Dots: Always-on agents

OpenAI's Dots launch drew mixed HN views on cost, trust, lock-in, and real use.

Backend or platform developers evaluating always-on agents

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- Only the title "Dots: Always-on agents" and the URL are available.
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Splitting agents by domain worked well, one user said
- A heavy Grok Bot user said separate work and personal bots keep memory from mixing.
- Combined with cloud agents, it solved running multiple git worktree streams at once.
- But tasks took about 1 hour versus about 10 minutes locally, and inference spend rose 2-3x.
No need for overnight agents, one view
- One developer said their throughput is limited by their own approval speed.
- They said webhooks can already deliver pre-researched bug reports.
Concerns about access and trust
- One commenter said coding agents still sometimes go the wrong way or misreport what they did.
- Giving unsupervised agents person-level access was called a footgun.
- One user claimed the cloud environment is MITM, seeing an OpenAI-issued certificate for gmail.com.
Lock-in and pricing concerns
- One view was that integrations and work history make agents harder to switch than models.

Start agents with read-only permissions
- List the connected-app permissions of the agent you use today.
- Turn off write and delete access and run read-only first.
Separate work and personal agent contexts
- Create separate agents and memory per domain.
- Block them from reading each other's memory.
Measure cost and time before adopting
- Run the same task locally and via an async agent.
- Record time and inference cost for each and compare.

always-on agentAn agent that keeps working in the cloud even when you aren't watching. Like an assistant on a 24-hour shift.

MITMA setup where someone in the middle can read your traffic. Like a mail carrier who opens and reseals your letters.

git worktreeA git feature that opens multiple branches of one repo in separate folders at once.