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Marketplace connecting paid domain-expert contractors to AI labs for data labeling, RLHF and model evaluation work.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
AI coding platform pairing a browser IDE, multi-model chat and an AI website/app builder with GitHub sync and instant deploy.
Design-system platform that packages tokens, code components, and rules into scoped context for AI coding agents.
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- ✦Data annotation and multi-format labeling
- ✦RLHF and human preference feedback
- ✦AI model red-teaming and safety testing
- ✦On-demand vetted ML/prompt engineering talent
- ✦Synthetic data generation
- ✦Structured model evaluation and benchmarking
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦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
- ✦Built-in AI IDE and code generator
- ✦Access to 15+ AI models in one platform
- ✦AI website/app builder from prompts
- ✦GitHub repository sync
- ✦Runs Python, React, Next.js and Node apps
- ✦Instant deploy to Vercel
- ✦Bring-your-own API keys for higher limits
- ✦Scoped MCP context distribution to multiple AI coding tools
- ✦Design token and component API management
- ✦Collaborative documentation with analytics
- ✦Figma and Storybook data source integration
- ✦Feedback loop for improving AI context quality
- ✦Skill and exporter management for agent capabilities
- →AI labs sourcing domain experts for RLHF projects
- →Companies needing red-teaming of a new model
- →Teams building custom labeled training datasets
- →Domain experts (healthcare, legal, finance) earning remote pay for AI training work
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →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
- →Building full-stack web apps with AI
- →Generating landing pages and WordPress plugins
- →Iterating on a synced GitHub codebase
- →Prototyping app clones quickly
- →Product teams giving AI coding agents accurate design-system context
- →Design system managers publishing a single source of truth
- →Engineering teams reducing token usage by scoping agent context per team