Something interesting has been happening with ChatGPT over the past several months, and we have been watching it closely. OpenAI has been quietly transforming its assistant from a clever conversationalist into a genuine agent, one that can take on a goal, break it into steps, browse the web, run tasks on a schedule, and work toward a result largely on its own.
If you have used the newer agent capabilities, you have probably felt the shift. You can hand ChatGPT a fuzzy, multi-part objective and watch it reason through the steps, pause for your input, and pick the work back up. You can set tasks to run at specific times or on a recurring basis. It is starting to feel less like a chatbot and more like a coworker who actually follows through.
What Actually Changed
The headline is that ChatGPT now leans hard into agentic behavior. Its agent mode can take on complex, multi-step tasks, reason through them, browse the web, and use tools to get things done, while still letting you interrupt, steer, or pause at any point. [1]
On top of that, OpenAI has been building out scheduled and recurring task capabilities, so an agent can run on a timer, react to events, and handle repeatable workflows without someone babysitting it. [2] For developers, the Agents SDK rounds this out with orchestration, handoffs between specialized sub-agents, and parallel execution. [3]
In other words, the things that used to require stitching together a pile of automation tools are increasingly becoming native to the assistant itself.
Why We Are Genuinely Happy About This
Here is the honest, slightly cheeky truth from our side of the table. A lot of what ChatGPT is now rolling out are capabilities we have been building into the Intueo platform for a while: persistent memory, specialized agents instead of one overloaded generalist, scheduled and autonomous task execution, and tool use that actually connects to real systems.
When the largest AI company on earth ships agentic scheduling and multi-step task execution to hundreds of millions of people, it does two things for us. First, it validates the direction we bet on early. We were not chasing a fad; we were building toward where the whole industry was clearly heading. Second, it educates the market. Every person who experiences a capable agent in ChatGPT becomes someone who immediately understands what we mean when we describe what our platform does.
The Part We Think About Carefully
We are not naive about it either. When core agentic features become table stakes inside the biggest consumer AI product, no single capability stays exclusive for long. The advantage stops being "we can do this and others cannot," and becomes "we can do this in a way that fits your specific business better than a general-purpose assistant ever will."
That is a healthy pressure. It pushes us to keep our edge where it actually matters: depth of memory, how tightly agents integrate with a company's real tools and data, reliability under production conditions, and the ability to shape the whole system around a particular workflow rather than a generic one.
Where That Leaves Us
We will be candid: our platform is still in beta. We are refining it, learning from real usage, and improving it constantly. And we are seriously considering focusing it on a specific niche, industry, or market where we can tailor it deeply and turn it into something purpose-built rather than broadly general.
The big players proving out agentic AI at scale does not threaten that plan. It strengthens it. A rising tide of capable agents makes specialization more valuable, not less. We got here early, we have done the hard testing, and we are excited about turning that head start into something genuinely useful for the right audience.
So yes, ChatGPT getting more agentic is good news. It is good for users, good for the industry, and good for us. We will keep building, keep refining, and keep our eyes on the place where we can make the biggest difference.
