Organic Flow: Clarity-First Development

Created: 2025-07-29 Context: Rethinking Organic Flow without metaphors, focusing on clear thinking

The Core Idea

Software development has a fundamental problem: we treat code as permanent and knowledge as temporary. This is backwards.

Code changes constantly. Knowledge - the understanding of problems, constraints, and solutions - is what endures. Organic Flow inverts the traditional relationship: knowledge becomes primary, code becomes secondary.

What This Means in Practice

Traditional Development

Write Code → Maybe Document → Knowledge Often Lost

Knowledge-First Development

Capture Input → Form Hypothesis → Experiment with Code → Extract Learning → Knowledge Persists

The Simple Workflow

1. Capture Inputs

Anything that sparks development:

Problems: “Users are losing their work”
Ideas: “What if we cached everything?”
Feedback: “The app feels slow lately”
Observations: “This pattern worked in another project”

2. Form Hypotheses

Before coding, state what you think will work:

## Hypothesis: Extend Session Timeout

If we extend sessions from 30 minutes to 4 hours,
then users won't lose their work,
assuming our infrastructure can handle the memory load.

3. Experiment in Branches

Create experiment/session-timeout-4hr for quick test
Or impl/session-management for larger feature
Implement the solution
Test your assumptions
Discover reality

4. Extract Knowledge

What actually happened?

## Learning: Session Timeout Experiment

**Result**: Failed - Redis ran out of memory

**Discovered**:
- Each session uses ~2MB of memory
- 90% of users are active for less than 1 hour  
- The real problem wasn't timeout length but lack of auto-save

**New Understanding**:
Don't solve the obvious problem, solve the real problem.

5. Apply Learning

Update requirements with evidence
Document newly discovered constraints
Inform the next experiment

Why This Works

Knowledge Compounds

Each experiment builds on previous learnings. Failed experiments often produce the most valuable insights.

Clear Thinking Produces Clear Code

When you can explain the problem conversationally, the solution often becomes obvious.

Nothing Is Lost

When developers leave or code gets rewritten, the accumulated understanding remains.

Real Example: The Session Story

Monday - The Problem

Sarah from support reports: "Users are losing hours of work when they get 
logged out. It's our #1 complaint." #problem:data-loss

Tuesday - The Hypothesis

We think: If we extend the session timeout to 4 hours, users won't lose work.
Assumption: Our Redis instance can handle longer sessions. #hypothesis:extend-timeout

Wednesday - The Experiment

git checkout -b experiment/4hr-sessions
# Quick test: just change the timeout value
# Change timeout, deploy to staging

Thursday - Reality Hits

Redis crashed at 3am. Memory usage: 80GB for 10k users.
Math: 10k users × 2MB × 4 hours = 80GB #limit:redis-memory

Also discovered: 90% of sessions last < 1 hour. We're solving 
for the wrong problem. #insight:usage-pattern

Friday - The Real Solution

New hypothesis: Auto-save every 30 seconds prevents data loss 
without infrastructure changes. #hypothesis:auto-save

This worked! Real problem was losing work, not session length.
#pattern:question-assumptions

The Key Shift

Instead of asking “What code should I write?”, ask:

What problem am I really solving?
What am I assuming to be true?
How will I know if it works?
What can others learn from this attempt?

Branch Types: Experiment vs Implementation

Both experiment/ and impl/ branches are for testing ideas - they differ in scope and intent:

experiment/ branches

Purpose: Quick, focused tests of specific hypotheses
Timeline: Hours to days
Scope: Single idea or assumption
Example: “Will caching improve search speed?“

impl/ branches

Purpose: Build features with intent to ship
Timeline: Days to weeks
Scope: Multiple integrated patterns
Example: “Build complete search system with caching, indexing, and UI”
Note: Can spawn their own experiments

Both produce knowledge through Knowledge PRs. The difference is that successful impl/ branches can become release/ branches.

Starting Today

You don’t need special tools. Just:

Before coding: Write down what you’re trying to solve
During coding: Note surprises and discoveries
After coding: Extract what you learned via Knowledge PR
Always: Share patterns that others can use

The Payoff

For You: Never solve the same problem twice
For Your Team: Build on collective understanding
For Your Future: Code can be regenerated from knowledge
For Your Organization: Institutional memory that actually works

Remember

Clear thinking produces clear code. Document the thinking, and the code becomes obvious.

The code is temporary. The understanding is forever.