توسعه نرم‌افزار با هوش مصنوعی از اولین پرامپت تا کد نهایی در محیط عملیاتی

عنوان دوره : Maven – AI Software Development: From First Prompt to Production Code

سطح : پیشرفته

زمان کل دوره : 12 ساعت و 48 دقیقه

تعداد فايل ها : 8

سال آموزش : 2026

فایل تمرینی : دارد

مربی دوره : Mihail Eric

نرم افزار : Adobe InDesign

زیرنویس انگلیسی : ندارد

Maven – AI Software Development: From First Prompt to Production Code

Last updated 7/2026
By Mihail Eric
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 8 Lessons ( 12h 48m ) | Size: 2.3 GB

Increase developer productivity with AI-first, production-ready workflows

Today many developers use AI, but few are maximally productive with it. I created Stanford’s first AI software development class, and after building a YC-backed coding company and leading AI at Amazon, I’ve seen how top engineers integrate AI into production workflows. My techniques have been used to train 200+ Stanford engineers and industry professionals.

My goal is simple: make you dramatically more productive writing software with AI than without it.

In this course, you’ll learn practical, end-to-end workflows for using AI in real-world development, not toy examples.

We’ll cover
Building production features with AI agents using the research → plan → implement → test workflow
Configuring an optimal AI native dev environment for your specific tech stack (IDE, code review, tool integrations, and beyond)
Setting up review and CI processes that catch AI errors, hallucinations, and slop before production
Enabling multiple agents to work together on the same codebase without conflict, accelerating software delivery and throughput
If you’re ready to write better code, ship to production faster, and stay in control of your coding agents, let’s get started.

What you’ll learn
Ship production features 2x faster by using coding agents across research, planning, implementation, testing, and review workflows

Configure optimal AI-first developer environments to improve your coding output

Set up any AI dev environment (Cursor, Claude Code, Windsurf) with custom prompting patterns optimized for your tech stack and coding style

Learn how to navigate the ecosystem of cutting-edge AI developer tools

Choose the right AI coding tools for your use case (lessons from evaluating 100+ products in the market)

Exercise effective strategies for prompting and building with coding agents

Build production features using the research → plan → implement → test → review loop that handles complex software tasks

Reduce hallucinations, software errors, and AI slop all while shipping faster

Identify which tasks coding agents handle autonomously and which need human oversight (and set up automated checks for both)

Become a manager of coding agents so you can keep many agents productive

Coordinate 3+ coding agents asynchronously on the same codebase without merge conflicts or quality issues

Develop a deep intuition for how AI coding platforms work under-the-hood

Build your own coding agent and MCP server from scratch to understand how Cursor and Claude Code actually work

Learn how agents like Claude Code are prompted and context engineered to handle autonomous software tasks

Who this course is for
Engineers who want to increase their productivity with AI-generated code while making it actually production grade.

Engineering managers who want to ensure their teams aren’t being left behind when it comes to the new way of developing software.

Those confused about how to develop with AI the right way (how to maintain context and manage multiple agents without compromising code)