OpenAI Codex Reliability Questions Follow DevDay 2026 Launches

A big stage, a busy lineup

OpenAI's DevDay 2026, held on September 29, was crowded with announcements. The company introduced always-on AI agents called Dots, a new GPT-6.1 Sol model, a collaborative ChatGPT workspace, new agent APIs for developers and a cloud-based version of its Codex coding tool 2. The headline developer feature is Codex Cloud, which lets programmers start a coding task on one device and pick it up on another, whether desktop, web or mobile 2. New plans for developers and businesses were also part of the package 2.

A widely shared post in the r/ChatGPTPro community adds a few details to that list. It cites ChatGPT Space and Pages and a refreshed Codex CLI, and it says GPT-6.1 Sol is priced at a fraction of Astra, an earlier model 1. The author calls the polish real and some of the work excellent 1. Both accounts agree that this was one of OpenAI's most ambitious developer releases.

The complaint: work that vanishes

The Reddit post is not mainly about the announcements. It is a public warning, labeled a PSA, about what developers say happens after the keynote. Its central claim is simple: long agent runs in ChatGPT Work and Codex fail, and the work is lost 1. The author also says failed runs still consume usage allowances, and that MCP connections drop during long sessions 1. MCP is the protocol agents use to connect to external tools and data.

The post also criticizes support. It describes OpenAI's help channel as a chat widget where users reach a bot before anyone else 1. It separates its complaints into two groups: reliability failures and plain product limitations 1.

These claims come with an important caveat. The author says every case is a user report collected from GitHub and the OpenAI Developer Community as of September 30, and that none have been confirmed by OpenAI 1. The material is anecdotal and gathered by one person who has already formed a view. The author says outright that OpenAI seems to be shipping too much at once without keeping quality under control 1. The mainstream coverage of the event does not mention reliability problems at all 2. That silence does not prove the problems are absent. It reflects that launch-day reporting describes what a company announces, not how the products hold up a day later.

Why the details matter

Even with those caveats, the specific complaints deserve attention because of where OpenAI is taking its products. Nearly everything announced at DevDay pushes toward longer, more autonomous work [2]:

• Dots are always-on agents.
• Codex Cloud keeps tasks running across devices and sessions.
• The new agent APIs invite developers to build multi-step workflows on OpenAI's infrastructure.

In that kind of system, a failed run costs more than a bad autocomplete suggestion. If an agent works for an extended period and then drops a tool connection or crashes without saving its progress, the developer loses time and context. If usage is also deducted for the failed attempt, as the post alleges 1, the user pays for that loss. As agent runs get longer, unreliability gets more expensive.

The support complaint fits the same pattern. For a casual user, a bot-first help widget is a minor annoyance. A team that has built a workflow around Codex and loses a long run needs a way to escalate the problem and ask for credit. The post's "thin back office" framing describes this gap between consumer-style support and professional-grade dependence 1.

Reading the gap

The two accounts describe the same products from opposite ends. The news coverage presents the shop window: new models, new surfaces and a cheaper flagship 2. The Reddit warning, which uses that same image, describes the stockroom behind it 1.

My reading is that both are probably true at once, and the tension is predictable rather than scandalous. Shipping a large set of agent products in one event almost guarantees rough edges. The real question is whether those edges damage the work itself. Lost runs, charges for failed attempts and unstable tool connections fall into that category, and they deserve more weight than cosmetic bugs.

Until OpenAI responds to these reports, a cautious approach makes sense for teams considering Codex Cloud or Dots for serious work:

• Treat long agent runs as checkpoints rather than single jobs.
• Keep work in version control outside the agent's session.
• Watch usage carefully after failures.

DevDay showed what OpenAI wants its agents to do. Whether they reliably finish what they start is still unproven in the reports available so far.