New video goes live 7am PT. I'm done with the subscription playbook. No more slop. Back to building live, one flat price, yours forever. https://youtu.be/pRPFRuxoWlE Come watch it when it goes up.

Lauren Tan from Cursor walked through how they actually run agents internally. Forgetful new-hire energy, then playbooks so they stop making the same mistake twice. This is the pstack / skills story: verification, feature maps, evals, smaller PRs, CI as the guardrail. Also Grok Bot at the end for product teams. Free 60-min recording from Colin Matthews’ AI Native Builder series. https://maven.com/p/e23d9c/how-cursor-turned-ai-agents-into-better-engineers

Cursor just bumped included usage for Grok models again. Lee Robinson posted it this morning. Grok 4.6 demand is up. They already doubled limits last month with more compute, and they just raised them again. Permanent, not a weekend promo. If you've been hitting the wall on Grok in Cursor, check your usage. Extra room on the plan you already have. https://x.com/leerob/status/2092276970226671789

This is my actual setup, not a universal recipe. Tweak the device list, providers, permissions, skills and MCPs for your own work. IMPORTANT TAILSCALE NOTE My topology assumes a Linux server connected to the same Tailnet as my other devices. I use Tailscale because I have more than three machines and want one private network for SSH and services. T3 Code does not require Tailscale. T3 Connect works without it and is enough for most people who only want to reach their T3 environment remotely. Do not add a Linux server or Tailscale just to copy me. THE ARCHITECTURE iPhone or another computer → T3 Connect, with no VPN required or → Tailscale, as an optional private device network → T3 Code on the host Mac → Codex, Claude or Grok provider CLI → project files, terminal, Git, preview, skills, MCP tools and local subagents WHAT I RUN • Apple M5 Max MacBook Pro with 128 GB RAM • T3 Code 0.0.33 • Codex, Claude and Grok enabled • Cursor Agent installed but disabled in T3 • OpenCode disabled • Codex: GPT-5.6 Sol, xhigh, priority • Claude project default: Fable 5 • Grok 4.6, xhigh, yolo off • Node 26, pnpm, Bun, Git, gh, Docker, uv and 1Password CLI T3 CONNECT AND TAILSCALE T3 Connect links the local T3 environment to a T3 account and uses a managed cloudflared tunnel with authenticated HTTPS/WSS. It keeps the repository, terminal and running process on the host. Tailscale joins devices to a private Tailnet. I use it for SSH and services across my Mac, iPhone, Linux server and other machines. Tailscale Serve is optional. Funnel is public and is not part of this setup. Current T3 install guide: https://github.com/pingdotgg/t3code/blob/main/docs/user/install.md T3 Connect internals: https://github.com/pingdotgg/t3code/blob/main/docs/internals/t3-connect.md Optional Tailnet HTTPS: npx t3 serve --tailscale-serve Tailscale for macOS:

I started using T3 Code for a very practical reason: the computer in front of me isn’t always the best computer for the work I need to do. My everyday company computer is a Lenovo Legion with an Intel i9-14900HX, 32 GB of RAM, and an RTX 4070 Laptop GPU. It’s a capable machine, but it still has limits. When I’m running an application, compiling projects, reviewing UI, keeping several coding sessions open, and working on multiple things at once, the Legion can quickly become the bottleneck. At the same time, I have legitimate access to other computers that are often sitting idle. At the company, there’s an iMac with only 12 GB of RAM. It’s useful when I need macOS, but it isn’t the machine I would choose for heavier parallel workloads. We also have a dedicated Windows GPU workstation with 64 GB of RAM and a Radeon RX 7600 XT with 16 GB of VRAM. That machine has considerably more headroom for large builds, multiple simultaneous tasks, local models, and GPU-intensive work—especially at night, when nobody else is using it. At home, I also have my personal Linux machine. It has its own role: persistent services, Linux-native tooling, background processes, and projects that make more sense in a Linux environment. Before T3, these felt like separate computers. Every machine had its own files, terminals, dependencies, running processes, and unfinished work. Moving between them meant rebuilding context, copying things around, or trying to make one computer handle everything. T3 Code—and especially T3 Connect—changed that for me. Now I can sit at the Legion and connect to whichever environment makes the most sense for the task. The repository, terminal, dependencies, Git state, and running processes remain on the machine actually doing the work. I don’t need to move the entire project just because I moved to a different desk or opened a different laptop. This means I can review an application’s UI from the Legion while the application itself runs on the 64 GB GPU workstation. I can leave a build or a long-running task working there while I continue something else on my Linux machine. If I need macOS, I can move to the iMac environment without disrupting everything else.