A [year ago](https://openai.com/index/built-to-benefit-everyone/#livestream-replay), OpenAI promised to deliver "an automated AI research intern" by September of 2026.
While it hasn't released the research intern as a product, there's one aspect of the GPT-5.6 launch where OpenAI has already blown past its goal.
In an exclusive interview with The Deep View, the OpenAI Research team confirmed that it used its new flagship GPT-5.6 Sol model to handle the post-training for its lightweight GPT-5.6 Luna model. In the process, Sol performed work that would have normally been done by a more experienced researcher.
"Sol helping post-train Luna is actually quite a big deal. This is not the kind of task we could hand to an intern," Tejal Patwardhan, OpenAI research lead on post-training, told The Deep View.
The tasks Sol carried out included:
Set up the post-training runMonitor the job over timeRepair technical problemsRun evalsOversee the workflow
"Previously, it might have been possible to ask the model to do one piece of this for you. It is much harder to pull all the pieces together and get to the desired end state, which is a successful training run," Katy Shi, lead for the Codex research team, told The Deep View.
This wasn't the first time that OpenAI has used one model to help train another. At the launch of GPT-5.3-Codex in February 2026, OpenAI announced that it was "our first model that was instrumental in creating itself." And CEO Sam Altman said, "It was amazing to watch how much faster we were able to ship 5.3-Codex by using 5.3-Codex."
However, the tasks Sol was able to execute while training Luna were a big leap forward, achieved less than six months later.
"The difference is the magnitude of capability, the amount of work, how senior the person normally has to be to do it, and how much context is required," said Patwardhan.
This wasn't recursive self-improvement (RSI), where the models build the next models. But it was beyond what an entry-level researcher could be expected to handle.
Nevertheless, this wasn't a case where the model was replacing a human or enabling a team to get work done with fewer people.
"I would say 80% of researchers’ jobs sometimes is just getting the experiment up and running," said Shi.
In this case, the model took over the time-consuming work of launching, debugging, and supervising the training run, freeing up researchers to spend more time developing ideas and running more creative experiments.
As a result of the success of using Sol to train Luna, the OpenAI team will disseminate the learnings across the company. "We’re looking at all parts of our research pipeline and how they can be accelerated with models," said Patwardhan.
Our Deeper View #
Beyond the automated research intern targeted for September 2026, OpenAI also promised "a truly automated AI researcher by March of 2028." The idea here is an agent you could assign a research task to, and it could automatically handle all of the steps with little to no human interaction. I know plenty of professionals across various industries who would love to have a research assistant to carry out important projects for them. What the OpenAI Research team accomplished by training Luna with Sol isn't quite that, but it showed that it could handle several aspects of that work, from completing multi-hour research workflows to overseeing end-to-end execution of tasks to continuing to work through ambiguity and problems. This is another stunning example of how much these models have improved in just a few short months.