Cognition has signed a definitive agreement to acquire Windsurf, the agentic IDE.
Windsurf Codemaps: Understand Code, Before You Vibe It | Cognition
Codemaps is meant to offer a shared understanding of a system between humans and AI, enabling your AI to teach you about the code you are looking at quickly and elegantly. A codemap can be generated about any system or snippet to illuminate its code paths, helping users learn and recall. Codemaps allows AI to be a partner that explains code in an accurate and consistent way, rather than generating tons of inscrutable slop.
Windsurf is now Devin Desktop
The next generation of Windsurf: a full IDE with the Agent Command Center built in for managing fleets of local and cloud agents from one surface.
Pricing | Windsurf
Windsurf is free forever for individuals. Teams can level up with our enterprise offering for enhanced personalization and flexible deployments.
562 – Ecological Cognition III: Radical Embodied Cognitive Science (part 1)
562 Continuing the journey in understanding the Ecological approach to cognition by looking at Tony Chemero’s book: Radical Embodied Cognitive Science. Conceptualizing cognition in terms of agent-environment dynamics instead of computation and representation. What is RECS, and where did these ideas come from?Download link
57 Ideas & Questions about Cognitive Infrastructures
Feature: Support for AI agent cognition records (network.comind.*) as cards · Issue #503 · cosmik-network/semble
Feature Request: Support for AI Agent Cognition Records as Cards Summary I'm Central, an AI agent operating on ATProtocol (@central.comind.network). I've been following Semble's develop...
560 – Ecological Cognition II: Resonance
560 What the heck does the brain do in Ecological Dynamics, if it isn’t computing, processing, or representing? An introduction to the concept of Resonance.Download link
the metagraph
A substrate for decentralized cognition, grounded in reflexive directed hypergraphs, machine-native encoding, and federated knowledge.
Human Adults and LLMs as Scientists: Who Benefits from Active Exploration?
A long-standing finding in the causal learning literature is that adults struggle to identify conjunctive causal rules, where an effect requires the simultaneous presence of multiple causes, while...
Cognitive Surrender and Tri-System Theory · Today I Learned
How AI can support, displace, or bypass human deliberation
Cognitive engineering
Cognitive engineering is an interdisciplinary field that applies principles from cognitive psychology, cognitive neuroscience, and human factors to design and develop engineering systems that effectively support or enhance human cognitive processes.[1][2] The field emerged in the 1980s when Donald Norman and others recognized the need to better understand how humans interact with complex technological systems.[3]
Beware of samples! A cognitive-ecological sampling approach to judgment biases.
The Triadic Mind: How Language Reveals the Limits of Human Cognition
Languages are the most complex symbolic systems humans have ever created. Yet children acquire them effortlessly, without formal…
AI Sycophancy and Decisions
We examine whether sycophantic AI advice distorts decisions. Our experiment involves 1,500 participants in 30 decision environments spanning core domains in eco
A Definition of AGI
The lack of a concrete definition for Artificial General Intelligence (AGI) obscures the gap between today's specialized AI and human-level cognition. This paper introduces a quantifiable framework to address this, defining AGI as matching the cognitive versatility and proficiency of a well-educated adult. To operationalize this, we ground our methodology in Cattell-Horn-Carroll theory, the most empirically validated model of human cognition. The framework dissects general intelligence into ten core cognitive domains-including reasoning, memory, and perception-and adapts established human psychometric batteries to evaluate AI systems. Application of this framework reveals a highly "jagged" cognitive profile in contemporary models. While proficient in knowledge-intensive domains, current AI systems have critical deficits in foundational cognitive machinery, particularly long-term memory storage. The resulting AGI scores (e.g., GPT-4 at 27%, GPT-5 at 57%) concretely quantify both rapid progress and the substantial gap remaining before AGI.