Delegated vs AutoGPT:
Hosted Specialist Agents vs Open-Source DIY Framework
AutoGPT is impressive technology — one of the first public autonomous agent systems to capture the imagination of what AI could do. But it requires significant technical setup and self-hosting. This comparison is for non-technical operators and small business owners who want the benefits of autonomous agents without the infrastructure.
Build-it-yourself vs ready in five minutes
AutoGPT is a framework. You clone the repo, configure API keys, set up a Python environment, and run an agent loop. If you know what you're doing technically, you can make it do remarkable things. If you don't, you spend your first weekend debugging dependency conflicts.
Delegated is a service. You sign up, connect your Gmail and calendar, give each agent a brief, and they start working. No infrastructure, no terminal, no API keys to manage. Five specialist agents — Sage (chief of staff), Scout (sales), Axel (web dev), Blaze (social), Lex (legal) — each scoped to a real business role.
Pricing Comparison
| Cost factor | Delegated | AutoGPT (self-hosted) |
|---|---|---|
| Base price | $49/mo flat | Free (open source) |
| LLM API costs | Included — no extra API bills | Separate (GPT-4/Claude charges per run) |
| Server / VPS costs | Included | Separate ($5–$20+/mo on Hetzner/DO) |
| Engineering setup time | ~5 minutes | Hours to days (varies by technical level) |
| Ongoing maintenance | None (managed service) | Requires updates, debugging, monitoring |
Feature Comparison
| Feature | Delegated | AutoGPT |
|---|---|---|
| No technical setup required | ||
| Managed hosting (no VPS to maintain) | ||
| LLM costs included in flat price | ||
| Dedicated browser per workspace | ||
| Live browser view | ||
| Five specialist agents | ||
| Inbox + calendar management | ||
| Lead generation + cold outreach | ||
| Website building (deployed) | ||
| Contract and legal review | ||
| Open-source / self-hostable | ||
| Full customisability | ||
| Community plugins + extensions | ||
| Works on any task (generalist) |
— = possible with custom configuration. Table reflects publicly available information as of May 2026.
Honest Limitations of Each Platform
Delegated limitations
- —Fixed agent roles — you cannot build entirely custom agents from scratch
- —Not open-source; relies on Delegated as a managed service
- —Monthly billing only (no annual discount yet)
- —Scoped to five business roles — not a general-purpose task runner
AutoGPT limitations
- —Requires technical setup; not accessible to non-developers
- —LLM costs add up quickly in recursive agent loops
- —No built-in specialist roles — you define everything from scratch
- —Ongoing maintenance required as dependencies and LLM APIs change
- —Agent loops can spin and accumulate costs before completing a task
Frequently Asked Questions
Should a non-technical small business owner use AutoGPT or Delegated?
Delegated. AutoGPT requires comfort with the command line, Python environments, API key management, and debugging. The setup time alone is a meaningful barrier. Delegated is purpose-built for small business operators who want autonomous agents working on real business tasks — inbox, leads, web, social, legal — without touching any infrastructure.
Is Delegated just AutoGPT in a nicer wrapper?
No. Delegated is built on OpenClaw, a custom proprietary agent runtime developed internally. The architecture is different: five named specialist agents, each configured and prompted for a specific role, running on a persistent VPS with a real browser, integrated with Gmail, Google Calendar, LinkedIn, and other business tools. AutoGPT is a generalist agent loop; Delegated is an opinionated, production-deployed team.
What tasks can AutoGPT do that Delegated cannot?
AutoGPT's generalist design means it can theoretically attempt any task you describe, and its open-source nature means you can extend it with custom tools. Delegated's five agents are scoped to specific roles — if you need an agent that does something outside those roles (e.g. writing and running custom data analysis scripts), AutoGPT with engineering investment is more flexible. For the five business functions Delegated covers, it is more reliable and requires no setup.
How much does running AutoGPT actually cost vs $49/month for Delegated?
For a non-trivial workload — say, Scout running daily lead generation and Sage triaging an inbox — the equivalent in AutoGPT would require significant LLM API usage (likely $50–$200+/month in GPT-4 costs depending on run frequency and context length) plus a VPS ($5–$20/month) and your own setup and maintenance time. Delegated's $49/month flat covers all LLM costs and infrastructure.
- You want autonomous agents working now, not after a weekend of setup
- You are not a developer and do not want to manage infrastructure
- You want all LLM costs included in a flat monthly fee
- You need specific business roles handled (inbox, leads, web, social, legal)
- →You are a developer building and experimenting with custom agent systems
- →You need full control over the agent loop and tool set
- →You want to self-host and own your agent infrastructure
- →You want to contribute to or extend an open-source project
Autonomous agents without the engineering.
Five specialist agents on a dedicated VM. Inbox, sales, web, social, legal. Sign up and they start working — no terminal, no API keys, no monthly LLM bills.
Start with Delegated — free →This page is published by Delegated (delegated.to) and reflects our honest assessment of publicly available information about AutoGPT as of May 2026. We are not affiliated with or endorsed by the AutoGPT project. Verify current information at agpt.co before making a decision.