OpenAI’s new API and Agents SDK consolidate a previously fragmented complex ecosystem into a unified, production-ready framework. For enterprise AI teams, the implications are potentially profound: Projects that previously demanded multiple frameworks, specialized vector databases, and complex orchestration logic can now be achieved through a single, standardized platform. But perhaps most revealing is OpenAI’s implicit acknowledgment that solving AI agent reliability issues requires outside expertise. This shift comes amid growing evidence that external developers are finding innovative solutions to agent reliability – something that the shocking Manus release also clearly demonstrated. This strategic concession represents a critical turning point: OpenAI recognizes that even with its vast resources, the path to truly reliable agents requires opening up to outside developers who can discover innovative solutions and workarounds that OpenAI’s internal teams might miss.Read More
The large language model (LLM) has become a cornerstone of many AI applications.
Computer use is a breakthrough capability from Anthropic that allows foundation models (FMs) to visually…
A directive from the National Institute of Standards and Technology eliminates mention of “AI safety”…
Speech foundation models, such as HuBERT and its variants, are pre-trained on large amounts of…
This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team…
At Definity, a leading Canadian P&C insurer with a history spanning over 150 years, we…