Most engineering teams are already using AI — but without a shared framework, it often creates more risk than leverage.
Engineers skip planning, generate large diffs, and rely on reviews to catch mistakes. Juniors hesitate to use AI at all. Seniors are skeptical. Managers struggle to define what “good” AI usage looks like. The result is inconsistency, bad habits, and uncertainty around ownership.
This course exists to reset the baseline.
AI doesn’t replace engineers — it changes what engineers are responsible for. The highest-leverage work is no longer typing code faster, but exploring systems, planning changes clearly, reviewing output skeptically, and maintaining ownership of what ships.
In this accelerator, you’ll learn a repeatable, production-ready workflow for using AI responsibly. We focus on how staff engineers actually work: turning vague ideas into reviewable plans, generating code incrementally, and holding humans accountable for outcomes.
This is not a vibe coding course. It’s a mindset and workflow shift designed to make AI safe, fast, and trustworthy in real production environments.
Move from ad-hoc AI usage to a clear, repeatable workflow for shipping production software with confidence.
Learn the Explore → Plan → Build framework used by senior engineers to turn vague ideas into reviewable, low-risk plans.
Practice incremental code generation and stricter review habits so AI output is production-safe.
Learn how to interrogate systems, architecture, and dependencies using AI without hallucination-driven thrash.
Replace days of trial-and-error with structured exploration and informed decision-making.
Learn when async delegation helps — and when it creates more problems than it solves.
Run background research, refactors, and audits while maintaining full human ownership.
Adopt workflows that produce smaller, clearer diffs that are easier to review and reason about.
Learn how to review AI-generated code more skeptically than human-written code.
Establish a common language for planning, ownership, and review that managers and engineers can align on.
Prevent AI adoption from devolving into tool-driven chaos or hype cycles.
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Founding Engineer @ Multiple Exited Startups
Engineers who want consistent, production-safe workflows, not guesswork or oversized diffs.
Team leads and managers responsible for AI adoption who need practical standards, not hype or tool comparisons.
Engineers tired of vibe coding and social-media advice who want real workflows from someone shipping code daily.
You should be comfortable building and maintaining features in your primary language or stack so you can focus on workflow, not syntax.
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Live sessions
Learn directly from Vignesh Mohankumar in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
Mar
18
Fundamentals
Mar
18
Live Coding Example
Mar
18
Wrap-up / Discussion
Mar
19
Coding Agent Tooling
Mar
19
Coding Agent Infrastructure
Mar
19
Wrap-up / Discussion
Mar
20
Optional: Hackathon/Office Hours Session 1
Mar
20
Optional: Hackathon/Office Hours Session 2
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Discover how Codex transformed OpenAI's workflow and master the essential features driving productivity
Apply proven prompt strategies and hidden capabilities used by OpenAI engineers in real projects
Implement Codex effectively in your development stack using OpenAI's tested approaches
Live sessions
14-20 hrs
Live Coding Session and Hackathons
Wed, Mar 18
4:00 PM—6:00 PM (UTC)
Wed, Mar 18
6:30 PM—8:30 PM (UTC)
Wed, Mar 18
8:30 PM—9:00 PM (UTC)

$950
USD