
Content creator | AI researcher & builder | AI insights from 2030 | @beyond_xai
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Joined May 2026
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Holy sh*t, I just turned my TV into Jarvis with Opus 5.5 + ChatGPT voice mode
I reverse-engineered my Samsung TV with Opus 5.5...
1 sentence out loud = 6 Claude Code agents opening on my living room TV.
here's the full guide step by step:
step 1 → put your Samsung Smart TV and your laptop on the same Wi-Fi
step 2 → paste the prompt below into Claude Code on Opus 5.5 with a photo of Settings → Support → About This TV
step 3 → Opus maps how the TV takes orders and finds the loophole:
Samsung's own remote-control API on your home network can open any web page in the TV browser
step 4 → it spins up 6 Claude Code agents in a tmux grid on the laptop and streams them as a private page on your Wi-Fi only
step 5 → it builds a tiny "Jarvis" connector with one single tool: open the agent wall.
ChatGPT voice mode is the ears, the connector is the hands
step 6 → press Allow on the TV once, the last time you touch the remote
step 7 → say "Open Claude Code CLI on my TV" and watch the windows pop in one by one
the result: the laptop does the work, the TV is the control room...
p.s: works on most Samsung Smart TVs with Tizen.
mine in the video runs Smart Hub. The remote now lives in a drawer
Find full prompt below
Then read the article below on how to reverse-engineer anything
Holy sh*t, I just turned my TV into Jarvis with Opus 5.5 + ChatGPT voice mode
I reverse-engineered my Samsung TV with Opus 5.5...
1 sentence out loud = 6 Claude Code agents opening on my living room TV.
here's the full guide step by step:
step 1 → put your Samsung Smart TV and your laptop on the same Wi-Fi
step 2 → paste the prompt below into Claude Code on Opus 5.5 with a photo of Settings → Support → About This TV
step 3 → Opus maps how the TV takes orders and finds the loophole:
Samsung's own remote-control API on your home network can open any web page in the TV browser
step 4 → it spins up 6 Claude Code agents in a tmux grid on the laptop and streams them as a private page on your Wi-Fi only
step 5 → it builds a tiny "Jarvis" connector with one single tool: open the agent wall.
ChatGPT voice mode is the ears, the connector is the hands
step 6 → press Allow on the TV once, the last time you touch the remote
step 7 → say "Open Claude Code CLI on my TV" and watch the windows pop in one by one
the result: the laptop does the work, the TV is the control room...
p.s: works on most Samsung Smart TVs with Tizen.
mine in the video runs Smart Hub. The remote now lives in a drawer
Find full prompt below
Then read the article below on how to reverse-engineer anything
full prompt:
"This is my own Samsung Smart TV, my own home Wi-Fi and my own laptop.
I want a wall of Claude Code agents running on this laptop and shown live on my TV, opened by voice: I say "Open Claude Code CLI on my TV" to ChatGPT voice mode and the agents appear on the screen.
I'll press Allow on the TV myself and approve every connection.
I authorize you to set up the laptop side, talk to the TV through Samsung's local remote-control API, install what's needed and make the changes below. Every change must be reversible.
I've attached a photo of the TV's Settings → Support → About This TV screen.
Done means: 6 Claude Code agents run in a tmux grid on this laptop, the grid streams as a password-protected web page on my home network only, and one voice command makes the TV open it full screen while I watch each step.
When a step doesn't need me, keep going.
→ First, map how my TV can be controlled and explain it in 5 lines: what runs on Tizen, what the local remote-control API (WebSocket, port 8002) allows, why it can open a URL in the TV browser, and why that's the way in. If the photo shows a TV without Tizen or without network remote control, tell me plainly, and stop. Never root, flash or sideload anything onto the TV.
→ Identify the model from the photo. Install tmux, ttyd and the samsungtvws Python library from official sources (Homebrew, PyPI or official GitHub releases) if missing. Find the TV's IP on my network. Tell me exactly where to look if "Device Connection Manager" or "Access Notification" blocks the connection. On macOS, "No route to host" usually means the terminal needs Local Network access: allow it and retry.
→ Before changing anything, save the TV's current input and app, every setting you'll touch, and the undo commands.
→ Build the agent grid: a tmux session called "tvwall" with 6 panes in a 3×2 layout, each running claude in my repo. Ask me for the repo path and the 6 tasks. If I skip, use refactor, tests, docs, build, review, deploy.
