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No-code AI platform that builds full-stack apps, websites and agents from plain-language prompts with hosting built in.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
Enterprise AI coding assistant that pulls context from an entire codebase to power chat, code edits and debugging.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
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- ✦Prompt-to-app full-stack generation
- ✦Built-in backend, database and auth
- ✦One-click integrations (Slack, Notion, HubSpot, etc.)
- ✦Instant hosting and custom domains
- ✦Superagents for automated workflows
- ✦GitHub sync and code export
- ✦Modern terminal rebuilt for agentic coding workflows
- ✦Warp Agent with multi-agent orchestration and model routing
- ✦Oz platform for launching agents into the cloud via SDK, CLI, or terminal
- ✦Codebase indexing and granular permission controls
- ✦Team-wide usage visibility and spend/credit caps
- ✦Open-source terminal core
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦Codebase-aware developer chat
- ✦AI code completions and inline edits
- ✦Customizable and shareable prompts
- ✦Automatic bug identification and debugging help
- ✦Context filters to exclude sensitive repos
- ✦Integrates with major code hosts and IDEs
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- →Building internal tools and dashboards
- →Launching websites and landing pages
- →Creating customer portals and CRMs
- →Deploying AI agents that automate tasks
- →Developers who want an AI-assisted terminal for daily coding
- →Teams orchestrating multiple coding agents (Claude Code, Codex) together
- →Engineering orgs needing governance over agent-driven development
- →Companies moving agent workflows from local machines to the cloud
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Engineers asking questions about an unfamiliar large codebase
- →Teams standardizing common coding tasks with shared prompts
- →Developers debugging errors faster with AI-assisted context
- →Enterprises running large-scale code migrations
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts