ZodTTD - App Publisher - AI - Made last year's chart-topping #1 app in App Store, Gamma game emulator. Brought ads to iPhone before it wasn't cool. Florida man.

Florida, US
Joined March 2008
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App Store needed a good Sega Dreamcast emulator so I made it happen. Psimulator has no ads, fully featured. It has miraculous performance from my cores. I guess arcade.gov and I both thought today needed gaming 😄 Get it on iOS App Store: apps.apple.com/us/app/psimul…
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OpenAI Codex performance has been so degraded this week, I'm about to switch out all my subscriptions
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OpenAI let you in and now they raise the walls. Half the usage, twice the price. Starting October 30, 2026, your included usage in ChatGPT Work and Codex will decrease from 20 times to 10 times the ChatGPT Plus allowance. GPT-6 Pro limit in Chat will decrease 200 to 100
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They cut the limits of Pro by 2x and raised the cost of a new tier by 2.5x… on their dev day 😂
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I built a Photoshop-like image editor. It’s called Compositor. robbietilton.com/compositor I originally built it for myself to get off my Adobe subscription, but decided to release it for free and make it open source. It has all the essential tools I need for compositing, with none of the BS. I know this workflow is kind of archaic in 2026, but I’m still using it until AI can actually get pixel-perfect on some of the details. The entire app is 12MB. Photoshop is 6,455MB on my machine.
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Driving down the road in my Delorean with my youngest son, I get a call from my daughter. “Uh dad is that you in the Delorean?” I immediately don’t answer and kick on the fog machines in the back and gun it and hang up on her 😂😂😂😂 She started flashing her brights at my and honking lol. She was driving home from sand volleyball.
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zodttd retweeted
On the 25 ARC-AGI-3 public games, GPT-6 Astra scored 100% using the new provider adapter harness. But that score alone doesn't show just how efficiently it solved them - or how close it came to the fewest-action solutions anyone has found, including runs produced through extensive software-assisted search. The chart below compares three data points for each Public game: 1. The human baseline, calculated by summing the upper-median human action count for each level 2. The number of actions Astra used at max reasoning with the new provider adapter harness, which preserves opaque reasoning across requests and enables auto-compaction 3. The best known valid fewest-action run on each game - aka the speedrun I asked Peter Findley, an engineer who holds or ties the speedrun record on all 25 games, how he produced his runs. He said he used Codex CLI and a custom harness combining object-oriented memory, layered metacognition, skills, and hooks. He used extensive breadth-first search on a 256 GB RAM machine, but says Monte Carlo tree search with negative perturbations found what he described as the global minima. In short, he put a lot of work into programmatically achieving speedruns. So how did Astra do? It crushed the human baseline, using 6,485 actions compared with 17,135. That efficiency, combined with completing every level, is how it achieved 100%. Almost as remarkable is how close it came to several speedrun records. It tied three games (ar25, ft09, and sb26) and came within 5% on three more (s5i5, tu93, and dc22). Summed across all 25 games, the speedruns used 5,502 actions. Astra used 6,485 - 62% fewer than the human baseline and just 18% more than the speedruns. The fact that it came this close in a single recorded run per game, without executing code or repeatedly replaying the games, is incredible. It speaks to how capable Astra is, at least on ARC-AGI-3-like tasks requiring world modeling, spatial reasoning, rule induction, state tracking, planning, exploration, adaptation, and efficient problem-solving.
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The frontier of AI in city-building games over 9 months: Nov 2025 - iso-city.com (left) - Composer 1 + cloud agents Aug 2026 - metropolis-ten-gamma.vercel.… (right) - Grok 4.6 + /loop Full 3D and AAA graphics are within reach.
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We just launched Xirp, a vendor-neutral agentic development environment. One place to manage agent sessions across @ClaudeDevs, @GeminiApp CLI, and @OpenAI Codex. 1,300+ @Spotify engineers already use it. Now it's available for you to try. Learn more at xirp.spotify.com.
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zodttd retweeted
Code RED is live. Priority support for people red teaming Bitcoin software, including reimbursement of past LLM token costs. opensats.org/blog/code-red-s…
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zodttd retweeted
LLMs shouldn’t even need to think about this kinda stuff at all. A small abstraction layer on top of threejs (and physx) lets AI focus on visuals and vibes, while behind the scenes the engine is managing instancing, lod switching, vram and tri budgets, logical vfx particle partitions, and even generating lods and billboards/octahedrals for things like trees, with networked physics, ownership and authority, object runtimes etc. Most of the work i’m doing now has transcended all of this, none of it matters anymore, there are zero limits and no way an LLM can ruin framerate. AI simply focuses on building meshes, vfx, sfx, and making things look and feel good. Most people still need fable and sol max to get good results, but our in-world generations come from extremely cheaper models now because the AI doesn’t have to worry about all the low-level stuff. I highly recommend people spend more time creating core environments that allow AI to express themselves more freely instead of wasting millions of tokens on the same solved problems over and over again.
Replying to @karpathy
We need to teach the AI to use instanced meshes whenever possible... 👀
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zodttd retweeted
Having entirely too much fun lately working on ridiculous music videos & choreography for my latest little album drop. (Her face is intentionally REDACTED as a joke, fyi). Here are a few fun dance sequences I’ve been playing around with today, it’s tedious getting editing and choreography just right, but it’s also super fun! I’ll have some proper music videos here soon. It’s crazy how much we can do for like, $5 nowadays.
🤖 Made with AI
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Improved the Character sprites to walk smoothly Added 3D Dialogue/Context Bubbles that appear over the interacted character’s head Experimenting with a Mixed Reality “Room” Feature that reskins your real world with textures from the game area you’re in Battles are still WIP
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zodttd retweeted
PROMPT: Build me a cel-shaded downhill BMX racing game in Three.js — four riders tearing down a mountain, point to point, at a level of craft above what a AAA studio would ship. Not a demo, not a prototype. A finished game that looks like a piece of published anime-styled game art in every single frame. The bar for this project is not "good for a browser game." The bar is that someone watching a clip of it cannot tell it was made in a browser, and someone playing it forgets to ask. Non-negotiable constraints Stack: Vite + Three.js (latest r1xx), TypeScript, ES modules. I run npm install, then npm run dev, and I'm playing. Nothing else to configure. Zero external assets. No downloaded models, textures, HDRIs, fonts, or audio. Every mesh is built in code, every texture generated in-code (canvas 2D or noise in a shader), every sound synthesized with the Web Audio API. If your own code didn't generate it, it doesn't ship. Target hardware: MacBook M5 Pro, Chrome. A locked 60fps at retina resolution, no exceptions, no frame spikes on jumps or crashes. Use instancing, a terrain clipmap, frustum culling, and adaptive pixel ratio. A beautiful game that hitches is a failed game. Art direction — NPR, and I want it pushed further than anyone pushes it in a browser The whole game is non-photorealistic rendering, anime cel-shaded. Guilty Gear Xrd's ink discipline, Lonely Mountains' terrain readability, the color energy of a Studio Ghibli mountainside. Zero PBR realism. If any surface in the final build reads as physically based, the art direction has failed. Build a real, unified NPR pipeline — not a shader stuck on a few meshes: Ramp / step lighting as the foundation. Custom ShaderMaterial with 3–4 band gradient ramps, NearestFilter, no interpolation. Per-material control over band thresholds and band colors, so rock, dirt, foliage, skin, and metal each get their own tuned response instead of one global look. Tune by eye against captured frames. Two cooperating line systems. Inverted-hull outlines on riders, bikes, rocks, and trees — vertices pushed along smoothed normals, BackSide, width scaled with view distance so screen-space thickness stays constant. Plus a screen-space Sobel edge detect over an MRT normal+depth prepass for interior lines the hull can't produce. Tune them so they never double up into muddy black. Variable line weight. Modulate outline thickness by surface curvature and by distance so lines taper and thicken like a hand-drawn stroke. This one detail is the difference between "toon shader" and "drawn." Stylized shadow interior. In