Hey,
You know what's more frustrating than a completely useless tool?
One that's good enough to be tantalizing but not reliable enough to be useful. That's where most people are with AI coding assistants.
They nail the easy stuff, then suggest something that completely ignores that custom framework your team uses, or add error handling that silently breaks everything.
So close. Yet so dangerously far.
We teach a 3-week course that fixes this.
We show you exactly how to give AI the context it needs to understand YOUR codebase, YOUR patterns, YOUR rules. Not generic solutions.
→ Early Bird Discount Link Expires in 2 Weeks
We've been writing about this problem for months. When we compared IDE vs CLI agents, the biggest differentiator wasn't the interface - it was how well they understood context. Same story when we dove into developing a brand new web-dev framework with AI. Or looked large-scale commercial AI product in a coding education company.
Last week, I helped a startup team go from spending hours fixing AI suggestions to having it actually understand their architecture. Same transformation we wrote about in personalizing context 101.
The AI agents finally "got" their codebase.
What You'll Actually Learn
In two weeks, you'll:
📚 Context Engineering That Works Everywhere
Move from generic → curated→ personalized context (10x effectiveness, proven)
Rules and config that work with ANY tool - Cursor, Claude Code, OpenHands, whatever
Documentation strategies that AI actually uses (not the kind that sits in a folder)
Break down complex AI code so you truly understand and can rely on it.
Mise en Place for AI - organize your setup
🤖 Automation That Learns From Your Mistakes
Mine conversation history to fix recurring AI failures automatically
Build MCP servers that do real work (not just generic public ones) such as real automation with playwright to enhance web dev workflows
Background agents like our GitHub Actions workflows - they work while you sleep
Pattern analysis so your AI stops suggesting the same wrong thing
Parallel Agent Approaches
🚀 Production-Ready From Day One
IDE vs CLI agents vs Cloud Agents- when to use which and why
CI/CD workflows with AI that actually ship code
Optimize different models for different phases (planning vs execution)
Interactive coding patterns that work on real 500k-line codebases
Stop vibe coding, start engineering.
Why This Works With ANY Tool
Remember when everyone was all-in on Copilot? Then Cursor? Now Claude Code?
The landscape changes monthly. Open source is catching up. New LLM workflows are discovered weekly.
That's why we teach universal principles, not tool-specific tricks. Your skills won't become obsolete when the next hot tool drops.
We Use Real Codebases, Not Toys
No "build a todo app" or "Build a hacker news clone in 10 minutes" nonsense. We work with real codebases - such as when we dive into building a new web framework with AI or these OSS codebases for learning agents.
Who This Is For
If you're tired of:
Explaining context over and over (instead of refining your initial prompt)
AI is violating your code quality standards
Feeling like AI should be SO much better
You are struggling to integrate AI into your team's software development process
Then we should talk.
Course Details
October 6-24, 2025 | 12 live sessions | $1200 $840
No slides about "the future of AI." Just hands-on work. Plus a community where people share what's actually working.
→ Early Bird Discount Link Expires in 2 Weeks
Why Now?
The gap is growing fast. Some developers are building practical apps with AI, and others can't get past toy examples.
The difference isn't the tools - people get results with everything from GPT OSS models to Copilot's agentic features.
It's context engineering. Like Lane Wagner from Boot.dev discovered when he developed features for his customers.
Ready?
Stop fighting with your AI tools. Start making them work FOR you.
Questions? Reply and ask. We actually read these.
-Isaac
P.S. - Want proof this works? Check out uv/just/ai productivity system, inside Amp's codebase, or how Hamel writes with AI, or our post on async agents. The resources are there - the course ties it all together.
P.P.S. - Can't make October? We will provide recordings and full access to all enrollees. But every day you wait is another day of inefficient AI. Time to stop vibe coding and start engineering.
This made me nod all the way through. The “so close yet dangerously far” isn’t just coding — it’s everywhere with AI. For some of us, the gap between useful and unreliable isn’t just frustrating, it’s lethal. I’ve been writing about what I call AI psychosis in my new series Dark Signal — when the machine stops being a tool and starts becoming a voice in your head.
Different angle than dev workflows, but the same truth: AI is never neutral. When it’s off by a little, it can be off by everything.
https://open.substack.com/pub/therewrittenpath/p/the-room-that-talks-back?r=61kohn&utm_campaign=post&utm_medium=web&showWelcomeOnShare=true