→ Write tvwall.sh with start, stop and status. Start runs ttyd in writable mode on port 7681, bound to my Wi-Fi interface only, with a random password saved to a local file (never print it in chat), a dark theme and a font size readable from the couch on a 4K screen.
→ Open it on the TV: use samsungtvws to open the TV browser at http://:7681 and go full screen. The first time, wait for me to press Allow on the TV. Save the pairing token to a local file with owner-only permissions.
→ Build the voice trigger: a tiny MCP server with exactly ONE tool, open_claude_wall, that runs tvwall.sh start and opens the page on the TV. No shell access, no arguments, nothing else. Connect it to ChatGPT as a custom connector in developer mode through a Cloudflare Tunnel protected by a secret token. If my ChatGPT plan or voice mode can't call custom connectors, tell me plainly and fall back to a local wake phrase listener on the laptop instead.
→ Check the TV state before every action (current app, connection status) and show me what you're about to send.
→ Never touch the TV's firmware, accounts, Samsung Pay, parental controls, network settings, SmartThings automations or any other device on my network.
→ Add a live monitor that prints each command with a timestamp, plus a one-line health check: agents up, ttyd up, TV paired, connector reachable.
→ End with a cheat sheet (start, stop, re-pair the TV, revoke the connector) and the undo commands.
Never expose the terminal itself to the internet, never type my passwords or sign in for me, never install apps from pirate sites."
Codez retweeted
Kling is back.
Kling 4.0 is now live on Higgsfield.
> Omni Reference: characters, objects and audio in one generation
> 30-second scenes in a single pass
> Start, middle and end frames to direct every beat
> Native 4K coming soon
Available now on Higgsfield.
this is impressive…
I can’t believe this small open-source model by @thewebAI is so good.
A 2.24 GB model just ran 2.4x faster than Qwen 9B.
No GPU. Just an Intel Xeon with 15 GiB RAM.
→ TwIL-LM3-Pro: 2.24 GB, 10.47 tok/s
→ Qwen3.5-9B: 5.67 GB, 4.36 tok/s
Same CPU, same memory limit. TwIL is faster just because its weights are smaller.
So I made them race in Snake
Same board. Same apples. 60 seconds. Real speeds.
TwIL: 450 pts
Qwen 9B: 210 pts
The model you can fit beats the model you can’t.
We ran TwIL on a CPU with 15 GiB of RAM. No GPU. It generated tokens 98x faster than Qwen3.8-27B on the same hardware.
The test:
- Intel Xeon CPU, 4 threads
- 15 GiB RAM
- No GPU
Results:
- TwIL-LM3-Pro (2.24 GB weights): 10.47 tokens per second
- Qwen3.5-9B (5.67 GB weights): 4.36 tokens per second
- Qwen3.8-27B (16.45 GB weights): 0.107 tokens per second
TwIL and Qwen 9B both run at the RAM's memory limit of about 24 GB/s. Qwen 9B is 2.4x slower only because its weights are 2.5x larger.
Qwen 27B's 16.45 GB of weights don't fit in the 15 GiB of RAM. Parts have to be re-read from disk for every token. Size alone would make it 7.3x slower. The disk reads add another 13x. Total: 98x slower than TwIL.
With enough RAM, the gap would shrink to about 7x. But most people don't have unlimited RAM, and most people don't have a top-tier GPU. The model you can actually fit matters more than the one you can't.
Download TwIL-LM3-Pro on @huggingface: huggingface.co/webAI-Officia…
Holy sh*t, I turned my Meta Ray-Ban glasses into a pro golf coach with Opus 5.5
Claude Opus 5.5 just reverse-engineered my Meta glasses...
1 prompt + 20 min = Claude Code agents built an AR putting coach that floats over the green.
here’s how Opus did it, step by step:
step 1 → it sniffed the Bluetooth traffic and decompiled the Meta AI app.
the loophole: whatever the phone renders, the lens shows
step 2 → it split the work across 4 agents in tmux: camera stream, vision, putt physics, UI
step 3 → SLAM + depth AI turn camera frames into a 3D mesh of the green, scaled by the ball (42.67 mm) and the cup (108 mm)
step 4 → it reads the slope of every 5 cm of grass and draws contour lines over the break
step 5 → it simulates hundreds of putts and keeps the one that finishes 17 inches past the cup.
blue = the ball’s path, red = where to aim
step 6 → hand tracking turns your fingertip into a mouse. tap a bubble, switch the view
the result: the glasses read the break, you just stroke the ball...
p.s: mine in the video is a practice green. Practice only, slope readers are banned in competition
Find full prompt below
Then read the article below on how to reverse-engineer anything
this is impressive…
I can’t believe this small open-source model by @thewebAI is so good.
