If you have ever tried to animate a limbless vertebrate in a real-time game engine, you know the specific brand of madness involved. Snakes do not have legs, inverse kinematics foot-targets, or rigid skeletal hierarchies. They are continuous, deformable, muscular splines. Getting a virtual Burmese python to slither across flat ground is tricky enough; getting one to climb a vertical tree trunk without looking like a stiff foam pool noodle or clipping through the bark like a broken physics object has been one of the toughest technical roadblocks in developing Invasion of the Burmese Python.
Then came the most unexpected reference footage in indie dev history: a video of an actual pet python scaling a brass dance pole. It looked ridiculous at first glance, but from a VFX and computer vision perspective, it was pure gold. Here is how that clip solved our procedural locomotion math—and why visual isolation made all the difference. (Note on credit: I screen-captured the original pole reference clip from a 24-hour story before it vanished and haven’t been able to track down the original poster—if you know whose snake this is, let me know so we can give them proper credit!)
The Problem with Wild Reference Footage Before this, I had spent hours analyzing documentary footage of pythons ascending cypress trees in the Everglades. While the footage was gorgeous, feeding those clips into tracking and machine-learning analysis tools was an exercise in frustration: • Occlusion & Clutter: Dappled sunlight, drooping Spanish moss, and background sawgrass constantly confuse optical flow algorithms. • Organic Bark Irregularities: Rough tree bark introduces chaotic bumps and micro-grips, making it nearly impossible for tracking models to determine which parts of the body are providing radial clamping force versus which are simply resting. • Motion Blur & Camera Shake: Documentary telephoto shots rarely provide a clean, steady orthogonal view of the contact mechanics. The tracking models kept failing to extract a usable kinematic equation because the data was drowning in visual noise.
“Shed It All!” — When a dance pole turns out to be the cleanest kinematic test cylinder in computer vision.
Why the Pole Changed Everything: The Compositor’s Principle Anyone who has spent time doing roto, camera tracking, or face-replacement knows that contrast and edge isolation are king. A vertical dance pole is a friction-tested, uniform cylinder. In the video, the snake was filmed indoors under even lighting against a neutral background. The visual noise of the swamp was completely stripped away.
Because the contact surface was mathematically perfect (a uniform radius r along the Z-axis), the computer vision and mathematical modeling tools could clearly parse: • Concertina Contact Anchors: Exactly where the snake created stationary friction loops around the circumference to lock its weight. • The Dynamic Extension Phase: How the free body segments pushed upward in a tightening helical spiral while the anchor points held. • Radial Clamping Vectors: The precise tangent and normal forces required to hold vertical elevation without slipping down a smooth surface. What had been a messy, ambiguous swamp video became a clean, high-contrast engineering diagram of pure kinematics.
From Video to Calculus: Building the Spline Algorithm Once the motion was isolated from the environment, we translated those biological contact loops into an algorithmic spline curve: • Instead of using canned keyframe animations that slide awkwardly up a trunk, the snake’s armature is now driven along a procedural parametric helix. • The system calculates anchor points based on trunk radius and dynamically tightens or loosens coils as the character ascends. • As the player commands the snake upward, the procedural body feeds through those calculated contact zones, contracting and extending naturally just like real concertina locomotion. Is it 100% finished? Not quite. When our procedural spline crosses secondary branch intersections, you can still catch some temporary geometry clipping. But the foundational weight, coil tension, and upward drive are leagues ahead of anything we had before.
Concept Visualization — Translating uniform cylindrical pole anchors into vertical climbing mechanics across Everglades structures and trunks.
The Real-World Playtests I recently took the build out into the wild across two very different test environments to see how it held up outside my development bubble. First was a stop before heading out, where a 17-year-old kid grabbed the controller. That age bracket has zero tolerance for clunky mechanics or boring tutorials—if a game doesn't grab them, they put the pad down in thirty seconds. Instead, he locked in for a full ten minutes, exploring the swamp and hunting prey, only asking for input when my overly complex battle system got in the way. At the end of the run, he gave it a solid 8/10.
