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As AI agents like Meta's Muse and OpenAI's dots handle tasks on behalf of users, websites need a way to verify a real person is actually behind each agent. World ID's Proof of Human system lets people prove they're unique individuals without revealing their identity, solving the problem that agent numbers are unlimited but humans are finite.
- Amazon already blocked Muse from shopping because the agent didn't disclose it was AI, showing websites will enforce rules about agent transparency and attribution as these tools scale
- Proof of Human matters for practical limits: rate limiting per person, counting unique customers, and preventing one person from gaming purchase allocations by running thousands of agents
- The system uses zero-knowledge proofs so agents can prove human backing without sharing personal data, and companies like Okta, Vercel, and Browserbase are already building it into their platforms
OpenAI is releasing Dots, autonomous AI agents powered by GPT-6 Astra that run 24/7 to handle tasks independently or alongside you across ChatGPT, Slack, and Teams. They learn your preferences over time, connect to 4,000+ apps, and include built-in safeguards so you control what they do.
- Dots can work autonomously on their own cloud computer, access connected apps, and handle multiple projects simultaneously, or work directly alongside you on your device with permission
- The system includes granular controls: you can set custom rules for when dots act independently vs. require approval, review their work in real time, and certain sensitive actions like password changes always require your involvement
- Specialist dots for enterprises come with their own identity and credentials, integrating with Microsoft Agent 365, designed to handle defined responsibilities like procurement and customer support with team oversight
A practical guide to connecting Claude Opus 5.5 as an external tool to ChatGPT's Dots system, using it selectively for deep research, strict reviews, visual analysis, and long-running tasks while keeping Dots as the orchestrator. The article walks through 10 specific upgrades to make the combined system cheaper and more capable.
- Opus 5.5 connects as a private backend tool called only when tasks need deeper context, stricter review, visual analysis, or patience — not as a model replacement inside Dots itself.
- The four weakest points in Dots (shallow reading, uniform effort levels, weak self-review, poor visual work) map directly to where Opus adds value, and each has a specific upgrade to fix it.
- Caching the unchanging prompt prefix (standing brief, house rules, schemas) with a one-hour TTL cuts costs dramatically for teams running multiple tasks per day, and compacting the context window before it fills prevents mid-task cutoffs.
- Sorting work by whether anyone is waiting lets you move patient tasks (weekly digests, backlog triage, doc sweeps) to off-hours at lower cost, and moving house rules into the repo eliminates contradictions across four separate places.