A 2.24 GB model just ran 2.4x faster than Qwen 9B.
No GPU. Just an Intel Xeon with 15 GiB RAM.
→ TwIL-LM3-Pro: 2.24 GB, 10.47 tok/s
→ Qwen3.5-9B: 5.67 GB, 4.36 tok/s
Same CPU, same memory limit. TwIL is faster just because its weights are smaller.
So I made them race in Snake
Same board. Same apples. 60 seconds. Real speeds.
TwIL: 450 pts
Qwen 9B: 210 pts
The model you can fit beats the model you can’t.
We ran TwIL on a CPU with 15 GiB of RAM. No GPU. It generated tokens 98x faster than Qwen3.8-27B on the same hardware.
The test:
- Intel Xeon CPU, 4 threads
- 15 GiB RAM
- No GPU
Results:
- TwIL-LM3-Pro (2.24 GB weights): 10.47 tokens per second
- Qwen3.5-9B (5.67 GB weights): 4.36 tokens per second
- Qwen3.8-27B (16.45 GB weights): 0.107 tokens per second
TwIL and Qwen 9B both run at the RAM's memory limit of about 24 GB/s. Qwen 9B is 2.4x slower only because its weights are 2.5x larger.
Qwen 27B's 16.45 GB of weights don't fit in the 15 GiB of RAM. Parts have to be re-read from disk for every token. Size alone would make it 7.3x slower. The disk reads add another 13x. Total: 98x slower than TwIL.
With enough RAM, the gap would shrink to about 7x. But most people don't have unlimited RAM, and most people don't have a top-tier GPU. The model you can actually fit matters more than the one you can't.
Download TwIL-LM3-Pro on @huggingface: huggingface.co/webAI-Officia…
Holy sh*t, I turned my Meta Ray-Ban glasses into a pro golf coach with Opus 5.5
Claude Opus 5.5 just reverse-engineered my Meta glasses...
1 prompt + 20 min = Claude Code agents built an AR putting coach that floats over the green.
here’s how Opus did it, step by step:
step 1 → it sniffed the Bluetooth traffic and decompiled the Meta AI app.
the loophole: whatever the phone renders, the lens shows
step 2 → it split the work across 4 agents in tmux: camera stream, vision, putt physics, UI
step 3 → SLAM + depth AI turn camera frames into a 3D mesh of the green, scaled by the ball (42.67 mm) and the cup (108 mm)
step 4 → it reads the slope of every 5 cm of grass and draws contour lines over the break
step 5 → it simulates hundreds of putts and keeps the one that finishes 17 inches past the cup.
blue = the ball’s path, red = where to aim
step 6 → hand tracking turns your fingertip into a mouse. tap a bubble, switch the view
the result: the glasses read the break, you just stroke the ball...
p.s: mine in the video is a practice green. Practice only, slope readers are banned in competition
Find full prompt below
Then read the article below on how to reverse-engineer anything
Full Prompt:
You're a senior AR + computer vision engineer.
I own Meta Ray-Ban 2 glasses (photo attached) and an Android phone. Turn the glasses into a real-time AR putting coach.
STEP 1: RECON
- Walk me through enabling Bluetooth HCI snoop log, then parse btsnoop_hci.log with tshark
- Decompile the Meta AI app with jadx and map how the camera stream and display overlay are called
- Cross-check against Meta's Wearables Device Access Toolkit
- Output: a spec of how to pull camera frames to the phone and push rendered pixels back to the lens
STEP 2: AGENTS
Spin up 4 Claude Code agents in tmux with one shared SPEC.md:
- agent 1: camera stream + overlay link
- agent 2: vision
- agent 3: putt physics
- agent 4: UI
Each agent tests against recorded footage of a green before touching the live glasses.
