Building ZeroTwo — The AI Agent That Plans, Acts, and Delivers.

Your most ambitious work, delivered.

I'm Reed Vogt — founder and CEO of ZeroTwo, the AI agent for ambitious work.

People are not short on ambition. They are short on execution capacity. There is a business to build, a campaign to launch, a market to research, a product to ship — and never enough hours to own all of it. Most AI stops at an answer and hands the real work back to you.

ZeroTwo closes the gap between intention and execution. Give it a goal. It gathers the context, makes a plan, acts across your files, apps, tools, and the web, and carries the work through to a polished result.

Bring the ambition. ZeroTwo delivers the work.

Reliable execution — Work you can depend on. ZeroTwo plans the work, takes action, preserves the context it needs, and keeps complex tasks moving toward completion. You see the plan, the progress, the recoveries, and the artifacts.

Affordable capacity — Room to explore, create, and accomplish. Take another approach without treating every attempt as an expensive decision. Affordable capacity means more completed work per subscription, not just a low price per request.

Polished deliverables — Finished work, not another starting point. Reports, decks, analyses, campaigns, applications, and documents that are ready to review, share, present, or ship.

Confidence to begin. Freedom to iterate. Work worth delivering.

1. Give ZeroTwo the outcome — Describe what you want accomplished. Add the relevant files, context, or constraints.

2. ZeroTwo plans and acts — It breaks the goal into steps, works across the necessary tools, and keeps the task moving.

3. Get back polished work — Review the result, refine it, then share, present, publish, or ship it.

Agentic execution

• Long-running agent sessions that plan, act, recover, and report progress
• Subagents and multi-agent delegation for parallel work
• Deep research that decides its own depth from what it finds
• Visible plans, task status, and approval gates before consequential actions
• Persistent goals, scheduled runs, and recurring automations

Deliverables and creation

• Documents, spreadsheets, and code artifacts with live preview
• Report generator and quarterly-business-review workflows
• Studio for images, video, audio, music, icons, and characters
• Image editing suite: inpainting, outpainting, relight, object insertion and removal, character swap, background removal, upscale, magic erase, and in-place text edits
• Sandboxed Python and shell execution for real analysis and builds

Connected work

• 470+ app connectors plus full MCP (Model Context Protocol) support
• Projects with file sources, knowledge graphing, sharing, and team collaboration
• A library that keeps every file, artifact, and generated asset in one place
• Web search, scraping, and fetch across multiple providers
• Installable skills and plugins that extend what the agent can do

Where it runs

• Web app, plus a desktop app with an integrated terminal, browser control, teach mode, and local MCP servers
• Device pairing and remote control from mobile
• Voice: dictation, companion speech, and a voice agent

Context and control

• Long-term memory across sessions, local and remote
• RAG over your documents with vector search and reranking
• Usage visibility, credits, and clear plan allowances
• Company onboarding, admin portal, and parental controls

Frontend

• React 18 + Vite, Electron for desktop
• shadcn/ui + Radix primitives
• Tailwind CSS + SCSS modules
• Zustand state
• ESLint + Prettier + Husky

Backend / Infra

• Node 24 + Express API
• Supabase (Postgres, Auth, Storage) with pgTAP-tested migrations
• Netlify (web), Render (API, task server, Redis), Railway

AI + Orchestration

• Multi-provider routing across OpenAI, Anthropic, Google, xAI, DeepSeek, Mistral, Cohere, Perplexity, Qwen, Moonshot/Kimi, Z.ai, MiniMax, Groq, Cerebras, Together, Fireworks, and more
• Model Context Protocol for connectors, tools, and local servers
• E2B for sandboxed code execution
• Mem0 for personalization and long-term memory
• Exa / Tavily / Serper / Brave / Jina for search, Firecrawl for extraction
• PostHog + Datadog for product and system telemetry

Models and routing are the mechanism, not the pitch. What matters is how much finished work comes out the other side.

• Production-grade agent systems: planning, tool calling, recovery, evals, tracing
• Cost per completed task as the real agent metric, not cost per request
• Multi-model streaming adapters and consistent UX across providers
• RAG pipelines: chunking, embeddings, hybrid search, reranking, caching
• Observability: latency, TTFT, token/cost metrics, failure taxonomy
• Security, approvals, and abuse controls for agents that take real actions
• Brand-level UX polish (fast, simple, "feels obvious")

• ZeroTwo: https://zerotwo.ai
• Company GitHub: https://github.com/zerothahuman
• My GitHub: https://github.com/EmilyThaHuman
• LinkedIn: https://www.linkedin.com/in/reed-vogt-ceo/
• X: https://x.com/vogt_reed
• Email: reed@zerotwo.ai

If you're building something ambitious and want to compare notes on agents, RAG, or shipping agentic products at scale, reach out: reed@zerotwo.ai