whateverai

Introducing WhateverAI — the Execution Layer for AI Agents 🚀 AI can think, plan, and reason. But it still can’t act across real apps, real devices, or real workflows. We fix this. We give agents a cloud environment where they can see, click, type, navigate—and execute.

support ticket 📲🎟️ "the app crashes when i try to upload a photo on android 13, samsung s22" old world: support engineer spends 2 hours reproducing new world: agent spawns a cloud phone, matches the device, reproduces the bug, captures the stack, files the jira hours → minutes ⏲️

happy monday. let's win this week!

language support isn't a checkbox whateverai ships with chinese + english out of the box. not because we translated a string file. because the vision model reads both natively. means your agent works on wechat, xiaohongshu, taobao, meituan — the same way it works on instagram, amazon, doordash. most "mobile agents" die at the gfw. ours ships past it.

pov: you're 4 hours into debugging a #selenium script because they added a loading spinner there is a better way...

5 reasons dom-based automation is a dead end 1/ the web was the last environment where dom-scraping worked. mobile is not the web. 2/ reason one: no dom. native apps don't expose a tree. you're staring at pixels. 3/ reason two: dynamic layouts. one carrier update and your xpath is garbage. 4/ reason three: captchas, webviews, and hybrid UIs break parsers in new ways every week. 5/ reason four: accessibility trees lie. half the labels are wrong or missing. 6/ reason five: humans don't use the dom. if your agent is smarter than a human, it shouldn't need training wheels the human doesn't have.

dom-scraping agents: break when the button moves 4px vision-native agents: "there's a blue button that says continue. i'll tap it." the future looks at screens the way humans do.

one agent key. hundreds of devices. serial execution per key (AGENT_BUSY protects you from race conditions). parallel across keys. you can run an entire fleet from one codebase. each device gets its own vision context, its own plan, its own outcome. this is how you scale agents past "cool demo" into actual work.

why we collapsed 12 tools into 3 1/ every mcp server out there: 40 tools, 200 parameters, 10k token descriptions. agents drown in their own toolbelt. 2/ we shipped whateverai with 12 tools. tap. swipe. scroll. type. read_screen. blah blah. agents spent more tokens picking tools than solving problems. 3/ so we cut. 12 → 3. execute. execute_and_wait. task_result. that's it. the agent plans, the phone acts. 4/ the unlock: the tool isn't the action. the goal is the action. let the agent reason at the goal level, let the execution layer figure out the clicks. 5/ fewer tools = better planning = faster agents. ship less, do more.

last month: 12 fine-grained ui tools this month: 3 tools cloudphone_execute cloudphone_execute_and_wait cloudphone_task_result your agent doesn't need a swiss army knife. it needs a hammer that works.

. @AnthropicAI accidentally shipped 500K lines of Claude Code source to npm. no credentials leaked. no customer data exposed. but it's a reminder: when agents operate autonomously, governance tooling isn't a nice-to-have. isolated sandboxes. encrypted execution. hardware-bound credentials. this is why we built WhateverAI the way we did.

Q: does it support concurrent tasks? A: serial per agent key. call execute → wait for terminal status → next task. keeps execution clean. Q: what if task_result returns "running"? A: expected. poll every ~10s until success/done/error. that's the SSE window. Q: 401 error? A: your apikey. check it. restart gateway. Q: works with Claude Code? A: yes. and OpenClaw. and any MCP-compatible host. building? hit the docs: whateverai.ai

my agent's daily schedule: 6am: wake up (boot cloud phone) 6:01am: check apps (observe screen) 6:02am: do the work (tap, swipe, execute) 6:03am: report back (structured results) 6:04am: next task no coffee breaks. no slack messages. no "quick sync." just runs.

5 things your AI agent can do with a real phone that it can't do with an emulator 1/ interact with production app versions — same build, same state, same push notifications your users get 2/ test biometric and hardware-dependent flows — NFC, GPS, camera, fingerprint 3/ validate real app store installs — download, permission grants, first-run experience 4/ handle cross-app workflows — open Uber from a Maps link, share to WhatsApp, deeplink chains 5/ run 24/7 unattended — our Phase III roadmap: benchmark 7x24h automation for production workloads real phones > emulators. every time. try it: whateverai.ai

GMGN! It's Monday! Time to lock in. WhateverAI --> Soon.

2026's defining shift: AI as assistant → AI as worker 40% of applications will use task-specific agents by year-end. assistants answer questions. workers do the job. our agents don't describe what to do on a phone. they pick up the phone and do it.

real talk — here's what the setup actually looks like: $ @openclaw plugins install @ whateverai/cloudphone then in openclaw.json: { "plugins": { "entries": { "cloudphone": { "enabled": true, "config": { "apikey": "your-key" } } } } } $ openclaw gateway restart your agent now controls a real phone. took 2 minutes. Try it soon…

stages of AI agent grief: 1. denial: "my chatbot is basically an agent" 2. anger: "why can't it click a button" 3. bargaining: "maybe if I write a 500-line selenium script" 4. depression: *stares at broken emulator* 5. acceptance: *installs CloudPhone MCP from WhateverAI*

. @Cursor just hit $29B valuation. Sierra: $10B. harvey : $5B. VC has spoken: AI agents are the next major software category. the ones that win won't just think — they'll execute across real surfaces. phones are the most ubiquitous computing surface on earth. we start there.

4/ the setup is one line: { "cloudphone": { "enabled": true, "config": { "apikey": "..." } } } that's it. your agent now has hands. ship agent runs, not slide decks. try it: whateverai.ai

3/ we gave agents a real phone. OS-level access. tap, swipe, type, screenshot — all through MCP tools your agent already knows how to call. one integration path for QA, support scripts, and agentic workflows. same device surface your users see.

1/ AI can think, plan, and reason. but it still can't act on phones. not on real apps. not on real devices. not in real workflows. until now.