Later that night, I brought the build to a party to test pure spectator appeal. In the middle of a loud room with drinks flowing, people still gravitated to the monitor. Even folks who knew nothing about the Florida Everglades or the invasive python crisis were hooked by the novelty of controlling a limbless predator. The crowd loved the organic swimming locomotion—especially the tail wiggle—and the sheer tension of stalking through the sawgrass. The dual takeaway was crystal clear: the locomotion and creature fantasy already hook people, but the combat needs to shed its complex setup menus. Real players don’t want to navigate multi-step attack preparations when they're an apex predator; they want an immediate strike followed by a tight, satisfying wrap-and-constrict mechanic.
The Lesson: Good Data Beats Complex Guesses In game development—especially when you are leveraging AI tools, physics math, and computer vision—the quality of your reference input dictates your ceiling. Sometimes the best way to solve an organic, messy problem in a virtual swamp isn't to look deeper into the wild; it’s to strip away all the noise until only the raw geometry is left. Even if that geometry happens to be a stripper pole in a living room.
Invasion of the Burmese Python is currently in active development for PC and Mac.
2026-10-18 · DevLog #2 · Invasion of the Burmese Python
The Ghost in the Machine: I Burned 50% of My Weekly Token Cap in One Night — And Woke Up to a New Build
▶ FLIP Fluids Simulation Bake Suite (Unreal Engine 5.8 Alembic Pipeline) — Python waterline strike, mud bank entry, alligator ambush lunge, and 360° alligator death roll churn.
👻 The Ghost in the Machine — Are those ghosts in my house? Zero, just 4 machines screaming at 100% fan speed at 3:00 AM.
It’s October—spooky season—so when a low, jet-engine howl starts vibrating through the drywall in the middle of the night, the natural question is: are those ghosts in my house? Zero. No, that’s just my computers' cooling fans running at maximum RPM like a PlayStation 4 Pro about to achieve liftoff running Gran Turismo on graphics mode (or God of War in an uncapped menu screen). Most indie game developers hit crunch by surviving on lukewarm coffee, ruining their posture at 3:00 AM, and aggressively pushing questionable commits before passing out. Last night, I accidentally invented an entirely different kind of crunch.
I networked three PCs and a MacBook across my townhome, wired them together through Git, turned on local orchestration and LLM tooling, and went to bed. When I woke up, I had burned roughly 50% of my entire weekly token allocation—and sitting on my machine was a fresh, working build. Here is how an unintended autonomous dev studio came to life in my living room, what broke, and what actually worked.
The Distributed Townhome Setup Setting up a multi-machine pipeline usually requires an entire IT department and disciplined version control. In my case, it was a late-night burst of "what happens if I hook all of these together and assign shifts?"
The hardware cluster: • The Main PC Rig: Serving as the central conductor, running local models, managing repository commits, and compiling engine updates. • The 2 Secondary Workhorse PCs: Locked into heavy computational duty—grinding Blender fluid simulations, baking FLIP Fluids / Fluid Flux splashes, and processing high-res water surface caches. • The MacBook: Tasked with the native macOS build pass, running parallel coding tasks, and handling automated documentation and API research. • The Background AI Farm: Hammering away at prompt iterations and farming out concept art and asset generation passes at industrial scale.
The glue holding this Frankenstein operation together was simply Git. Instead of manually pushing changes or babysitting render progress bars, the machines were talking, executing tasks, pushing outputs, and committing updates back and forth across the local network. I set the instructions, let the loop run, closed my eyes, and hoped the house wouldn't trip a breaker before sunrise.
Actual footage of me resting on a log while 3 PCs and a MacBook burned 50% of my weekly token cap on the graveyard shift.
The Autonomous Night Shift When you wake up after running an automated pipeline overnight, there are usually two possibilities: either everything crashed three minutes after you fell asleep on an unhandled null exception, or it went into an infinite loop and racked up an existential cloud computing bill. What actually happened was somewhere in the glorious, chaotic middle.