STEP 3: SCAN THE GREEN
- Monocular SLAM for head pose + Depth Anything V2 for dense depth
- Metric scale from known objects: ball = 42.67 mm, cup = 108 mm
- Point cloud → Delaunay mesh → heightmap with 5 cm cells
STEP 4: READ THE BREAK
- Slope per cell from the heightmap gradient
- Contour line every 1 cm of elevation (marching squares)
- YOLO detects the ball, flagstick + dark ellipse = the hole
STEP 5: SIMULATE THE PUTT
- Rolling ball physics: 5/7 g along the slope, friction from green speed (default Stimp 10, editable)
- RK4 integration, 1 ms steps
- Search launch angle + speed so the ball finishes 17 inches past the cup
- Render: ideal line (blue), aim line (red), aim point, corridor of putts that still drop, yellow setup lines at my feet square to the aim line
STEP 6: HANDS-FREE UI
- MediaPipe Hands on the same camera feed, index fingertip on a bubble = tap
- Floating bubble menu: Ideal Line, Aiming Line, Contour Lines, Setup Lines, Corridor, Putt Info, Animation
- Actions: New Ball, New Target, New Putt
RULES
- Re-project every overlay into the current camera pose each frame, under 100 ms end to end
- Ask me before anything that needs a physical action (pairing, approving the connection)
- Ship a working build I can test on a practice green today
Holy sh*t, I’m running Claude Code on CarPlay right in BMW dealership
Claude Opus 5.5 just reverse-engineered my CarPlay...
1 prompt + 20 min = 4 Claude Code agents shipping code live on my dash. Apple never approved a thing
here’s the full guide step by step:
step 1 → plug an Android CarPlay AI box into your car’s USB (Ottocast, Carlinkit Tbox)
step 2 → paste the prompt below into Claude Code on Opus 5.5 with a photo of your head unit
step 3 → Opus maps how CarPlay draws pixels and finds the loophole: whatever runs on the box, the car displays
step 4 → it spins up 4 Claude Code agents in tmux and streams them to your dash
step 5 → approve the connection on the screen once, the last time you lift a finger
step 6 → tap a pane to jump between agents, approve diffs, ship from the driver’s seat
the result: the laptop does the work, the dash is the control room...
p.s: works on almost any car with wireless CarPlay. Mine in the video is a BMW iDrive. Parked only
Find full prompt below
Then read the article below on how to reverse-engineer anything
Holy sh*t… Wabi just made the App Store feel old.
→ 2008: 500 apps.
→ 2009: "there's an app for that."
→ Today: millions of apps, and your home screen looks exactly like everyone else's.
Wabi flips it. You don't download an app, you ask for one:
→ "help me train for my half marathon"
→ it builds you a marathon coach: your race, your date, your 16-week plan
→ right inside the chat you already use with friends & family
There used to be an app for that.
Now there's an app for you.
🤝 Paid partnership
Wabi 2.0 is live!
personal agents are one person, one chat. but the parts of life that matter run on more than one person
Wabi is an agent you use together. you talk to it, it does stuff, builds the apps you need, and anyone can join the thread - your partner, your best friend, the preschool moms groupchat
school changes pickup time → Wabi updates the family calendar, everyone sees it.
a show you’d both love → Wabi finds a night that works, gets the tickets.
the trip everyone keeps talking about → Wabi picks the dates, builds the itinerary, books it
go start a thread with your people 👇
This is insane...
A solo founder was spending $1.2M a month on the Anthropic API.
He just revealed how he’s cutting it to ~$50K.
→ Teamed up with Sapiom to rethink the whole setup
→ Rented GPUs instead of paying per token
→ Moved workloads to open-source models
This change helped Polsia hit $20M run rate.
This is the best video I’ve watched on running a one-person AI startup from $0 to $20M run rate.
🤝 Paid partnership
Polsia is about to hit $25M run rate.
Next stop: $100M ARR.
And things keep accelerating:
$0 → $1M in 12 weeks
$1M → $10M in 10 weeks
$10M → $20M in 6 weeks
I just published one of my favorite and most successful aisloP episodes yet: “The Run Rate.”
I tell the whole story, from idea to $20M, month by month.
The episode ends in Tokyo, where I went a few weeks ago.
Probably the best place on Earth to take a deep breath, get inspired, and rethink what’s possible.
I came back with an even bolder vision for Polsia.
The road from $25M to $100M is going to look very different.
Polsia v2 is coming soon.
Holy sh*t, I’m running Claude Code on CarPlay right in BMW dealership
Claude Opus 5.5 just reverse-engineered my CarPlay...
