$ the JSM Skills Workflow, live. tap a skill below.
TAP A SKILL TO RUN IT · THIS IS THE ACTUAL WORKFLOW
/scopePlans what to build
/auditCaptures project context
/architectDefines the technical approach
/developBuilds the feature
/checkVerifies the changes
/testWrites tests
/documentWrites project docs
/syncUpdates project context
/debugFinds and fixes bugs
/scopePlans what to build
/auditCaptures project context
/architectDefines the technical approach
/developBuilds the feature
/checkVerifies the changes
/testWrites tests
/documentWrites project docs
/syncUpdates project context
/debugFinds and fixes bugs
//The wall everyone hits
Greatfor30minutes.Thenthecodebasefightsitself.
Quality over one AI session
You type "build the login page." You're impressed. Then new features break old ones, the AI contradicts a decision it made an hour ago, and you keep prompting, hoping it fixes itself. It doesn't.
prompt & hopewith structureQualityTime →~30 min: still greatthen it collapses
This isn't an AI problem. It's a workflow problem. And no tool, plugin, or subscription fixes that.
//The real skill
Theskilliswhathappensbeforeyoutype.
01Knowing what to withhold
Less context, better output
The instinct is to give the model everything. The skill is knowing what to leave out, because the wrong 400 lines pull it toward the wrong answer with total confidence.
output quality
sweet spot
less contextmore → worse
02Knowing when it's drifting
Catch it at loop three, not thirty
The model doesn't announce when it's drifting. Reading what comes back the way a senior reads a junior's PR, that's the skill. You catch the wrong turn at loop three, not after it's built thirty loops on top of it.
output quality
driftingcatch @ loop 3
loop 1loop 30
03Read the wrong turn
Stop the drift
Catch the AI heading confidently the wrong way and steer it back onto the intended path without throwing the whole thing out.
intendedoff-track
Almost nobody teaches this, because until you're the one holding it, "AI coding" looks figured out. It isn't. That gap is the course.
//The turning point
SoIspent12monthsfindingthemiddle.
Approach A · too heavy
Nine context files
Loaded every session. They go stale, the window fills before you write a line of feature code.
collapses under its weight
The system
The JSM Skills Workflow
Somewhere in between and it took longer to find than I expected.
holds up as projects grow
Approach B · too light
Quick prompts, trust it
Minimal context. That's just vibe coding with extra steps until things get complex.
breaks the moment it scales
//The cost of skipping it
Webuiltthesameapptwice.Here'sthebill.
"The fast way gets expensive later" is easy to say so we didn't just say it. We built the same app both ways and put the real numbers side by side.
Vibe-coded
The fast way
Cost to build$180
Cost to run$2,400/mo
When it had to scale+ $14,000
Year one$42,980
The workflow
The system
Cost to build$340
Cost to run$260/mo
When it had to scale$0
Year one$3,460
Sameapp.12×thecost-nearlyallofitafterlaunch.
Figures from one real build. Yours will differ; the shape won't.
//What makes this different
Onelinein.Shippedcodeout.
Open-source commands you install into your projects. But watch what it refuses to do.
Type one line describing the feature, and the workflow runs the loop. But this isn't "generate whatever compiles."
When it hits a decision nobody made, it stops and asks, instead of guessing and building the wrong thing silently. An AI that refuses to decide things behind your back.
one loopper feature
01/develop build the checkout pageYou type one line.
02The skill writes the full promptIt reads your codebase and your project plan for you.
03You review & push backSomething off? Say so. Then say go.
04The AI builds itFeature code, following your patterns.
05A different model reviews itA second opinion from a second doctor.
06You ship itThen run the loop again. Every feature.
//What real work looks like
Everyoneteachesscenarioone.Youliveinallthree.
◆What AI courses teachWhat you actually do all day →
Greenfield · ~20%
New features in a live project
Code you inherited
Most courses drill the 20% you rarely do. This one covers all three.
new-project
▸ src/empty$ /scope
idea → blueprint
Scenario 1~20% of the work
Empty folder
An idea, no code yet. The workflow challenges the idea before a line is written, then makes the technical calls for you.
/scope/architect/develop
The part others teach. We teach it better but it's not where the value is.
app · live
+
next feature
Scenario 2every day
Live project, new feature
Add payments. Fix search. Build a dashboard. The workflow picks the next feature and runs the loop. No re-explaining, no scope creep.
