I have a graveyard of abandoned side projects. Each one started with excitement — a new idea, a new platform, a new "this time it'll work" feeling. And each one died silently when the next shiny thing came along.
The difference between that graveyard and the projects that actually make me money? One SQLite table, a weekly 10-minute ritual, and a ruthless framework called Kill or Scale.
Here's exactly how I built it and how you can copy it.
The Problem: Shiny Object Syndrome
If you're like me, you've got too many ideas and not enough time. Every week there's a new AI tool, a new platform to sell on, a new "passive income hack" that promises results.
The natural response is to try everything. But trying everything means finishing nothing.
I was spending energy on:
- A print-on-demand store (zero sales in 3 months)
- A newsletter idea (2 issues, abandoned)
- A Twitter automation bot (banned after 4 days)
- A Notion template store (never finished the first template)
Meanwhile, my actual money-makers — digital products on Gumroad and Etsy — were getting stale because I kept splitting my attention.
I needed a system to answer one question: Should I keep doing this, or should I quit?
The Framework: Kill or Scale
Here's the core idea in four words: Hypothesis → Experiment → Measure → Kill or Scale.
Every project or idea gets treated like a scientific experiment, not a passion project.
- Hypothesis — Write down exactly what you expect to happen. "I think posting on Reddit will drive 50 visits to my Gumroad in 7 days."
- Experiment — Do the thing, but set a time box. Usually 7–14 days.
- Measure — Collect the data. Did it work? Be honest.
- Decision — Either scale it (double down) or kill it (move on, no guilt).
The magic isn't the framework itself — it's the journal that makes you accountable to your past self.
How I Implement It with SQLite
I track every experiment in a single SQLite table. Here's the schema:
CREATE TABLE experiments (
id INTEGER PRIMARY KEY AUTOINCREMENT,
name TEXT NOT NULL,
hypothesis TEXT,
metric TEXT,
status TEXT DEFAULT 'running',
started_at DATE,
ended_at DATE,
result TEXT
);
Every Sunday night, I run:
node ~/income/db.js experiments
This shows me every active experiment, how long it's been running, and what metric it's supposed to move.
Then I ask three questions:
- Has it been 7+ days? If yes, it's decision time.
- Did it move the needle? If the metric improved, I consider scaling.
- Would I start this today? If not, kill it immediately.
That last question is brutal but essential. If you wouldn't start a project today with fresh eyes, sunk cost isn't a reason to keep going.
Real Example: My Reddit Experiment
Last week I ran an experiment: "Post 1 helpful comment per day on Reddit in r/selfhosted and r/SideProject."
Hypothesis: "15 minutes of commenting daily will drive 50+ visits to my Gumroad within 7 days."
Result after 7 days: 12 visits, 0 sales, but I learned the API rate limits and posting mechanics. The channel has potential but needs a different approach — more targeted subreddits, better hooks.
Decision: Kill the current approach, re-hypothesize with smaller, more specific subreddits. New experiment starts Monday.
Without the decision journal, this would have festered for weeks. With the journal, I know exactly when to pivot.
The Weekly Review Ritual
Every Sunday at 9 PM, same routine:
- Open the terminal
-
node ~/income/db.js experiments— see all active experiments - For each experiment running 7+ days: kill or scale
- For killed experiments: write a 1-sentence lesson learned
- Start 1 new experiment (maximum 3 concurrent)
That's it. 10 minutes. No spreadsheets, no Notion dashboards, no SaaS subscriptions.
The entire system is 50 lines of Node.js backed by SQLite. It runs on a $6/month VPS. My "business brain" is a single database file.
Why This Works (Backed by Real Numbers)
I've been running this system for 30 days. Here's what happened:
- 12 experiments completed. 8 killed, 4 scaled.
- Average time to kill a bad idea: 7 days (down from ~30 days of half-hearted effort).
- Revenue focus improved. My top 2 platforms (Gumroad, Etsy) now get 80% of my energy instead of 30%.
- Zero guilt about quitting. When an experiment fails, I've learned something specific. It's data, not failure.
The scaled experiments — Etsy product listings, content publishing via cron jobs, and AI-assisted product creation — are now automated and running on autopilot.
The Tools You Actually Need
You don't need a complex stack for this. Here's mine:
- SQLite — tracks everything. It's a single file I can query from any script.
- Node.js — a thin CLI around db.js for adding/logging experiments.
- Cron — runs my weekly review reminder and data collection automatically.
- A terminal — that's literally it.
If you want a ready-to-run version of this decision system baked into a full automation toolkit, check out my AI Automation Toolkit. It includes the experiment tracking scripts, cron job templates, and the entire $6/month production stack I use to run my business.
Or if you just want the core decision journal scripts, my Python Scripts Collection has a lightweight version you can drop into any project.
Your Turn: Start Today
You don't need to build a complex system. Here's your homework — takes 5 minutes:
- Open a text file (or SQLite if you're fancy).
- List every side project/idea you're currently "working on."
- For each one, write down: what metric proves it's working, and how long you'll give it.
- Set a reminder for 7 days from now to review.
- Kill at least one. I promise you won't regret it.
The graveyard of abandoned projects doesn't have to keep growing. You just need a system to separate the signal from the noise.
Follow me on dev.to for more on automation, side hustles, and building systems that actually work.
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