1 prompt + 20 min = 4 Claude Code agents shipping code live on my dash. Apple never approved a thing
here’s the full guide step by step:
step 1 → plug an Android CarPlay AI box into your car’s USB (Ottocast, Carlinkit Tbox)
step 2 → paste the prompt below into Claude Code on Opus 5.5 with a photo of your head unit
step 3 → Opus maps how CarPlay draws pixels and finds the loophole: whatever runs on the box, the car displays
step 4 → it spins up 4 Claude Code agents in tmux and streams them to your dash
step 5 → approve the connection on the screen once, the last time you lift a finger
step 6 → tap a pane to jump between agents, approve diffs, ship from the driver’s seat
the result: the laptop does the work, the dash is the control room...
p.s: works on almost any car with wireless CarPlay. Mine in the video is a BMW iDrive. Parked only
Find full prompt below
Then read the article below on how to reverse-engineer anything
full prompt:
"This is my own car and my own Android CarPlay AI box (Ottocast / Carlinkit Tbox or similar), plugged into the car's USB port. The laptop is mine too.
I want a swarm of Claude Code agents running on this laptop and shown live on my car's center screen, so I can watch them and tap between them from the dashboard.
I'll turn on developer mode on the box myself and approve every connection on the screen.
I authorize you to set up the laptop side, connect to the box with ADB (Android's official developer tool), install what's needed and make the changes below. Every change must be reversible.
I've attached a photo of my head unit and of the box's Settings → About screen.
Done means: 4 Claude Code agents run in a tmux grid on this laptop, the grid streams as a password-protected web page on the hotspot network only, and one command opens it full screen on my car's dash while I watch each step.
When a step doesn't need me, keep going.
→ First, map how CarPlay puts pixels on my screen and explain it in 5 lines: what the iPhone renders, what the head unit only displays, why Apple only allows approved app categories, and why the AI box is the way in. If the photo shows no Android box, tell me plainly a terminal can't go on the dash that way, and stop. Never jailbreak the iPhone or get around Apple's entitlements.
→ Identify the box from the photo. Install adb, tmux and ttyd from official sources (Homebrew or official GitHub releases) if missing. Tell me exactly where to tap to turn on Developer options and Wireless debugging and find the box's IP. If adb connect is refused, use Wireless debugging pairing. On macOS, "No route to host" usually means the terminal needs Local Network access: allow it and retry.
→ Put the laptop and the box on my phone's hotspot. Find the laptop's IP on that network.
→ Before changing anything on the box, save its package list, every setting you'll touch and the undo commands.
→ Build the agent grid: a tmux session called "carplay" with 4 panes, each running claude in my repo. Ask me for the repo path and the 4 tasks. If I skip, use refactor, tests, build, deploy.
→ Write carplay.sh with start, stop and status. Start runs ttyd in writable mode on port 7681, bound to the hotspot interface only, with a random password saved to a local file (never print it in chat), a dark theme and a font size readable on a wide 1920x720 display.
→ Open it on the dash: launch the box's browser to http://:7681 with an adb VIEW intent and go full screen. If there's no usable browser, install one only from its official GitHub releases, for example TV Bro.
→ Use real taps and key presses so I see every step, and check the screen (screenshot or uiautomator dump) before pressing OK.
→ Never touch the CarPlay or Android Auto service, navigation, radio or tuner, the reverse camera, CAN-bus or any driving or safety app, the launcher, Play Services, or the keyboard and input services.
→ Add a live monitor that prints each command with a timestamp, plus a one-line health check: agents up, ttyd up, box connected.
→ End with a cheat sheet (start, stop, reconnect, switch panes from the dash) and the undo commands.
Do everything parked. Never expose the terminal to the internet, never type my passwords or sign in for me, never root or flash anything, never modify vehicle firmware, no pirate sites."
Claude Opus 5.5 just reverse-engineered my CarPlay...