/scope/develop/review
What you actually do every day at work.
80,000 LOC
unknown patterns
Scenario 3most common · least taught
80,000 lines you didn't write
Add a feature without breaking anything. Nobody teaches this. /audit reads the codebase and learns its conventions before you touch a file.
/audit/develop/review
The most underserved scenario in all of AI education.
//The workflow selector
WhichworkflowshouldIrun?
Run only the workflows a change needs. Different changes take different paths.
What are you working on?
New product
Empty folder. Start from scratch, then create the project's context.
/scopechallenge the idea
/architectmake the calls
/developbuild it
ship ✓
New feature
Existing project. Understand it first, then plan and build.
/scopefrom your codebase
/developenforce the design
/reviewsecond model checks
ship ✓
Legacy code
80k lines you didn't write. Learn the patterns, then move safely.
/auditread the codebase
/developmatch conventions
/reviewverify nothing broke
ship ✓
Something broke
Diagnose why before fixing. Take the shortest safe path.
/debugfind the real cause
/developtargeted fix
/reviewconfirm the fix
ship ✓
//What you get
Theskillsarefree,butthejudgmentisn't...
Free, open-source skills are normal in this space now, we ship ours, others ship theirs, install them all. That's not the argument.
The argument is what happens after you install them. Use ours for a week and you'll notice the hard part was never running the commands.
It's knowing which one to reach for, what to decide when it stops and asks, whether the AI's recommendation is any good, and what to do when the plan is wrong. You can't install judgment from a GitHub repo. That's what the course is, and it's the part no repo, ours or anyone's, can hand you.
/develop/develop
Stage 04 · build
Builds a feature from its spec, user interface or backend. For UI, it enforces your design system straight from a screenshot.
$/develop checkout page/developcheckoutpage
→matched 12 components
→to your existing tokens
//Who this is for
Youalreadywritecode.
Four quick checks. If the first three sound like you, this was built for you.
Yes: You use AI daily but feel like you're doing it wrong. This is exactly who it's built for.
Yes: Your projects work great for 30 minutes, then fall apart. The workflow fixes the structural problem behind that.
Yes: You're a working developer and the ground is shifting. You don't need to be senior. You don't need TypeScript.
Not you: You've never written a line of code. Not yet. Start with the free JavaScript content first.
//What's inside
Eightmodules.Onecompletesystem.
It starts before the workflow, understanding how these agents actually work. Then greenfield, then shipping into a live project, then the two things that earn the price: legacy recovery, and building your own skills.
The tool was never the skill14:22
Context is the whole job21:40
The calls you make before typing18:05
Installing the skills9:48
Your first /scope16:12
Running the loop end to end24:35
The /architect Command Pattern12:10
Automated PR Reviews20:53
Handling Context Collapse18:31
Orchestrating Multiple Agents47:33
Picking the next feature15:20
Shipping without scope creep26:41
Teaching the project to remember19:07
Auditing 80,000 lines you didn't write28:14
Learning a codebase's conventions22:36
Safe, incremental refactors33:41
Why the builder can't review itself11:55
Wiring the review pass23:18
Reading the failure mode17:44
Polluted sessions and how to reset20:09
When the foundation is wrong25:52
Challenge: ship a feature solo31:26
Worked solution walkthrough29:03
//From the community
It'snotthemodel.It'sthestructure.
“
I ran your six-file context system with a model that's not even Claude-level, and the results were genuinely surprising. It made the model perform closer to Sonnet. That's when your point clicked — it's not about the model, it's about the structure you give it.
Mostafa·SketchUp extension developer“
I use Claude Code daily and I still feel like I'm not doing it right.
Krish·Working developer“
Yesterday I was selected as a junior backend developer without having a degree. I just passed high school. I've learned so much of web development from you.
Shahnoor·JSM student“
Big thanks to you, Adrian! You taught me from zero to pro, and now I've built my dream app and got a job. Plus, I just finished creating an AI that understands me perfectly. Thank you for everything!
Levis·Web developer“
I've learned production-level skills that I didn't gain from my work experience. We didn't do that in my previous company.
Alvin·JSM Pro member“
Most developers start AI coding the wrong way. They delegate everything, or they delegate nothing. Both are reactive.
