Agent-desktop is truly a gamechanger
What shipped at Vercel Labs in October
95 releases
730 issues closed
3,500+ PRs merged
New: agent-desktop
→ Computer use for any coding agent
→ macOS, Windows + Linux
New: tsc-ts
→ The TypeScript 7 compiler, written in TypeScript
→ Compiled to native with scriptc
agent-browser
→ Safer MCP
→ 42 browser tools for eve agents
skills
→ Sync skills across a monorepo
→ Sync reads optional + peer deps
→ Faster updates
json-render
→ Streaming fixes
→ Form + PDF fixes
→ json-render-shadcn skill
portless
→ No more sudo
→ portless mcp
deepsec
→ Kimi K3.1 Pro + DeepSeek V4.1 Flash benchmarks
native
→ native test for TS apps
→ Reusable markup components
→ Virtual lists
scriptc
→ Fully native, no JS engine
→ WebAssembly compiles to native
→ Profile-guided optimization
just-bash
→ mktemp + yes
→ Closer to real bash + jq
fx
→ Launches 23× faster
→ 41% fewer tokens
→ Agents that survive redeploys
wterm
→ Faster color rendering
→ Emoji + flags in one cell
→ Vim matches your page theme
vgpu
→ Build-time WGSL shaders
→ Turbopack support
→ Depth + MSAA on canvas
lat․md
→ lat ui to browse your knowledge graph
→ Graph view + static export
emulate
→ npx emulate mcp
→ AWS Cognito
→ Slack interactivity
ai-cli
→ ai mcp
→ ai decide can judge images
mcp-handler
→ MCP Events
run
→ CPU time limits for agent code
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Ux should now be default liquid - except all the backend “core” system like DB, auth, model, gateway, payments
I'm now building an "improvements" feature into all of my personal vibecoded applications: a freeform text input that's hooked up to an agent that yolo implements whatever is submitted.
It's an interesting experience -- the activation energy barrier to sanding any rough edge or ature becomes extremely low. Someone else who uses one of the applications I created has already implemented 150 improvements over the course of a few days. This pattern feels like a new kind of tool -- liquid software? -- and every application that doesn't have this feature now has a slightly rigid and anachronistic flavor. Why can't I just tell it how I want it to be different?
Now, it's not obvious to me how this pattern can or should scale. Does it become unmaintainable after a while? (Maybe model intelligence improvement outstrips my feature appetite such that it's fine?) How does collaborative software work in this model? Can software designed this way be secure and reliable?
Whatever the larger questions about broader deployment, it definitely works great in a personal context. It reminds me a little of the visions of Lisp/Lisp machines, Smalltalk, and HyperCard -- systems that the user can take control of and modify. Those visions never quite worked, though: the vast majority of software today is not end-user modifiable in any useful way. So, while this "liquid" affordance is a very small touch, the way it changes one's relation to the software feels a bit transgressive and empowering in a Lickliderian and Engelbartian way.
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There is no enterprise level, multi-player, always on AI (yet)
It’s almost incomprehensible how wide the distance is between someone who’s working at the frontier with AI and basically everyone else right now.
The crazy thing is these lines are not converging, but only growing farther apart. If the curve of AI progress had leveled off, it would certainly have given most people and companies time to catch up or implement their workflows in a standardized way. The technology would have neutralized competitive advantage because everyone would be using it the same way.
But what’s happened is the opposite. The curve of AI progress is basically going vertical right now, which means if you had codified your processes 3-6 months ago you’re likely already behind again. Now imagine most companies that kicked into gear a year ago and thought that they were done. Even further behind now.
I’ve never seen a technology in my life and career that improves at this rate, which consequently means you need to upgrade your expectations at a similar rate. Our brains weren’t wired for this, and our organizational change management processes certainly weren’t either.
With any form of recursive self improvement, things just get wilder. It’s a time when you will need to be constantly reevaluating the things that didn’t work just a couple months ago to see if they now can be solved. AI native companies certainly have a strong advantage due to this right now, so now it comes down to can the bigger companies keep up. Wild times.
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Quick POC?
@RamaswmySridhar should fight. The two companies are complementary. Since you're not doing this AI stuff, I really think Snowflake should consider getting its AI tokens through Databricks. You can get both cheap OSS models as well as frontier (OAI/Ant/Gemini/Grok) models from our platform. It all goes through Unity Gateway which has Smart Routing, Budgets, and Access Control. You can even use Omnigent with any harness, including CoCo. Most of our customers used this to reduce token spend ~30% last few months while token count went up. Genie lets you then track, control, manage that spend, all your financials, marketing, etc. Quick POC?
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Leetcode dead?
Why are companies still asking coding interview
Why are companies still asking coding interview
The coding interview is dead, at least for my team at Anthropic. I've seen enough to know that it no longer provides signal. I removed it from loops this month.
I have a spicy, optimistic take - I think there's an opportunity for junior engineers: felixrieseberg.com/hunger-beats-t…
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Mustafa retweeted
The coding interview is dead, at least for my team at Anthropic. I've seen enough to know that it no longer provides signal. I removed it from loops this month.
I have a spicy, optimistic take - I think there's an opportunity for junior engineers: felixrieseberg.com/hunger-beats-t…
I have a spicy, optimistic take - I think there's an opportunity for junior engineers: felixrieseberg.com/hunger-beats-t…
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