The ONE Decision
That Changed
My Agent Architecture

A personal story about over-engineering

My Biggest Mistake

3 weeks building complexity

0 weeks learning from real users

The system was beautiful.
And completely unnecessary.

What I Built (The Complex Version)

Multi-Agent System

• Agent 1: Intent Classifier
• Agent 2: FAQ Retrieval Specialist
• Agent 3: Knowledge Base Searcher
• Agent 4: Response Generator
• Agent 5: Quality Checker

Plus:
• Orchestration Layer
• State Management
• Message Queue

For a problem that needed: Answer customer FAQs

Complex vs Simple

Complex (Never Shipped)

Accuracy 87%

Latency 2.3s

Cost/Query $0.08

Lines of Code 2,847

Time to Build 3 weeks

Shipped Never ❌

Simple (Shipped Week 1)

Accuracy 84%

Latency 0.9s

Cost/Query $0.02

Lines of Code 156

Time to Build 1 afternoon

Shipped Week 1 ✅

The Realization

I was optimizing for the wrong thing

What I Optimized For:

❌ Architectural elegance
❌ Future scalability
❌ Engineering best practices
❌ Interesting problems

What I Should Have Optimized For:

✅ Time to first user feedback
✅ Learning velocity
✅ Shipping value
✅ Real user problems

Why We Over-Engineer

Because it's interesting.

A single-agent system? Boring. I'd built those before.

A multi-agent orchestration system? Novel! Challenging! Something to talk about!

I wasn't solving the client's problem.
I was solving my own boredom.

We confuse complexity with sophistication.

The Decision Framework

Before adding complexity, ask:

Question 1

Does this solve a real user problem?

Not a hypothetical future problem

Question 2

Is there a simpler solution?

That I'm dismissing because it's "not interesting"?

Question 3

Can I test this quickly?

In days, not weeks?

If ANY answer is uncertain → Choose simpler

Key Principle

You Can Add Complexity Later

When you hit real limits.
When you've tried optimizing simple.
When you have data proving it's necessary.

You Can't Easily Remove Complexity

Once it's built, it's tech debt.
Every layer adds debugging surface.
Removal requires rewriting.

Therefore: Start simple → Ship → Learn → Iterate

When Complexity IS Justified

Criterion 1

You've shipped simple and hit real limits

Not theoretical limits. Real users saying "this is too slow."

Criterion 2

You've tried optimizing the simple version

Better prompts, better retrieval, better caching.

Criterion 3

Complexity solves a measured problem

Latency improved 3s → 1s. Accuracy improved 80% → 92%.

Evolve, Don't Over-Architect

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Learn to build production agents that evolve
Not perfect architectures that never ship

What We Teach:
• When single-agent vs multi-agent
• How to evolve based on real usage
• Production patterns that matter
• What to optimize for at each stage

Next Cohort: February 15, 2025

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For senior engineers with 3+ years experience

                Ship simple. Learn. Iterate.

                That's how production systems are built.

The ONE DecisionThat ChangedMy Agent Architecture