shadow bands, blend in a screen-aligned hatch or halftone pattern at low opacity rather than flat darkness — the way a cel background painter fills a shadow. Subtle. It should read as texture, not as a filter. Fresnel rim light on riders and bikes so silhouettes cut cleanly against terrain at every camera angle. Banded specular with hard-edged highlight shapes on frames, helmets, and wet rock. Fake reflections with a matcap or ramp — never a cubemap probe. Quantized atmospheric depth. Distance fog stepped into discrete bands so far ridges read as flat paper layers stacking into the haze — the classic anime mountain composition. This is what will make your wide shots look painted. Sky and light: gradient sky dome shader, hard-edged cel clouds drifting at two parallax depths, geometric sun shafts through the tree line, a hard-threshold bloom that stays graphic rather than photographic. Generate a color-grading LUT in code and apply it as a final pass. Pick one committed palette — dawn-gold, or overcast-teal, or high-noon alpine — and drive every material through it. Speed and impact — the anime layer A racing game lives or dies on whether speed feels like speed. Build these as real systems: Radial speed lines that ramp in with velocity, drawn as a screen-space post effect, anime-style — subtle at pace, aggressive on boost. Motion smear on the rider and wheels at high speed, and on limbs during trick rotations. Cel-shaded dust and dirt — hard-edged puff shapes kicked up by tires, not soft particle sprites. Puffs on skids, sprays on landings, a trailing plume through scree. Impact frames. On a hard landing or crash, hold for one or two frames with a high-contrast flash — the anime impact convention. Used sparingly it will make hits feel enormous. Camera language: spring-damped chase cam that whips through corners, FOV kick with speed, screenshake scaled to landing force, an automatic swing-around during big air, and a brief slow-mo on the biggest jumps. Terrain — its own AAA-sized problem Give the mountain a dedicated sub-agent and more iterations than anything else. It's most of every frame. Procedural mountain built from layered noise, then run a hydraulic erosion simulation over the heightmap so ridgelines, gullies, and alluvial fans form naturally. Raw noise reads as lumpy and fake; eroded terrain reads as a real mountain. Do the erosion. Altitude and slope banding into material zones — grass and wildflowers low, dirt and exposed rock mid, scree and snow at the peak — with hard cel transitions between zones, not blends. Instanced foliage: toon-shaded trees with billboard-cross canopies, rocks, bushes, grass tufts. Dense enough to feel alive, LOD'd and culled hard enough to hold 60fps. No popping — fade or scale transitions only. Terrain clipmap LOD so the view down the valley runs for kilometers with no seam and no visible tiling. The track A point-to-point downhill run from the summit to the valley floor — not a lap circuit. Design an actual great course, with pacing: A tight technical start on exposed rock, then a fast open scree section to build speed. Bermed switchbacks through the tree line, tight enough to reward braking discipline. A rock garden that punishes bad line choice. Two big jumps — one tabletop, one gap over a ravine — with clear takeoff read. A narrow ridge sprint with real exposure on both sides. A drop into a stream bed, then a final sprint to the finish gate. Built on a CatmullRomCurve3 spline conformed to terrain, rendered as a dirt ribbon with hard-edged cel banding at the trail edges and worn tire-line detail. Checkpoints, split times, wrong-way detection, and a corner-preview indicator. A saved ghost of my best run to race against. Bike physics — arcade, but with real weight Raycast-vehicle style, two wheels, real suspension travel with visible fork and shock compression. Lean and counter-steer, grip curves that differ per surface (rock, dirt, grass, scree), brake slides that scrub speed and throw dirt. Rider input that matters: Preload and pump — crouch to compress, release at the lip for extra air. Timing should be learnable and feel great. Bunny hop and manual. Air control with real rotation authority, and landing angle matching: nail the slope angle and keep your speed, land flat and wash out, land badly and crash. Crash and recovery — a proper physical tumble, not a respawn fade. Tricks with a scoring system feeding a boost meter: tabletop, x-up, superman, tailwhip, 360, backflip, frontflip. Trick input during air, landing cleanly to bank the score. The rider — this is where the AAA claim gets tested The rider animation is the single highest-visibility piece of craft in this game, and it's what everyone gets wrong. Build a procedurally animated rig with proper IK: Hands stay locked to the bars through every movement. Feet stay on the pedals. No sliding, no detaching, ever. Spine bends into lean, head turns to look