When software platforms started integrating LLMs, developers were juggling different IDE plugins & frameworks to connect external systems...proving the NxM method was a fragile bet on scalability.

Since Anthropic proposed the MCP standard in late 2024, interoperable standards became a core topic for building reliable AI infrastructure. Major tech firms collaborated extensively on this open source protocol that was gaining traction in the software community.

Early this month, the Linux Foundation created the AAIF (Agentic AI Foundation) and welcomed Anthropic's donation of the MCP protocol as an industry standard.

The industry is now gradually shifting towards orchestrating agent workflows more confidently because the protocol has been constantly updated - from RI, to schemas, OAuth flows...allowing for longer running API processes.

That being said while parallel reasoning scales, parallel execution is still a challenge...and defining AGI use cases becomes more of a distraction.

The MCP paved the way for tool calling, but building agents beyond read-only capabilities requires deterministic evals, governance, state isolation, log analysis, workflow merging & other systematic reviews with constant human in the loop hardening.

Consumers are witnessing this paradigm through tools like browsers transforming into 'agent-runtimes' ...as tech companies progressively build broad ecosystem apps (ex: Open AI's Atlas & Perplexity Comet) while running evals on the backend.

A lot of news sources are portraying this as aggressive web tool or browser competition... but at this point of time the hype is misinformation at best. Those VC funded initiatives are still in experimental phase for understanding tool boundary & reliability.

Innovation in web agents has been steadfast & while AI browsers are an important step in implementing evals on a massive scale, the gap between LLMs & core infrastructure is an urgent issue in terms of security (native policy layer).

While MCP has allowed for safe tool calling...dev teams still need to implement strong audit trail & behavior validation habits in their collaborative workspace (if they want to build scalable agentic architecture).