How a research collaboration in contracting is helping us train and evaluate AI agents on complex professional work.
When we introduced GPT‑6 Astra, we demonstrated how far our models have come in using computers for professional work, from preparing documents to testing websites. Our next goal is to make agents more capable and efficient at using specialized software to solve complex business problems. We’re exploring how to train models to understand a company’s business rules, execute multi-step workflows, and verify that their work meets the original requirements.
To accelerate this research, we’re partnering directly with a small number of software companies that understand these workflows best. Together, we’re identifying challenging, high-value tasks and turning them into research problems for training and evaluating our models, ultimately making our models more capable and useful in real-world business applications.
Our first partner is Ironclad, a leader in AI contracting. Working closely with Ironclad’s team, we’ve developed tasks that require agents to configure agreements, approvals, and reusable legal terms, and demonstrated progress on these complex workflows. Ironclad’s expertise has been instrumental in defining what success looks like and bringing real customer needs directly into frontier model development. We’re grateful for their partnership and excited to share what we’ve accomplished together.
GPT‑6 Astra is our first frontier model trained on Ironclad tasks. On our research evaluation, its average score was 32% higher than GPT‑5.6 Sol’s, while estimated time per attempt was 48% lower.1
Consider a legal operations team setting up a process for buying software.
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