Vignesh Mohankumar – Agent-First Software Engineering
Original price was: $1,350.00.$142.00Current price is: $142.00.
Learn how to interrogate systems, architecture, and dependencies using AI without hallucination-driven thrash.
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Description
Vignesh Mohankumar – Agent-First Software Engineering
Ship production code 10× faster with the workflows staff engineers actually use
You’ll see us build real software using the exact workflows we use in our own consulting work. This is not a vibe coding course.
We built this accelerator because we’re engineers first. For the past few years, we’ve been using AI tools to ship production features that used to take weeks in days. We started by sharing these workflows privately with the senior engineers we worked with. We created this accelerator to scale the knowledge to hundreds of developers.
You will learn both:
- Synchronous workflows — coding live with AI, structuring state and context, getting clean and correct code out of models.
- Asynchronous workflows — background jobs, automated agents, Slack triggers, multi-step processes that run while you focus on something else.
And we cover everything that surrounds coding, too:
- Design-doc generation from meeting notes
- Debugging with AI
- PR review workflows
- Custom commands, sub-agents, rules
By the end of the accelerator, you’ll have a repeatable engineering framework you can apply to any codebase, stack, and dev environment. And you’ll walk away having shipped a real feature using these methods.
Trusted by 200+ developers.
What you’ll learn
Move from ad-hoc AI usage to a clear, repeatable workflow for shipping production software with confidence.
Plan and ship AI-assisted features without losing ownership
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Learn the Explore → Plan → Build framework used by senior engineers to turn vague ideas into reviewable, low-risk plans.
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Practice incremental code generation and stricter review habits so AI output is production-safe.
Use AI to explore and understand large codebases faster
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Learn how to interrogate systems, architecture, and dependencies using AI without hallucination-driven thrash.
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Replace days of trial-and-error with structured exploration and informed decision-making.
Apply asynchronous agents safely and intentionally
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Learn when async delegation helps — and when it creates more problems than it solves.
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Run background research, refactors, and audits while maintaining full human ownership.
Improve PR quality and reduce review friction
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Adopt workflows that produce smaller, clearer diffs that are easier to review and reason about.
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Learn how to review AI-generated code more skeptically than human-written code.
Build shared standards for AI usage across teams
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Establish a common language for planning, ownership, and review that managers and engineers can align on.
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Prevent AI adoption from devolving into tool-driven chaos or hype cycles.
Learn directly from Vignesh
Founding Engineer @ Multiple Exited Startups
Who this course is for
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Engineers who want consistent, production-safe workflows, not guesswork or oversized diffs.
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Team leads and managers responsible for AI adoption who need practical standards, not hype or tool comparisons.
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Engineers tired of vibe coding and social-media advice who want real workflows from someone shipping code daily.
Prerequisites
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Experience shipping production software
You should be comfortable building and maintaining features in your primary language or stack so you can focus on workflow, not syntax.
What’s included
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.
Course syllabus
Week 1
Mar 25—Mar 27
Day 1 — Fundamentals of AI Software Engineering
- Mar 25
Fundamentals
- Mar 26
Live Coding Example
- Mar 26
Wrap-up / Discussion
Day 2 — Advanced Workflows
- Mar 26
Coding Agent Tooling
- Mar 27
Coding Agent Infrastructure
- Mar 27
Wrap-up / Discussion
Day 3 — Hackathon & Implementation
- Mar 27
Optional: Hackathon/Office Hours Session 1
Optional
- Mar 27
Optional: Hackathon/Office Hours Session 2
Optional
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