Wonderfully Weird 🌟

The Philosophy ✨

Wonderfully Weird is what happens when you build systems that weren't really designed—they just grew. You start with a simple idea, add another simple piece, then another, and suddenly you have something that works beautifully but makes no sense to anyone who didn't watch it evolve.

These systems work precisely because they weren't planned. They emerged from actual use, shaped by real needs, growing organically like a garden rather than being architected like a building. They're weird because no one would deliberately design them this way. They're wonderful because they actually work.

How It Happens 🌱

You don't set out to build something weird, you didn't really set out to build anything at all. You just wanted to solve a simple problem with the simplest possible solution, something that required the least amount of work but not only solved the problem at hand, but that entire class of problem. They always come back otherwise.

Then you need to solve another problem, so you add another simple piece. Or you have an idea, while in the middle of something completely different, about how that little reporting pipeline really should be an API. Because then all those little CLI tools could share an output engine with that Jenkins pipeline. Then suddenly you realize that wanting to simplify how one development team handles post-release cleanup now means that everyone gets a real time dashboard for each and every one of their delivery pipelines. The pieces start talking to each other in ways you didn't expect. Behaviors emerge that you didn't plan for but turn out to be exactly what you needed.

Before you know it, you have:

A task manager that's also a knowledge container to facilitate multi-agent workflows
A websocket based markdown renderer for viewing AI generated content that grows into the real time display engine for the entire playform
A diagnostic and reporting tool that can also correct any issues it finds, and embed itself along side your code to tell its story about what happened to anyone else that happens across a similar issue
An executable markdown file that merges the power of Jupyter notebooks with narrative storytelling to usher in the next generation of Infrastructure as Code tooling, that not only tells you what and where, but also how, why and when
Systems that do things you can't quite explain but can't live without

The Neurodivergent Advantage 🧠

When your brain naturally sees everything as small, interconnected pieces rather than monolithic wholes, you build the same way. You don't architect grand systems—you grow gardens of simple components that happen to work together.

This isn't a design choice. It's just how things naturally emerge when you:

Start with the smallest possible solution
Add only what you need, when you need it
Let the system tell you what it wants to become
Trust emergence over architecture

Ulimately, it's institutionalized laziness. Nothing comes for free and everything is a conscious descion to take that next step. Break the big problem into manageable chunks, process those chunks with strong pattern matching and systemic thinking, and what emerges is recognition. The problem space is finite. Find the lynch pin and watch as an entire class of tasks melts off the board.

Real Examples 🚀

The "Put It Up on the Big Screen" System

Started as a websocket-based markdown rendering viewport so I could display AI-generated knowledge artifacts on a monitor. Just wanted to say "put it up on the big screen" and have it appear. Now it's the cornerstone of an entire platform's real-time portal, with web components rendering from custom markdown containers to facilitate dashboards and live output from delivery pipelines. No one plans to build a platform display engine. You just wanted to show something on a screen, flip your shades down and scream "Yeah!!!" once in a while.

The Executable Markdown That Became Infrastructure

Spent all day rewriting the core of an API to streamline AWS API calls to work around heavy contention and throttling causing monitoring noise and deployment failures. Deployed an eFix that reduced a 18s+ thread poll destroying call to a one time cold start penalty and consistent 100ms performance. The response was from my management was a question as to why we had spent time on that and not following up on AWS' suggested change to our Datadog settings.

Created a markdown-based Jupyter clone for Infrastructure as Code—markdown that represents a serialized graph with code or data at each node, plus children and textual content for literate IaC. Now YAML workflows run inside self-executing markdown documents. It's infrastructure that tells its own story while it deploys itself. Try explaining that in a design review. And I used it to reply "because this is how much it will cost us for each cluster, by cluster" as a series of markdown documents, attached to the Jira ticket, as a subtle way of saying "because my way doesn't cost us an extra $500,000 in Container Insights costs"... "oh, and this is Casebook :)"

The Detective Cases That Weren't

Built a temporal event stream and knowledge container system. Needed a metaphor that made sense, so I dressed it up as detective case logs. Now it's hooked into MCP + API + CLI as a personal assistant and knowledge worker enhancement system called the Recursive Mirror. It works because it grew from actual detective work (debugging), not from trying to build a detective system and as it turns out, if you get a bunch of theatre kids (LLMs trained on centuries of human knowledge and tradition... story telling) and get them to play detective, you get a really powerful system with a bunch of agents that really want to write down what they're doing and why. And if you're clever, and you've built a markdown wrapped YAML based workflow engine that happens to be able to call the same tools the agents that are working the "case" can because they both proxy the same central APIs, then you can build a pretty simple funnel to convert those solved cases with all those notes into actual workflows that anyone can run, and pack in enough narrative so that they know why they are and what to do when Mr Murphy comes a knockin'.

Why They Work 🪄

These systems succeed because they:

Evolved from actual use, not theoretical requirements, each solved a real problem in a way that allows it to snowball
Grew with their users, adapting to real workflows, define simple basic functions, let their use define the next layer of composite function - don't dictate use, allow it to emerge and make utility simple to capture
Embrace simplicity at the component level, do one thing well but be friendly to your neighbours
Allow emergence at the system level, don't build platforms, build eco-systems - provide the building blocks and let the environment dictate the platform
Feel natural because they match how you actually think, provide multiple approaches, fail-safes and varied abstractions - things will break, things won't work - and then they will, and it will surprise you and then you'll see

They're like desire paths in parks—the trails people actually walk, not the sidewalks someone planned. They work because they're honest about how things really get used.

The Recognition Pattern 👁️

When people first encounter these systems:

"This doesn't make any sense" → "Why does it work this way?" → "Oh, it just grew like this" → "Actually, this is perfect for what I need" → "I couldn't imagine it working any other way"

The confusion is real. These systems don't follow best practices or design patterns. They follow emergence patterns—the shapes that naturally form when simple things interact over time. They learn from you because you ultimately create them when you use them. The best systems get out of your way.

I facilitate workflows, a simple tool to list this, an API to fetch that. Dump this into a file, sort that, strip that and feed it over there. Next time, a script might do steps 2, 3 & 4 and by the end of the month it's an API. By the end of month three it's an API that's integral to the entire system because somewhere along the way, steps 2, 3 & 4 went from being a problem to being a component in a system. Don't just solve the problem at hand, extract the core of the problem into a solution and make it resuable you've solved that problem forever. And just like a good problem keeps coming back to haunt you, a good solution will always come back to save you.

The Invitation 💌

Wonderfully Weird isn't a methodology you can learn. It's what happens when you:

Let the system evolve through use
Start building before you finish planning, 60% of something today is worth infinitely more than 100% of something "when it's ready"
Trust emergence over architecture
Embrace the weird if it works
Accept that the best systems often make no sense until they make perfect sense

It's permission to build things that work even if you can't quite explain why. To create systems that no one would design but everyone wants to use once they exist.

The best systems aren't designed. They grow. They emerge. They become. And yes, they're weird—wonderfully, beautifully weird - just like me. 🌟