Satwik·Software developer“
I really love this approach to agentic coding. It boosts confidence of the developer, knowing exactly what to expect from tasks given to AI. Thanks Adrian.
@theophilusaika·JSM community“
I really love the way you teach — it feels energetic and engaging. You can say one line to teach a topic where others need five. My biggest regret is I couldn't get JSM Pro for lifetime when it was in beta. JSM Pro is a course every developer needs in this AI era.
Hamza Aryan Sapnil·JSM Pro member“
Recently joined JSM Pro, and got my first real dev job in just a few months. It gave me exactly what I needed to switch careers. Staying subscribed for the community!
Arjun Mehta·JSM Pro member“
JSM makes the best real-world projects out there. I landed a good internship by showing one of the projects he made on his YouTube channel. Also, The Ultimate Next.js course is just unmatchable.
Jai Srivastava·Developer“
My dev career started by being thrown in the deep end without any previous training, and I struggled for about 2 years just doing YouTube tutorials. After going through all of your courses at my own pace, I found my confidence and abilities scaling to new heights. I recently landed an awesome new job with the exact specs I was looking for.
Tyron·Developer
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//Before you decide.
FrequentlyAskedQuestions
Agentic engineering is the practice of directing AI coding agents through a structured workflow, scoping, architecting, building, verifying, and recovering, instead of prompting them one message at a time. Where "vibe coding" means describing a feature and hoping the output holds up, agentic engineering keeps the developer in the role of decision-maker: the agent executes, but a human makes the architectural calls and catches it when it's wrong. It's how developers work with AI on real production codebases rather than one-off demos.
The JS Mastery Agentic Engineering Course is a self-paced course that teaches developers a complete, repeatable workflow for building real software with AI coding agents. It covers the full sequence, from scoping an idea to shipping and maintaining it, and includes the scenarios most courses skip: extending a live project, taking over legacy code you didn't write, and recovering when the AI gets something wrong. It's built around nine open-source skills that run as one system.
This course is for developers who already write code, from junior to senior, who want to work with AI agents on serious projects instead of just prompting in a chat window. You don't need to be senior; you need to be comfortable building something small on your own, a component, an API route, a simple app. It's not for complete beginners who've never written a line of code, and we say so plainly up front.
You need to be able to write code, use a terminal at a basic level, and navigate a code editor. That's the whole technical prerequisite. You do not need to know any specific framework, any AI tool, or anything about agents going in, the course builds all of that from the ground up. The one non-technical prerequisite that matters more than any skill: a willingness to change how you work.
The free YouTube channel is where these ideas were figured out in public; the course is the figured-out version, organized as one system and taught on real projects. The videos show you individual pieces. The course connects them into a workflow you can actually run start to finish, and adds the parts that never make good videos: legacy code, recovery when things break, and the judgment for when to use what.
Most AI coding courses teach the tools, the fundamentals, and a greenfield "build this app" project. This one is built around four things they mostly don't cover: a single sequenced workflow that runs as one system instead of a toolbox of separate commands; taking over legacy code you didn't write; recovering when the AI ships something subtly wrong; and a real before/after case study with the actual cost shown. The fundamentals are here too, they're just the floor, not the whole course.
No, it's close to the opposite of vibe coding. Vibe coding means describing what you want and accepting whatever the AI produces; this course keeps you as the engineer directing the work. The AI becomes the fastest junior developer you've ever worked with, and your job is to make the decisions, review what comes back, and catch it when it's wrong.
Yes, if you've hit the wall where AI works fine on small tasks but falls apart on bigger or messier projects. Move quickly through the early fundamentals if you already run agents daily, then slow down at legacy codebases and recovery, because that's where even experienced agent users are usually improvising rather than following a system.
Yes. The workflow and the nine skills are tool-agnostic and run on Claude Code, Cursor, Codex, Gemini CLI, and other agents. The value is in the sequence and the judgment behind it, not in any single tool, so it stays useful as the tools change.
AI replaces developers who only execute instructions, not the ones who make architectural decisions, catch the AI's mistakes, and own the codebase. As code generation becomes a commodity, judgment becomes the scarce, valuable skill, and judgment is exactly what this course is built to teach. The agent doesn't give you judgment; it raises the price of not having any.
