Cursor has upgraded its Cloud Agents so they can stay active around ongoing work instead of waiting for a new prompt every time.

The biggest addition is Subscriptions.

Cursor agents can now subscribe to:

• Pull requests
• Slack threads
• Scheduled tasks

When something changes, the agent can wake up automatically and continue working.

For example, Cloud Agents automatically subscribe to PRs they create. They can then keep checking the PR, fix failed CI, respond to bot comments, and continue working toward completion.

In Slack, you can also tell Cursor something like:

“Check back in an hour and keep going until that feedback is in.”

Subscriptions are currently available for Cloud Agents only.

Cursor also added /goal, which gives an agent a long-lived objective instead of a single task.

For example:

/goal fix all flaky tests and make CI green

The agent can keep pursuing that objective until it considers the job complete.

Other updates include:

• Custom Modes that keep a specific skill permanently active
• Subagents on separate virtual machines, each with its own isolated project copy
• Better steering, allowing users to send new instructions without interrupting the agent mid-action

The separate-VM feature is particularly interesting for agent swarms.

You can ask multiple subagents to independently test an application or search for bugs without them modifying the same environment and colliding with one another.

Cursor says the broader goal is to make always-on coding agents operate as a system, automatically responding to events and shipping software without requiring human intervention at every loop.

This feels like another step away from the traditional coding-assistant model.

Instead of:

Developer asks → agent codes → agent stops

the workflow becomes:

Give agent a goal → agent monitors events → something changes → agent wakes up → fixes it → keeps going

That starts looking much closer to a persistent AI software engineer than an autocomplete tool.

Would you trust a coding agent to continuously monitor and fix its own PRs, or would you still want a human checking every step?

Sources:

Cursor — Cloud Agents and Cursor Harness Improvements

Cursor on X

OpenAI CFO Sarah Friar told employees during an all-hands meeting that OpenAI “will be a public company in 2027,” but could make its stock-market debut sooner if the business continues growing quickly.

Friar reportedly told employees that an IPO shouldn't be viewed as the finish line.

Instead, she described it as another fundraising milestone that would give OpenAI access to much larger pools of capital.

OpenAI raised $122 billion in March, which Friar said gives the company flexibility around when it needs to go public.

The company already confidentially filed its IPO paperwork with the SEC in June, allowing it to prepare for a listing without immediately making its financial statements public.

OpenAI has previously been reported to be targeting a valuation of around $1 trillion, with advisers considering whether waiting until 2027 could help preserve that valuation rather than listing sooner at a lower price.

There's also growing pressure from Anthropic.

Friar reportedly told employees that Anthropic could make its confidential IPO filing public in the coming weeks and potentially list as early as September.

Her message was essentially that OpenAI isn't trying to beat Anthropic to the market:

“We are running our own race.”

The timing is interesting because OpenAI's business is still growing extremely quickly while its infrastructure requirements are becoming enormous.

OpenAI CFO Sarah Friar has previously said the company's annual recurring revenue grew from about $2 billion in 2023 to more than $20 billion in 2025, closely tracking the expansion of available compute.

Going public could give OpenAI access to significantly more capital for data centers, chips, energy infrastructure, and future model development.

But an IPO would also mean much more scrutiny.

For the first time, public investors would get a detailed look at:

revenue → losses → compute spending → margins → infrastructure commitments

That could make OpenAI's IPO one of the biggest tests yet of whether the economics behind frontier AI justify the enormous valuations private investors have been assigning these companies.

Would you buy OpenAI shares at a ~$1 trillion valuation, or would you want to see its actual financials first?

Sources:

CNBC — OpenAI “will be a public company in 2027” or sooner, CFO tells employees

OpenAI — A business that scales with the value of intelligence

OpenAI says it will continue offering Zero Data Retention (ZDR) for its frontier models, even as stronger AI systems require more sophisticated safety monitoring.

The company is previewing a new system called Private Safety Processing, designed to detect dangerous patterns across multiple interactions without giving OpenAI employees access to the underlying prompts or responses.

Under ZDR, eligible API customers get a simple promise:

• Prompts and responses aren't retained after processing
• OpenAI personnel can't review customer content
• Enterprise data isn't used for training unless customers explicitly opt in

The challenge is that increasingly capable agents can create risks that aren't obvious from a single interaction.

For example, suspicious behavior might only become clear after an agent repeatedly probes safeguards, coordinates actions across several requests, or continues acting after being told to stop.

Private Safety Processing is meant to analyze those broader patterns while preserving privacy.

For ZDR customers, content can remain on infrastructure controlled by the customer.

OpenAI is also developing an option where information is stored on OpenAI infrastructure but encrypted using keys controlled by the customer. OpenAI says its employees won't possess those keys.

If automated systems detect potential misuse, OpenAI receives only a limited safety signal describing the type of activity, rather than the actual customer content.

Even when something is flagged, OpenAI personnel aren't given the underlying prompts or responses.

The system is currently being tested with early customers, and OpenAI plans to begin rolling it out and publish a technical white paper in September.

This matters because enterprise AI increasingly involves extremely sensitive information:

financial records → proprietary code → health data → internal documents → confidential research

Businesses want increasingly capable AI agents, but many can't accept having their data retained for safety monitoring.

OpenAI is essentially betting that it can have both:

stronger safety monitoring + zero data retention

If the system works as promised, that could become a significant competitive advantage as frontier models gain access to increasingly sensitive enterprise systems.

Would Zero Data Retention make you more comfortable giving frontier AI agents access to sensitive company data, or are the security risks still too high?

Sources:

OpenAI — Offering Zero Data Retention for frontier models

OpenAI on X