Sharpbyte @sharpbyte_

Monolithic LLMs are dinosaurs waiting for the meteor. Trying to cram every human skill into a single 2-trillion-parameter black box is the most expensive dead end in computer science. The future of machine intelligence isn't a bigger chatbot. It is an autonomous micro-swarm: puluhan specialized 1B–3B liquid nodes synchronizing in sub-milliseconds, routing tasks dynamically, and mutating their own execution graphs on the fly. One giant brain hallucinates. A deterministic swarm converges. I just published a full architectural breakdown on how we orchestrate local micro-swarms that crush frontier monoliths at 1/40th of the compute cost. Read the full blueprint & grab the routing protocol below. x.com/sharpbyte_/sta…

and the mic is always-on btw. plus: automatic content recognition, geo positioning, network mapping, a targeted ads service, 4 different drm stacks, user profile building and a pile of other juicy telemetry. so it's you, God, a $3000 tv, and samsung + 400 partners.

bought a fairly new samsung tv. 2025 model. then started noticing ads that were a little too on the nose. tried pulling the firmware apart first. aes encrypted, no public keys. would've needed uart/jtag hardware magic. so: zero days it is. root shell on current samsung tvs. what i found inside is a privacy horror show. write-up below.

CLAUDE CODE FOUND A HACKER'S DEVICE ON MY HOME WIFI i own 9 things that connect: my phone, laptop, the tv, two smart plugs. asked claude code to show me everything the router sees. it counted 11. turned out one extra was a hallway smart plug i stopped thinking about years ago. whatever. the second showed nothing. no hostname, and its mac didn't resolve to any known vendor. that's exactly what a laptop looks like when it masks its real address. and per the logs it had been hopping on every evening. for months. i rotated the wifi password and watched the client list go quiet. my nine came back. the other two didn't. whoever that was could see every camera and smart plug i own and push traffic through my ip. check yours, takes 2 minutes: 1. get on your home wifi and tell claude code: "read-only. list every device on my lan via the arp table and a light ping sweep. per device: ip, mac, vendor lookup, best guess of device type" 2. first write your own list. phones, laptops, tv, console, bulbs, the printer you forgot. his list longer? keep going 3. for every row you don't recognize ask: is the mac randomized? who's the vendor? phone, camera or iot? a randomized address almost always means a phone or laptop 4. then the router: fresh wifi password, wps off. reconnect only yours. iot stuff goes to the guest network so a compromised bulb can't see your laptop 5. something you never installed, or it comes back after the reset? don't unplug it yet. screenshot the client list with timestamps first want it in one shot? paste into claude code: "role: home network auditor. my lan, read-only. task: list every device: ip, mac, vendor, randomized mac yes/no, type guess. flag cameras, mics, unknown phones. end with a plan: new wifi password, wps off, guest net for iot" save it. you won't remember at 1am in a strange room.

i don't understand why motion designers aren't running this setup. the stack: one folder + Claude Code. inside — a render engine, an animation library and Blender. that's the whole studio. you write spec.md, the agent writes render.py, ffmpeg glues frames to audio. no timeline. no keyframes. the "edit" is a git diff. the dossier in this video — panels, the brain, every label — came out of that pipeline end-to-end: HTML in, rendered video out. the part nobody prices in: iteration is free. "make the camera slower" isn't a request to a freelancer, it's a parameter. run 200 variants overnight for the cost of tokens. the pipeline isn't "AI makes video". it's "agents make the thing that makes the video". volume of experiments is the new skill ceiling.

the only thing worse than an agent that can't decide is an agent that decides badly at scale. 12 use cases. one decision layer. email triage. youtube comments. leads, meetings, trading, agents — every inbound gets scored, routed and either handled or parked for a human. the dashboard from this run: 2,715 decisions in one session ~256 ms median latency ≈ $0.42 per 10K decisions confidence gate at 0.85 below the gate it doesn't guess — it asks. and my favorite line in the whole panel: "never auto-post to X". the machine decides, a human ships. LLM writes - Jev decides - code acts.

"Build a single-file HTML ocean flyover in raw WebGL2, no libraries: - 220x220 vertex grid, gerstner-style sum-of-sines heightfield displaced per frame - fragment shader: fresnel mixing deep/shallow water into reflected sky, sun specular (pow 240 + pow 24), fbm glitter, foam on wave crests - fullscreen sky pass: gradient horizon-to-top + fbm noise clouds + sun disc - camera: slow forward flight, gentle altitude sway, WASD/Space-Q fly controls, HUD showing FPS/ALT - under 10KB total paste into Claude Sonnet or Gemini 3 (AI Studio) - both handle raw GLSL. if it outputs three.js, re-send with 'zero imports, WebGL2 only'"

this ocean is a single HTML file. no libraries. no engine. just raw WebGL and math. one prompt to Claude Sonnet, saved as .html, opened in any browser. the whole scene: ~200 lines, under 8 KB. what's actually running: - gerstner-style wave sum displacing 100k vertices per frame - fragment shader computing fresnel, sun specular and foam on crests - fbm noise clouds baked into the sky pass - a 220x220 grid marching at 60fps on integrated graphics no three.js. no unity. no assets. the entire world is 6 sine functions and one fbm noise stack. the catch everyone misses: this doesn't come from "write me an ocean". it comes from one structured prompt that names the exact primitives - gerstner sum, fresnel reflect, fbm sky. vague prompt gets you a blue div. precise vocabulary gets you a renderer. works in Claude, Gemini 3, GPT-5 - any model that won't sneak three.js into the answer. the exact prompt is in the replies. grab it and one-shot your own.

"Split my Claude Code into a trio: sonnet = builder, medium effort haiku = watcher, fingerprints error signatures on the AST stream opus = advisor, summon-only hard rule: same signature twice = halt, summon opus, reset plan never let the builder touch that file a third time"

most agent setups fail the same way: one model doing every job until it argues with itself in circles. here's a cheaper topology. three models, three roles, one hard rule: builder: sonnet 5.5 on medium effort watcher: haiku 5.5 streaming the AST every 16ms advisor: opus 5.5, asleep until summoned claude --model sonnet --gatekeeper haiku --advisor opus the watcher doesn't fix anything. it just fingerprints error signatures. identical signature twice in a row = execution halts on the spot. no third blind patch. that third attempt is where $50 of context quietly dies. opus wakes for three questions only: is the plan broken at the root? is this the same failure wearing a new stack trace? what did the worker miss before we call it done? underneath, JEV micro-checks clear 1,200+ mechanical verifications per run. sub-16ms each. the expensive models never touch lint noise. the economics are the point: haiku watching costs almost nothing. sonnet retrying a dead end costs everything. build on medium. watch on low. escalate on strike two. setup prompt in the replies.

Not sure which to install first? Send this thread to Opus 5.5 and add: “Look through my project and tell me which of these 3 repos to install first, and which command to start with. Explain why. Don’t install anything until I say yes.”

3. Design, testing, security → msitarzewski/agency-agents (160K stars) Agents for a dozen departments live in separate folders. Copy the one you need: git clone github.com/msitarzewski/a… cp agency-agents/design/*.md ~/.claude/agents/

3 GitHub repos turn Opus 5.5 into an entire company. Nearly 300K stars combined: → addyosmani/agent-skills → anthropics/knowledge-work-plugins → msitarzewski/agency-agents What each does, and what to run first 🧵