Monitoring and tracking artificial intelligence development and risk assessment in real-time.

Skynet Chance (+0.09%): The model's capability to build complex software autonomously and, critically, its use in debugging and improving itself represents a concrete step toward recursive self-improvement, a key concern in AI control and alignment literature. The expansion of who can build software also potentially democratizes access to powerful AI development tools, increasing risks of misuse or unintended consequences.

Skynet Date (-1 days): Self-improving AI capabilities and autonomous software development accelerate the timeline toward advanced AI systems with greater autonomy and reduced human oversight. The competitive race between major AI labs (OpenAI and Anthropic releasing within minutes) suggests rapid capability escalation is intensifying.

AGI Progress (+0.06%): The ability to autonomously create complex applications over days and perform "nearly anything developers do on a computer" represents significant progress toward generalist AI capabilities. The self-improvement aspect—using the model to debug itself—demonstrates meta-learning and recursive capability enhancement, both considered critical milestones on the path to AGI.

AGI Date (-1 days): Self-improving models that can contribute to their own development create a potential feedback loop that accelerates AI progress. The competitive dynamics forcing synchronized releases between major labs indicates an arms race mentality that prioritizes speed over caution, likely accelerating the AGI timeline.

Skynet Chance (+0.04%): Distributing AI infrastructure across orbital satellites makes centralized oversight and control more challenging, potentially increasing risks of autonomous systems operating beyond terrestrial governance frameworks. The decentralization and inaccessibility of space-based compute could complicate shutdown mechanisms if alignment problems emerge.

Skynet Date (-1 days): The orbital data center infrastructure could accelerate the timeline by enabling more cost-effective scaling of AI compute capacity, though the technical hurdles of space deployment provide some offsetting delay. The net effect modestly accelerates the pace toward potential control issues.

AGI Progress (+0.03%): The proposal to dramatically expand available compute capacity through orbital infrastructure represents a significant step toward overcoming one of the key bottlenecks in AGI development—access to sufficient, cost-effective computing power. If realized, this could enable training runs at scales currently infeasible on Earth.

AGI Date (-1 days): Musk's timeline predicting orbital AI capacity exceeding Earth's total within five years suggests a major acceleration in available compute resources, potentially shortening the path to AGI by 2028-2030. The FCC's favorable regulatory environment and SpaceX's launch capabilities make rapid deployment plausible, accelerating the AGI timeline.

Skynet Chance (+0.04%): Enterprise-scale deployment of autonomous AI agents with external system access increases potential attack surface and unintended consequences, though built-in access controls and management features provide some mitigation. The proliferation of agents across critical infrastructure companies like Oracle and State Farm raises stakes for potential misalignment or exploitation.

Skynet Date (-1 days): Accelerates practical deployment of autonomous agents into enterprise environments with real-world system access, moving AI capabilities closer to operational control of critical infrastructure. The platform's focus on scalability and ease of deployment could speed widespread adoption of agentic systems.

AGI Progress (+0.03%): Represents significant progress in making AI agents practical and scalable for complex, real-world enterprise tasks with external integrations and autonomous decision-making. The employee-like management paradigm suggests advancement toward more general-purpose, adaptable AI systems.

AGI Date (-1 days): Platform infrastructure that reduces friction for enterprise AI agent adoption accelerates the feedback loop between deployed AI systems and further capability development. Major enterprise partnerships provide OpenAI with substantial real-world data and use cases to refine agentic capabilities toward more general intelligence.

Skynet Chance (+0.04%): Multi-agent coordination represents a step toward more autonomous AI systems that can self-organize and divide complex tasks with less human oversight, potentially increasing alignment challenges. However, this remains within controlled commercial deployment with human-in-the-loop workflows, moderating the risk increase.

Skynet Date (-1 days): The deployment of coordinated multi-agent systems accelerates the development of more autonomous AI capabilities that could operate with reduced supervision. The practical implementation in commercial products suggests faster real-world adoption of agentic AI paradigms.

AGI Progress (+0.03%): Agent teams that can autonomously coordinate and parallelize work represent meaningful progress toward more general problem-solving capabilities, a key AGI requirement. The expanded context window and broader applicability across knowledge work domains demonstrates improved generalization beyond narrow task execution.

AGI Date (-1 days): The rapid iteration from Opus 4.5 (November) to 4.6 (February) with significant architectural enhancements suggests an accelerating development pace. Multi-agent coordination capabilities being deployed commercially indicates faster-than-expected progress in scaling AI autonomy and collaborative reasoning.

Skynet Chance (+0.01%): Massive consumer adoption (750M users) of AI systems increases societal dependence on AI decision-making and normalizes AI integration into daily life, marginally raising long-term risks of uncontrolled AI influence. However, this represents deployment of existing technology rather than fundamental capability breakthroughs in autonomy or control.

Skynet Date (+0 days): Widespread commercial deployment and rapid user growth accelerates AI infrastructure build-out and normalization of AI systems in society, slightly hastening the timeline for potential advanced AI scenarios. The competitive pressure between major AI labs may push faster iteration cycles.

AGI Progress (+0.02%): The launch of Gemini 3 with "unprecedented depth and nuance" and processing over 10 billion tokens per minute demonstrates continued scaling and capability improvements in large language models. This represents meaningful incremental progress toward more general AI systems, though it's still within the current paradigm of scaled language models.

AGI Date (+0 days): Google's massive revenue growth ($400B annual) and continued investment in AI infrastructure (new Ironwood TPU chips) provides substantial resources for accelerated research and development. The competitive dynamics with ChatGPT and deployment at scale create strong market incentives for faster AGI capability development.

Skynet Chance (+0.01%): Agentic AI tools gaining deeper access to development environments and performing increasingly autonomous tasks represents incremental progress toward systems with more agency, though this remains a narrowly scoped coding assistant. The integration is designed with human oversight and reversion capabilities, which provides some control mechanisms.

Skynet Date (+0 days): The widespread deployment of agentic AI tools in mainstream development environments slightly accelerates the normalization and capability growth of autonomous AI systems. However, the impact on timeline is minimal as this is an incremental deployment rather than a fundamental breakthrough.

AGI Progress (+0.02%): This represents meaningful progress in AI agents performing complex, multi-step tasks autonomously within real-world development workflows, including planning, execution, testing, and error correction. The use of MCP for tool integration and the agents' ability to understand project structure and iterate on solutions demonstrates advancing agentic capabilities relevant to AGI.

AGI Date (+0 days): The commercial deployment of sophisticated agentic coding tools by a major tech company accelerates the development and refinement of agentic AI systems through real-world usage at scale. This feedback loop and infrastructure development (like MCP standardization) may modestly accelerate progress toward more capable autonomous systems.