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VS Code extension letting developers chat with their own custom OpenAI assistants without leaving the editor.
Self-hosted cloud development environments and AI-agent governance, letting enterprises run coding agents on their own infrastructure.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Data-labeling and RL data platform supplying training data, environments and evaluation for frontier AI labs and enterprises.
Outlier is a platform where experts earn freelance income training and evaluating AI by writing prompts, rubrics and rating answers.
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No public pricing
No public pricing
No public pricing
- ✦in-editor chat with OpenAI assistants
- ✦workspace source-code context sharing
- ✦support for custom, user-defined assistants
- ✦secure management of the user's OpenAI account
- ✦Self-hosted workspaces with desktop and web IDEs
- ✦Coder Agents run coding agents on isolated infrastructure
- ✦AI Governance gateway for LLM usage control
- ✦SSO (OpenID Connect) and role/group sync
- ✦Audit logging and resource quotas
- ✦Multi-organization access controls
- ✦High availability and workspace proxies
- ✦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
- ✦Data labeling across modalities
- ✦RL environments and reward signals
- ✦Custom model evaluations and benchmarks
- ✦Human preference/annotation from an expert network
- ✦Recursion RL platform for enterprise agents
- ✦Robotics data (video, trajectories)
- ✦Remote AI-training gig work
- ✦Tasks: prompt writing, rubrics, rating answers
- ✦Flexible hours, work from anywhere
- ✦Weekly, quality-based pay
- ✦Roles across coding, STEM and languages
- ✦Free access to paid AI models
- →getting coding help without switching out of VS Code
- →using a personalized OpenAI assistant tuned to a project
- →quick in-editor Q&A while writing code
- →Standardize developer environments
- →Run AI coding agents securely on-prem
- →Enforce governance and compliance
- →Cut VDI costs
- →Speed up developer onboarding
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
- →Building training and evaluation datasets
- →Post-training and RLHF for models
- →Benchmarking model capability
- →Training enterprise specialist agents
- →Earning side income as an AI trainer
- →Contributing expertise to improve AI
- →Flexible remote work for grads and experts
- →Gaining hands-on AI and prompt experience