1 voice command + 5 min = total control: CarPlay that obeys me, ads skipped, any app on the dash and that’s just the beginning
here’s the full guide step by step:
step 1 → plug your iPhone into the car and put your laptop on the same hotspot
step 2 → paste the prompt below into Claude Code with a photo of your head unit
step 3 → unlock the hidden engineering menu - Claude tells you the exact button combo on the wheel
step 4 → hit “allow” on the screen once - last time you lift a finger
step 5 → say “Hey Claude, open the Roadster launch on CarPlay” - it opens YouTube, types the search, hits play
step 6 → add any app straight from GitHub - no App Store, no CarPlay whitelist
the result: you talk, the dash moves. anything you can say, your car can do...
p.s: works on almost any CarPlay head unit. Mine in the video is a BMW iDrive
Try it now, you’re welcome. Then read the article below on how to reverse-engineer anything:
Claude Opus 5.5 just reverse-engineered my CarPlay...
1 voice command + 5 min = total control: CarPlay that obeys me, ads skipped, any app on the dash and that’s just the beginning
here’s the full guide step by step:
step 1 → plug your iPhone into the car and put your laptop on the same hotspot
step 2 → paste the prompt below into Claude Code with a photo of your head unit
step 3 → unlock the hidden engineering menu - Claude tells you the exact button combo on the wheel
step 4 → hit “allow” on the screen once - last time you lift a finger
step 5 → say “Hey Claude, open the Roadster launch on CarPlay” - it opens YouTube, types the search, hits play
step 6 → add any app straight from GitHub - no App Store, no CarPlay whitelist
the result: you talk, the dash moves. anything you can say, your car can do...
p.s: works on almost any CarPlay head unit. Mine in the video is a BMW iDrive
Try it now, you’re welcome. Then read the article below on how to reverse-engineer anything:
full prompt:
"This is my own car head unit (Android-based / CarPlay AI-box) on my own device.
It came full of preinstalled bloat, recommendation rows and apps I can't remove from the menu, and I want it clean, fast and controlled from this computer.
I'll turn on developer mode myself and approve the connection on the screen.
I authorize you to connect to it with ADB, Android's official developer tool, read its settings and make the changes below. Every change must be reversible.
I've attached a photo of my head unit (or its Settings → About screen).
Done means: you're connected, the unit is cleaned of bloat and runs faster, an open-source app of my choice is installed, and one command opens YouTube on the dash and plays a video I name while I watch each step on the screen.
When a step doesn't need me, keep going.
- Identify the model from the photo. If it's a locked OEM system (like BMW iDrive, not an Android-based unit), tell me plainly that ADB control isn't possible there and what its official local control allows, and do only that.
- Install adb from official sources if it's missing. Tell me exactly where to tap to turn on Developer options and USB or Wireless debugging, and to find the unit's IP. If adb connect is refused, use Wireless debugging pairing. On macOS, "No route to host" usually means the terminal needs Local Network access: allow it and retry.
- Before changing anything, save the package list, every setting you'll touch and the undo commands.
- Propose the cleanup and wait for my OK: disable (never uninstall) ad, recommendation, feedback and demo apps; never touch the CarPlay or Android Auto service, navigation, radio or tuner, the reverse camera, CAN-bus or any driving or safety app, the launcher, Play Services, the keyboard or input services, or anything you can't identify; animations to 0.5;
Private DNS dns.adguard-dns.com
- Install apps only from their official GitHub releases, for example the TV Bro browser.
- Use real taps and key presses so I see every step, and check the screen (screenshot or uiautomator dump) before pressing OK. Screenshots of a playing video are blank because of DRM. Handle the "Who's watching?" screen.
- Add a live monitor that prints each command with a timestamp and shows logcat only while a command runs.
- End with a cheat sheet and the undo commands.
Do everything parked with the engine off. Never type passwords or sign in for me, never root or flash anything, never modify vehicle firmware, no pirate sites."
Anthropic engineers just released best 1-hour course on running 1,000 Claude agents with Opus 5.5:
“Opus 5.5 is the best model for building agentic systems and reverse engineering with it.”
• 00:39 - Flows: Claude orchestrates its own multi-agent topology
• 10:36 - building an agent with Opus 5.5 (live demo)
• 21:14 - Claude agent system: Fable, Opus, Haiku
• 39:03 - 1,000+ agent orchestration (live demo)
• 1:11:17 - agent safety: brain, sandboxes, auto mode
most $500 agentic courses don't give you even 20% of what's inside this workshop.
watch it today, then explore how to reverse engineer anything with Opus 5.5 in the article below.
Nooo way, i asked my GrokBot:
"GrokBot, make a GTA game with the new Roadster, make no mistakes."
result:
roadster-city.vercel.app
This is insane....







