April 3, 2025 News
Cognition Introduces Affordable Pay-as-you-go Plan for Devin AI Coding Assistant
Cognition has launched a new entry-level pricing plan for its autonomous coding tool Devin, starting at $20 with a pay-as-you-go structure after initial credits are used. The company claims Devin 2.0 is significantly improved from its December release, now featuring project planning capabilities and better documentation features, though independent evaluations suggest it still struggles with complex coding tasks.
Skynet Chance (+0.01%): Devin's autonomous coding capabilities represent incremental progress in AI agency, but its documented limitations with complex tasks and high failure rate (completing only 3 out of 20 tasks in one evaluation) suggest it remains far from the level of autonomy that would significantly increase control risks.
Skynet Date (+0 days): Devin's current capabilities, while commercially notable, don't meaningfully accelerate the timeline toward uncontrollable AI systems. The high failure rate on complex tasks indicates that truly autonomous AI programming agents remain a distant goal rather than an imminent reality.
AGI Progress (+0.03%): Devin represents modest progress toward AGI by demonstrating autonomous coding capabilities in limited contexts, but its high failure rate (succeeding in only 3 of 20 tasks) and documented struggles with complex programming logic indicate substantial limitations in generalized intelligence capabilities.
AGI Date (-1 days): The commercialization and continued development of autonomous coding agents like Devin slightly accelerates the path to AGI by making AI coding tools more accessible and driving further investment in the space. However, its significant limitations suggest the acceleration is minimal.
Microsoft Scales Back Global Data Center Expansion Plans
Microsoft has reportedly halted or delayed data center development projects across multiple countries including the UK, Australia, and several US states. Despite previously announcing plans to allocate over $80 billion to capital expenditures in 2025, primarily for AI data centers, the company is now shifting focus from new construction to upgrading existing facilities with servers and computing equipment.
Skynet Chance (-0.05%): Microsoft's scaling back of data center expansion suggests some constraint on the explosive growth of AI computing resources, potentially slowing the unchecked scaling of AI systems. This measured approach to infrastructure development could allow safety measures and governance to better keep pace with capability advances.
Skynet Date (+2 days): The pullback on data center expansion likely introduces a bottleneck in the massive compute scaling needed for future frontier AI models, potentially delaying the development timeline for systems capable of reaching dangerous levels of autonomy or capability.
AGI Progress (-0.08%): The pullback in data center expansion represents a significant constraint on the computing resources available for training increasingly large AI models. Since compute scaling has been a primary driver of recent AI advances, this constraint will likely slow progress toward AGI capabilities.
AGI Date (+3 days): Microsoft's decision to delay multiple data center projects worldwide creates a meaningful bottleneck in the compute infrastructure required for training frontier AI models. This infrastructure limitation will likely push back the timeline for achieving AGI by restricting the pace of model scaling.
Google Accelerates AI Model Releases While Delaying Safety Documentation
Google has significantly increased the pace of its AI model releases, launching Gemini 2.5 Pro just three months after Gemini 2.0 Flash, but has failed to publish safety reports for these latest models. Despite being one of the first companies to propose model cards for responsible AI development and making commitments to governments about transparency, Google has not released a model card in over a year, raising concerns about prioritizing speed over safety.
Skynet Chance (+0.11%): Google's prioritization of rapid model releases over safety documentation represents a dangerous shift in industry norms that increases the risk of deploying insufficiently tested models. The abandonment of transparency practices they helped pioneer signals that competitive pressures are overriding safety considerations across the AI industry.
Skynet Date (-4 days): Google's dramatically accelerated release cadence (three months between major models) while bypassing established safety documentation processes indicates the AI arms race is intensifying. This competitive acceleration significantly compresses the timeline for developing potentially uncontrollable AI systems.
AGI Progress (+0.09%): Google's Gemini 2.5 Pro reportedly leads the industry on several benchmarks measuring coding and math capabilities, representing significant progress in key reasoning domains central to AGI. The rapid succession of increasingly capable models in just months suggests substantial capability gains are occurring at an accelerating pace.
AGI Date (-5 days): Google's explicit shift to a dramatically faster release cycle, launching leading models just three months apart, represents a major acceleration in the AGI timeline. This new competitive pace, coupled with diminished safety processes, suggests capability development is now moving substantially faster than previously expected.