Three companies are coming together to create AI agent standards that could be useful across online platforms. This collaboration could rocket AI forward.
Imagine a world in which various AI agents can’t and won’t work together because every company blusters too much by creating closed systems. That means the AI request on one platform would provide different results from other platforms for the same request, which could become confusing for users. Thankfully, three major players have created a collaboration that could open the door to future AI success.
The big dogs get together to create AI agent standards
Three major AI companies just made a move that could change how AI agents work together. OpenAI, Anthropic, and Block launched the Agentic AI Foundation collaboration under the Linux Foundation AI, and they’re donating their core agent technologies to make sure different AI systems can actually talk to each other. Think of it like the early days of the internet, when everyone needed to agree on how websites would connect. Anthropic handed over its Model Context Protocol, OpenAI contributed AGENTS.md, and Block gave up Goose. Big names like Google, Microsoft, and AWS are backing the effort. The whole point is to avoid a future where AI agents from different companies can’t work together because everyone built their own closed system.
The Agentic AI Foundation (AAIF) brings open source AI agents together
The world of AI is taking online production in the same direction that the early days of the internet operated. If various systems don’t work together and move beyond the closed processing of the current atmosphere, things could easily break down in a world of incompatibility. AI inoperability isn’t something that any user or AI company wants to experience, leading to this enterprise of AI integration. With this movement forward, the AAIF allows for open source projects using AI agents and the new standards that are being put in place.
Are there other members helping create new AI agent standards
While Anthropic, Block, and OpenAI are the three major players, there are other contributors to the newly formed AAIF. Other members include AWD, Bloomberg, Cloudflare, and Google. This shows a new direction in the tech world for sharing information and creating industry-level standards that allow AI agents to be trustworthy on a much larger scale than they are right now.
Communication is key, especially in this instance
While the advice that communication is key to success in any relationship, it’s certainly the case here. This new collaboration brings various agents together to work seamlessly, ensuring developers don’t have to create integrations that are only applicable to each AI system. This can be a huge time saver for users, allowing projects to cross over various agents and systems without requiring special coding, permissions, or the use of a closed process.
“We need multiple protocols to negotiate, communicate, and work together to deliver value for people, and that sort of openness and communication is why it’s not ever going to be one provider, one host, one company.”
– Nick Cooper, OpenAI engineer
Forget proprietary, it’s time to share
Creating successful and sustainable AI agent standards means ensuring systems can be utilized across various platforms to avoid operators running into closed walls and blocks that are put in place because one agent doesn’t share with another. This means bringing everything together under one collaborative group to ensure developers can utilize the tools and benefits of AI without too much trouble.
“By bringing these projects together under the AAIF, we are now able to coordinate interoperability, safety patterns, and best practices specifically for AI agents.”
– Jim Zemlin, executive director of the Linux Foundation
Block might be an unusual addition to the AI agent standards
Block isn’t known for AI infrastructure, but for its payment systems, Square and CashApp. Still offering the use of Goose to allow openness across systems makes Block a major contributor to the newly formed AAIF. This system proves that openness at scale can allow developers to create their projects easily. Goose is used by thousands of engineers every week for coding, data analysis, and documentation. By open-sourcing Goose, the system serves a dual purpose for Block. It gives Block access to community stress tests while allowing it to work on the AAIF vision.
This new collaboration should open AI for many developers and engineers who will benefit from new AI agent standards to bring their projects together more seamlessly and hassle-free.