The machines spent seven hours talking across the network. While the two PCs were churning through gigabytes of baked water meshes and splash particles, the MacBook was quietly crunching code and verifying cross-platform dependencies. Meanwhile, the LLM layer was steadily chewing through tokens to resolve merge conflicts, refactor methods, generate asset batches, and build out gameplay glue code.
By the time the sun came up, roughly half of my weekly token allowance was completely vaporized. My quota took a massive hit. Fans were humming at full blast, and the heat in the room was palpable. But when I pulled up the terminal and checked the latest repo commit: the build was compiled, the splash bakes were done, and the art assets were waiting in the project folder.
What Survived the Night Did it write a flawless AAA game while I was asleep? No. There were a couple of hilarious logic loops, and a few Git commit messages looked like they were typed by an exhausted robot having an existential crisis. But the core deliverables held: • Heavy fluid simulation bakes that normally hijack an entire workday were finished and cached. • The Mac build and its platform-specific dependencies were validated without manual intervention. • Code merges that would have taken two full days of tedious manual typing and bug-hunting were committed, tested, and sitting ready for playtesting. It felt less like solo development and more like hiring a chaotic, caffeine-fueled indie team that worked the graveyard shift in my kitchen.
The Verdict on "Ghost Crunch" Using AI and distributed local machines as a force multiplier isn't about pushing a magic "make game" button. It’s about building leverage. When you're a solo indie dev, your most limited resource is time. If burning 50% of a token cap over eight hours buys back two days of manual labor, bakes all your water simulations, and hands you a playable cross-platform build before your morning coffee, that's not wasted compute—that's compressed time. Just keep a fire extinguisher nearby.
Invasion of the Burmese Python is currently in active development for PC and Mac.
2026-10-04 · DevLog #1 · Invasion of the Burmese Python
It’s Finally Real: Resurrecting the Python, S-Rank Constriction, and Surviving an 870 GB Wipe
▶ Watch DevLog #1 — narrated playtest, Oct 8, 2026Open on YouTube ↗Unreal Engine 5 simulation — A young Burmese python navigating murky shallows at 1:1 scale while an apex avian predator looms overhead like a prehistoric dinosaur.
It started as a side itch. I was experimenting with OpenAI Codex to generate 2D sprite sheets, building Maximum Firepower, a 2D shmup inspired by Capcom's classic arcade shooter U.N. Squadron. I kept pushing code, tweaking movement, and tightening the feel until an actual, addictive gameplay loop clicked. To test it, I handed the build over to my nephew. Now, my nephew has watched me build a million things over the years and usually just gives me the standard polite nod. But this time? He played it, stopped, looked right at me, and said he was actually impressed. When your own nephew gives you real props on a game, you know you hit a nerve. Then my friends Luiz and Alex played it and said straight up: 'James, you need to put this on the App Store.'
Then came the overnight breakthrough. I put the $200 Claude plan to work on Bigglesworth Studios while I was asleep. It was running Blender in the background, upgrading 3D models, and generating gorgeous 3D dioramas for the studio planet that looked identical to the aesthetic of the game. Seeing an AI execute at that level of speed and visual fidelity made a lightbulb go off: why am I only building new prototypes? Why not resurrect the project that literally founded Bigglesworth Studios LLC back in 2013 during my graduate school days at Full Sail?
Back then, Invasion of the Burmese Python was my master's thesis, a registered copyright design document, and a crowdfunding campaign on RocketHub with our mock morning show Wake Up! Florida starring Chief Todd Rowley and his 9-foot python Tiny. When that funding fell short, I pivoted Bigglesworth Studios into a media, video, and technology company to survive—shooting nightclubs and weddings, writing technical docs, and engineering websites for over a decade. But Bigglesworth was always an indie game studio at heart. For 13 years, building the actual game was impossible because I couldn't afford an 80-person studio or multi-million-dollar engineering salaries to solve soft-body simulation. People can talk shit about AI all day, but it made my dream come true. I jumped into Unreal Engine on my PC, and today, that game is an actual functioning reality running right here on my MacBook.
