How I went from burning $1,000/month on token costs to building production-ready applications with AI agent swarms
If you’ve experimented with AI coding assistants in the last year, you’ve probably experienced the intoxicating rush of “vibe coding”—that magical feeling when you describe what you want in plain English and watch code materialize before your eyes. But you’ve likely also hit the wall that comes after: spaghetti code, lost context, and the creeping realization that your AI-generated masterpiece is held together with digital duct tape.
I’ve spent the last six months deep in the trenches of AI-assisted development, and I want to share a fundamental shift in thinking that’s transformed how I build software. It’s the difference between vibe coding and what I call “agentic engineering”—and understanding this distinction might just save you from the $800-1,000 monthly token bills I was racking up while learning these lessons the hard way.
The Vibe Coding Trap
Let’s start with what we all know and love: vibe coding. It’s our first taste of AI-assisted development, where you create by instinct, often without a predefined plan, focusing on the moment. Tools like Bolt.new, Lovable.dev, and dozens of others have made it possible to spin up a prototype in minutes using nothing but natural language.
The numbers are staggering—Lovable.dev alone is generating about 30,000 apps per day. Clearly, people are finding value here. And for good reason: vibe coding is perfect for:
- Rapid prototyping
- Learning new technologies
- Building simple, personal-use applications
- That dopamine hit of instant creation
But here’s the thing about vibe coding that nobody talks about until they’re deep in a project: the longer you vibe, the bigger mess you make.
The Context Window Crisis
Picture this: You start a ChatGPT session to build a feature. The AI suggests, “Would you like to add this one extra thing?” Of course you do. “How about this brilliant little polish?” Sure!
Thirty minutes later, your context window is completely saturated. The AI can no longer remember what you were building in the first place. It starts contradicting earlier decisions, reimplementing things differently, or worse—confidently hallucinating solutions that look right but subtly break everything else.
I once spent an entire afternoon in this loop, ending up with an over-engineered monstrosity where an environment variable validation got stuck in an infinite loop, effectively locking me out of my own application. The sunk cost fallacy had me pumping more tokens into fixing it rather than admitting defeat and starting over.
The Quality Problem
Even when context isn’t an issue, vibe coding has a fundamental quality problem:
- No cleanup: Each iteration adds code without removing the old
- No architecture: Solutions are point-to-point, not systematic
- No consistency: Different parts of your app follow different patterns
- No tests: The AI rarely writes tests unless explicitly prompted
- No documentation: Comments and docs are afterthoughts
Enter Agentic Engineering
This is where agentic engineering comes in. Instead of creating by instinct, an agentic engineer works with:
- Defined architecture
- Clear processes
- Deliberate steps from concept to completion
- Every decision serving a purpose within a larger vision
The shift is profound. Instead of being the person frantically typing prompts and copying code, you become the architect orchestrating specialized AI agents that each excel at specific tasks.
My Journey Through the Tool Landscape
Let me walk you through my expensive education in this space:
Stage 1: The Copy-Paste Era
Started where we all did—copying code from ChatGPT, Claude, or Gemini into my IDE. Great for snippets, terrible for anything substantial. The context problem hit hard and fast.
Stage 2: The VS Code Extension Phase
Experimented with various VS Code extensions, eventually landing on Cline and its fork, RooCode. These were game-changers because they:
- Maintained memory across sessions
- Could analyze existing projects
- Introduced multi-agent teams with orchestrators
RooCode’s innovation was particularly interesting—using “boomerang tasks” where an orchestrator maintains project context while farming out specific tasks to specialized agents with limited, focused context.
But the costs… oh, the costs. I was burning through $800-1,000 per month, mostly on Claude Sonnet tokens. And sometimes I’d end up with code so complex I couldn’t even understand what I’d built.
Stage 3: The Claude Code Revolution
About two months ago, everything changed when I started using Claude Code as my daily driver. Within a week, I’d uninstalled RooCode, Cline, and every other extension.
Claude Code feels like drinking water from a mountain spring instead of through layers of filtration. It works better than external APIs, and with Anthropic’s Max subscription plans ($50-200/month), I could develop unlimited (with time-based cooldowns instead of hard token limits).
The game-changer? Claude Code has native support for sub-agents that can run in parallel. What used to take 2-3 days now takes 3-4 hours.
The Paradigm Shift
Here’s what makes agentic engineering different from vibe coding:
1. Planning First, Coding Second
Before writing a single line of code, you create:
- Detailed Product Requirements Documents (PRDs)
- User stories with acceptance criteria
- Test strategies (yes, before the code exists)
- Architecture diagrams
This feels backwards at first, but it’s the secret to getting quality output from AI agents.
2. Specialized Agents, Not General Assistants
Instead of one AI trying to do everything, you have:
- Architecture agents that design systems
- Developer agents that implement features
- QA agents that write and run tests
- Review agents that ensure code quality
- Documentation agents that keep everything updated
3. Structured Workflows, Not Conversations
Agentic engineering follows established patterns like SPARC (Specifications, Pseudocode, Architecture, Repeat, Complete) rather than free-form chat sessions.
4. Memory and Context Management
Unlike vibe coding where context is lost between sessions, agentic systems maintain:
- Persistent memory in SQLite databases
- GitHub checkpointing for rollback capabilities
- Shared context between specialized agents
The Results Speak for Themselves
Since adopting agentic engineering, I’ve built:
- A complete community platform (think OpenSocial but modern)
- A Flowwise to Langchain converter
- A Drupal to Supabase migration tool
- Multiple production applications for clients
The kicker? These aren’t prototypes. They’re production-ready applications with:
- Proper test coverage
- Consistent architecture
- Clean, maintainable code
- Actual documentation
Is This the Death of Traditional Development?
Not quite. But it’s definitely a transformation. As Drupal’s founder Dries Buytaert recently called it: “Software on Demand.” We’re moving from building universal solutions to creating personalized software for specific needs.
The economics are compelling. Why pay for a SaaS connector when you can have AI build exactly what you need in hours? Why maintain legacy systems when you can have them rebuilt with modern stacks in days?
What’s Next?
In the next post, I’ll dive deep into the practical setup of Claude Code and Claude Flow—the tools that make agentic engineering possible. I’ll show you exactly how to go from zero to running your first agent swarm.
But here’s my challenge to you: Stop vibe coding for anything beyond prototypes. Start thinking like an agentic engineer. Plan your architecture, define your requirements, and let specialized agents do what they do best.
The difference between spending 20 minutes building a todo app that actually works (like I demonstrated during my presentation) versus spending hours debugging context-confused spaghetti code? It’s all in the approach.
Have you experienced the context window crisis? What’s your biggest frustration with AI-assisted development? Drop a comment below or reach out—I’d love to hear about your journey.
Next up: The Modern AI Development Stack: Claude Code + Claude Flow – A practical guide to setting up your agentic engineering environment
