May 13, 2026 News
Notion Launches Developer Platform to Orchestrate AI Agents and Automate Workflows
Notion has introduced a new developer platform that allows teams to build custom AI agents, connect external agents, and create automated multi-step workflows that integrate data from any database. The platform includes Workers for running custom code, database sync capabilities, and support for external AI agents like Claude Code and Cursor, positioning Notion as an orchestration layer for human-AI collaboration. Over one million custom agents have been created by Notion users since the feature's February launch.
Skynet Chance (+0.01%): The proliferation of autonomous agents with cross-platform capabilities and custom code execution increases the complexity of AI systems, which could marginally raise coordination and control challenges. However, these are still bounded, task-specific agents operating within defined workflows rather than general autonomous systems.
Skynet Date (+0 days): By making agent deployment and orchestration more accessible to non-technical users and enabling agents to operate across multiple platforms, this slightly accelerates the pace at which autonomous AI systems become embedded in critical workflows. The impact is minor as these remain narrow, tool-using agents rather than autonomous decision-makers.
AGI Progress (+0.01%): This represents meaningful progress in agent orchestration and multi-tool coordination, which are important components of more general AI systems. The ability to coordinate multiple agents, execute custom logic, and integrate diverse data sources demonstrates advancement toward more capable and flexible AI systems.
AGI Date (+0 days): By democratizing agent development and providing infrastructure for agent coordination, Notion is accelerating the practical deployment and scaling of agentic AI systems. The platform's focus on making agent orchestration accessible to developers speeds up the timeline for widespread adoption of more sophisticated AI workflows.
Anthropic Targets Proactive AI Agents That Anticipate User Needs
Anthropic is experiencing rapid growth, potentially reaching a $950 billion valuation and outpacing OpenAI in business market share. Cat Wu, head of product for Claude Code and Cowork, discusses Anthropic's product strategy focused on staying at the AI frontier rather than reacting to competitors, and reveals the company's next major focus: developing proactive AI agents that can anticipate user needs and automate workflows without explicit instruction. The company continues rapid model releases while exploring specialized deployments like Glasswing for security-sensitive applications.
Skynet Chance (+0.04%): Proactive AI that anticipates needs and autonomously sets up automations represents advancement toward systems with greater agency and reduced human oversight, potentially increasing alignment challenges. The focus on agents managing fleets of other agents creates layered complexity that could obscure control and decision-making processes.
Skynet Date (-1 days): The rapid deployment pace (six models in one year) and explicit focus on proactive autonomous agents that work without explicit human instruction accelerates the timeline toward increasingly agentic AI systems. However, Anthropic's cautious approach with models like Glasswing and emphasis on safety provides some counterbalance to acceleration.
AGI Progress (+0.03%): The shift from reactive chatbots to proactive agents that understand context, anticipate needs, and autonomously configure workflows represents meaningful progress toward more general intelligence capabilities. The company's sustained rapid model improvements and market success suggest they're successfully scaling along capability curves.
AGI Date (-1 days): Anthropic's ability to release six major models in a year while maintaining quality and the explicit roadmap toward proactive, autonomous agents indicates accelerating development pace. The company's growing valuation and market share suggest increased resources that will further accelerate AGI research timelines.
Anthropic Surpasses OpenAI in Business Customer Adoption for First Time
According to Ramp's AI Index based on expense data from over 50,000 companies, Anthropic now has 34.4% of verified business customers compared to OpenAI's 32.3%, marking the first time Anthropic holds the top position. Anthropic's market share grew by 26% over the past year while OpenAI's declined by 1%, driven by Anthropic's strategy of targeting technical customers and broadening through enterprise tools.
Skynet Chance (-0.03%): Increased market competition and diversification of AI providers reduces single-point-of-failure risks and creates market pressure for responsible practices, though the effect is marginal. Multiple strong players competing on safety and reliability can lead to better alignment incentives.
Skynet Date (+0 days): Market share shifts between existing AI labs do not materially accelerate or decelerate the pace toward potential loss-of-control scenarios. This represents redistribution of existing capabilities rather than fundamental capability advancement or safety breakthrough.
AGI Progress (+0.01%): Growing enterprise adoption and market validation of advanced AI systems demonstrates practical utility approaching general-purpose capabilities, though this represents deployment rather than fundamental capability breakthrough. The competitive pressure may drive incremental improvements in model capabilities.
AGI Date (+0 days): Increased business adoption and revenue for AI labs provides more resources for continued R&D and creates competitive pressure for capability advancement, modestly accelerating the timeline. The market expansion suggests sustainable funding for continued development.
Adaption Launches AutoScientist: AI System for Automated Model Training and Self-Improvement
Adaption, a new AI research lab, has released AutoScientist, a tool that automates the fine-tuning process by co-optimizing data and models to help AI systems learn capabilities more efficiently. The system is designed to enable continuous model improvement and could democratize frontier AI training beyond major labs. The company claims AutoScientist has more than doubled win-rates across different models and is offering free access for the first 30 days.
Skynet Chance (+0.04%): Self-improving AI systems that can optimize themselves with minimal human oversight represent a step toward recursive self-improvement, a key concern in AI safety and loss of control scenarios. However, this system appears focused on task-specific fine-tuning rather than fundamental architectural changes, limiting immediate risk elevation.
Skynet Date (-1 days): By democratizing advanced model training capabilities beyond major labs and accelerating the fine-tuning process, this tool could accelerate the development of increasingly capable systems across more actors. The automation of what was previously human-intensive work speeds the overall pace of AI capability advancement.
AGI Progress (+0.03%): AutoScientist represents meaningful progress toward automated AI development pipelines and self-improving systems, which are important capabilities on the path to AGI. The ability to co-optimize data and models automatically addresses key bottlenecks in scaling AI capabilities and suggests movement toward more autonomous AI research.
AGI Date (-1 days): The tool significantly accelerates model training and fine-tuning processes while democratizing access to frontier-level capabilities, potentially multiplying the effective research capacity working on advanced AI. This automation of previously manual optimization processes could materially speed the timeline toward AGI by reducing iteration cycles and expanding the number of teams capable of frontier research.