into corners and toward landings. Arms and legs absorb landings with real compression timing, sequenced — wheels, then fork, then legs, then spine, then head. Pedaling cadence tied to speed; standing versus seated posture depending on terrain and effort. Distinct, readable trick poses — the silhouette alone should identify the trick. Crash animations with limbs reacting to the impact direction. If a critic sub-agent looks at a frame and sees a rigid mannequin bolted to a bike, that subsystem is not done, regardless of how far along the rest of the game is. The race Me plus 3 AI riders. Spline-following with lookahead steering and terrain awareness, jump timing they can actually get wrong, per-rider personality (one aggressive and crash-prone, one clean and fast, one erratic), collision and avoidance between riders, and mild rubber-banding so the race stays close to the finish. They should make mistakes — beating them has to feel earned. Countdown start, live position and gap display, results screen with times, placement, trick score, and an automatic replay of my biggest air of the run from a cinematic camera. HUD in the same cel style — speed, position, checkpoint splits, boost meter, trick score popups, a route profile showing my progress down the mountain. Hand-designed, not default HTML. Audio, all synthesized: chain and freewheel clicks, tire tone shifting by surface, wind rising with speed, suspension compression, impacts, a start horn. How I want you to work Fan out sub-agents. One owns terrain generation and erosion. One owns the NPR pipeline and line work. One owns bike physics and feel. One owns rider rig and animation. One owns AI and race logic. One owns camera, speed FX, and impact language. One owns HUD and audio. One owns performance. Define the shared architecture first, then run them in parallel. Build the capture harness before anything else. Playwright, headless, able to load the game, drive it to a specific moment, and capture retina frames from multiple angles — and capture frame sequences and short video clips. Stills are not enough for this project: animation and speed feel can only be judged in motion, so the harness must produce motion for the critics to review. Run two separate critic sub-agents. A stills critic judging composition, line work, banding, palette, and silhouette. A motion critic judging animation quality, weight, camera feel, and whether speed reads as speed. Both must be harsh and specific — naming defects like "outline breaks on the rider's shoulder at three-quarter view," "landing compression resolves too fast to read as weight," "distant ridges blend instead of banding." They report defects. They do not approve work to be agreeable. /loop every subsystem against its critic until the critic runs out of specific defects to name. Working is the floor, not the goal. Milestones, each one playable: (1) eroded terrain + camera, (2) bike physics and feel on raw terrain, (3) full NPR pipeline applied to everything, (4) track, checkpoints, race flow, (5) rider rig and animation, (6) tricks, speed FX, and impact language, (7) AI riders, (8) HUD, audio, replay, (9) performance and final polish pass. Give me something runnable at every one. Report your quality bar honestly. If the rider rig is at 60% or the erosion pass is producing mush, tell me and tell me why. I would much rather hear it from you than find it myself. Deliverable A repo with a README, clean architecture, readable and commented shader code, and a working npm install && npm run dev. When I run it, I want the first ten seconds of the descent to look like a frame from a film, and I want to hit restart the moment I cross the finish line. Ultracode.
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Alrighty, so I let Opus 5 complete another round of improvements on the kart racing game. Partial renders, mobile performance, controls/camera adjustments are much better now. Not sure what's more impressive, that AI can produce this.. or that this runs in the browser (thanks @threejs!). Mind blowing honestly. What should I do next? Try it out yourself here: racing.ryancampbell.com/ For those asking, I used @mattshumer_'s prompt described here: somethingbig.ai/gauntlet-loo…
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The digital signature scheme is HAWK, which is designed to be robust even against hypothetical quantum computers. HAWK has survived two years of expert review, but in 60 hours Mythos Preview found a previously-unknown attack that reduced the scheme’s key strength by half.
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The symmetric cipher is a reduced version of the Advanced Encryption Standard (AES)—which has received decades of scrutiny (more than almost any other encryption algorithm). In a week, Mythos Preview found a way to speed up an attack on this version of AES by 200-800×.
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