (scripts and boilerplate where AI excels). You will learn how to rigorously review AI outputs, mitigating risks and protecting your codebases and your career.

Inside the Course:

1. The "Pragmatic AI" Mindset & Career Strategy

  • Debunking the "10x productivity" myth and finding the realistic AI baseline.

  • Sharing my own statistics - how AI affected my productivity? What's my % gain?

  • Customized AI strategies for Junior, Medior, and Senior developers: How to use AI to accelerate your specific career stage without sabotaging your technical growth.

  • Sharing my experience - how some juniors I mentored ruined their careers with AI?

  • Understanding exactly where AI saves time and where it wastes it.

2. Mastering AI-First Development with Cursor IDE

  • Deep dive into Cursor workflows: Agents, line code completion, fixing bugs, and using advanced Cursor Rules, Skills, and Commands.

  • Integrate Cursor to non-AI-first IDE (WebStorm).

  • Bridging the gap between Business requirements and Technical prompts.

3. Real-World Task Execution

  • Real SDLC workflow: Task analysis, converting business requirements into technical assignment, architecture design, refactoring legacy code, auditing logic, and successfully deleting technical debt.

  • Debugging production crashes safely with AI assistance.

  • Building complex features from scratch.

  • Using multiple AI models in parallel and comparing their results, choosing the best.

4. 100% Private, Local Agentic Coding

  • Working under an NDA or in a strict enterprise environment? You cannot send proprietary code to OpenAI or Anthropic.

  • Learn how to set up LM Studio and run completely private, local AI models right on your machine.

  • Integrate local models directly into your IDE (like WebStorm) for secure, offline, agentic coding with OpenCode.

5. Choosing the Right Models

  • Understanding the AI landscape: When to use local models vs. powerful cloud models like Claude Opus.

  • Why Claude Opus thinks differently about code, and how to harness it for complex logic.

  • When to choose the most powerful model available and when it's enough to choose the cheap one.


If you want to protect your career, write better code, and master the tools of the future without falling for the hype, this course is for you.

Enroll today and take control of your AI workflow!

Who this course is for:

  • Developers Overwhelmed by AI Hype: Programmers who are tired of the "10x developer" myths and want a grounded, realistic, and mindful approach to integrating AI into their daily workflow without overusing it.
  • Junior Developers Protecting Their Careers: Early-career devs who want to accelerate their learning with AI safely, avoiding the fatal mistake of letting AI write code they don't understand, which can stunt their long-term growth and ruin their career foundations.
  • Senior Developers and Tech Leads: Experienced engineers who need to establish AI coding standards for their teams. If you are responsible for reviewing AI-generated pull requests and need to teach others the difference between "durable" (core architecture) and "disposable" (quick scripts) code, this course is for you.
  • Privacy-Conscious Engineers: Developers who want to leverage the power of AI but work under strict NDAs or in enterprise environments, requiring the use of 100% private, local models (like LM Studio).

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