About Stewart Labs

Stewart Labs is the personal research wing of Jason Stewart — a person who, by all external appearances, seems completely normal, until you discover he has voluntarily written code to determine which letter of the alphabet is the *least* compatible with forming five disjoint 5-letter words.

Jason is a long-time engineer, technologist, data tinkerer, and certified “I can totally automate that” personality type. He’s spent more than two decades helping people understand complex technology, and then he goes home and voluntarily makes it more complex for fun.

Stewart Labs is where those experiments live. And yes — they asked for none of this.

Stewart Labs operates on a few core principles:

• If a question is pointless, it is probably interesting.

The world has enough dashboards tracking quarterly KPIs. What the world does **not** have is a multi-hour computational analysis of which single English letter refuses to cooperate with a 25-letter word union.

Jason naturally gravitates toward these “nobody asked, but we’re doing it anyway” projects — because sometimes the joy is in the rabbit hole, not the conclusion.

• Music data belongs in a lab too.

Jason is also the creator of Setlist Oracle, home of thousands of meticulously organized Bob Dylan performances, concert histories, and tour maps.

t Stewart Labs is where the more experimental concepts go: clustering songs, analyzing transitions, mapping musical eras, and building weird-but-wonderful tools that only Dylan fans and data engineers could love.

• Tools should exist even if no one asked for them.

Proposal generators? Sure. API-assisted setlist validators? Why not. A Python script that screams “HIT CAP (50M)” during an alphabet-wide search? Absolutely.

Stewart Labs is a playground for creating things simply because they are fun to create. If they end up being useful — bonus.

• Python is always the answer. Even when it isn’t.

Jason has developed a perfectly healthy, completely rational belief that Python should be used for everything. Data analysis? Python. Backtracking search that might be faster in C? Python. A task that screams “this should be Rust”? Still Python.

This is not because Python is always the best tool for the job — it often isn’t — but because consistency, readability, and personal stubbornness matter. If a solution can be written clearly, instrumented obsessively, and allowed to run overnight while printing node counts to the terminal, then Python has done its duty.

Stewart Labs proudly embraces this philosophy: choose the language you know well, then push it far past where common sense suggests you should stop.

• Curiosity first. Questions later.

The guiding philosophy of Stewart Labs is simple: follow the interesting thread and see what happens.

Maybe it becomes a useful tool. Maybe it becomes a dataset. Maybe it becomes a six-hour computational experiment that discovers “only J and X behave nicely in the Wordle universe.”

Either way — that’s the fun of it.

If you're reading this page, you’re probably a curious person too. Or you clicked the wrong link. Either way, welcome. Stewart Labs is always open for the next strange idea.