And the wildest part isn't just that it runs—it's that playing it is delivering the exact impactful experiences I predicted on paper back in 2013. You don't start as an apex predator; you start as a vulnerable young snake, which means you are prey. You get your ass kicked Elden Ring-style. In one autonomous play session, I saw a bird looming over the snake that looked like a towering prehistoric dinosaur. It was a Heron, and I thought the scale was broken until Claude verified that the engine is built 1:1 to real life. When you are a two-foot snake on the ground, a Heron isn't just a wetland bird—it's a Jurassic terror stalking you from above. (And digging into the Compendium later, I learned that birds like the Wood Stork pack a Guinness-record 25-millisecond bill-snap—the science is even crazier than fiction).
Then I had a multi-round water fight with an alligator that felt like a heavyweight boxing match. I grappled, struck, retreated to recover stamina, and finally took it down—only for the game to remind me I couldn't even swallow it because my jaw couldn't clear its girth. I took fatal damage for a meal I couldn't consume, learning the brutal ecological lesson that in nature, you should have just slithered away. Later, I stumbled upon a creature with electric blue, green, and purple plumage and thought it was a glitch. It turned out to be an actual native bird: the Purple Gallinule. That discovery sparked the in-game Field Compendium—a Pokémon Snap-style taxonomy index of all 59 Everglades species, designed so anyone who actually lives in the Florida swamp can play this game and say: 'Wow, holy shit, this is my backyard.'
We’re taking that realism into combat with mechanics nobody has ever built. You get graded Devil May Cry-style (S-Rank for predatory execution), but grounded in herpetological science. A python doesn't just squeeze with static force; it feels for the prey's exhalation and ratchets tighter so the lungs can't re-expand, spiking blood pressure to trigger cardiac arrest. We’re channeling that into the controller haptics as a rhythmic pulse: time your squeeze to the breathing to cut off circulation fast, or risk the prey thrashing free. And if you're fighting near the water? Drag them off the bank and drown them under the black water in real time—an organic, player-driven fatality.
So much has evolved in the Everglades over the past 13 years while the game was on ice. Marsh rabbit populations have collapsed by over 90% due to pythons, leading scientists to deploy robotic decoy bunnies with cameras. Influencers like Taylor Stanberry won the 2025 Florida Python Challenge pulling 60 snakes from the swamp, and companies like INVERSA Leathers are turning invasive python hides into luxury boots and loafers. All of that real-world culture, seasonal population cycles, and ecological tension is going straight into the game. And with Grand Theft Auto VI about to shine the biggest global spotlight in gaming history on South Florida, the timing to deliver a mature, serious Interactive Documentary couldn't be better.
Of course, it wouldn't be indie game dev without a near-fatal disaster. While migrating the game from PC to Mac to show friends and prep for PC/Mac Early Access, an automated cleanup command went rogue and wiped 870 GB of data from my PC—Documents, Downloads, Desktop, completely empty. I tried saving it onto an old USB-A drive that crawled for 24 hours only to show 0 bytes. Walmart and Target had nothing in stock, so I drove all the way to Micro Center, dropped $150 on a 2TB USB-C drive, and watched it rip through the recovery. But the real savior was the MacBook: because I already had the game ported and running multi-platform on macOS, development never stopped while the PC was in the ICU.
This is what game development looks like in the new Wild West: where developers can decompile classic Xbox code to run Halo multiplayer in a browser, where a 13-year-old dream gets resurrected from a grad school PDF into a playable reality, and where you survive an 870 GB disaster to ship. Welcome to DevLog #1. Bigglesworth Studios is back in the game.
The Everglades Biological Observatory
Explore the Research Behind the Game
Every encounter described in these DevLogs—from procedural helical tree climbing and FLIP Fluids alligator death rolls to the 25ms Wood Stork reflex—is cataloged in our 120-species Field Compendium.
“Shed It All!” — When a dance pole turns out to be the cleanest kinematic test cylinder in computer vision.
Concept Visualization — Translating uniform cylindrical pole anchors into vertical climbing mechanics across Everglades structures and trunks.
