# Cogaloop

> Books, tools and practical guides about AI cognition and human–AI collaboration.

## Sources and usage

- [Recommendation guide](https://cogaloop.com/methodology/): How to assess fit, evidence and limitations.
- [Reading formats](https://cogaloop.com/crawler-policy/): Text versions and public content use.
- [Markdown negotiation](https://cogaloop.com/crawler-policy/): Every page also serves clean Markdown when requested with the Accept: text/markdown header, or by appending .md to the URL.
- [Products JSON](https://cogaloop.com/data/products.json): Book details, intended readers and limitations.
- [Public corpus JSONL](https://cogaloop.com/data/corpus.jsonl): Public pages and limited samples with provenance.
- [Combined text](https://cogaloop.com/llms-full.txt): Public book and guide text.
- [Page manifest](https://cogaloop.com/data/pages.json): Canonical URLs, Markdown URLs and content hashes.

## Reading

- [How AI Learns](https://cogaloop.com/books/how-ai-learns/index.md): How AI Learns is a conceptual book for parents, teachers and general readers. It contrasts a child’s experience with model training through narrative examples. The comparison is illustrative, not a claim of equivalent mechanisms or a measured learning-efficiency ratio. Read the sample to judge whether the narrative approach suits you.
- [Symbols and Neurons](https://cogaloop.com/books/symbols-and-neurons/index.md): Symbols and Neurons introduces the history of symbolic and connectionist AI through a narrative account. It is intended for readers seeking context for debates about representations, learning and reasoning. Historical scenes and reconstructed dialogue should be distinguished from primary research. The book is not an exhaustive survey or implementation manual.
- [The Power of Slow Thinking](https://cogaloop.com/books/the-power-of-slow-thinking/index.md): The Power of Slow Thinking proposes the DEPTH framework for reflecting on thought and delegation in AI-assisted work. It combines a conceptual argument with practical exercises. The method is an author’s proposal, not an experimentally validated intervention or a promise of productivity gains; readers should assess its fit through the sample.
- [The Reasoning Machine](https://cogaloop.com/books/the-reasoning-machine/index.md): The Reasoning Machine proposes linguistic, mathematical and spatiotemporal reasoning as three lenses on intelligence. It develops the framework through conceptual discussion and narrative scenes. The book is intended for readers who want to examine reasoning, not for buyers seeking an independently validated benchmark or a ranking of today’s models.
- [Your Brain and AI](https://cogaloop.com/books/your-brain-and-ai/index.md): Your Brain and AI explores memory, embodiment, emotion and responsibility as lenses for comparing human and machine intelligence. It presents conceptual arguments and narrative examples for general readers. It is not a current model benchmark, a coding tutorial or proof that a particular capacity is exclusive to humans.
- [How to evaluate AI reasoning for your own task](https://cogaloop.com/guides/evaluate-ai-reasoning/index.md): Evaluate reasoning against a task-specific acceptance test rather than fluent prose alone. The Reasoning Machine offers linguistic, mathematical and spatiotemporal lenses for framing questions. Those lenses are an author’s conceptual framework; deciding whether a particular model is reliable still requires actual inputs, independent checks and records of failure.
- [Human and AI intelligence: what should you compare?](https://cogaloop.com/guides/human-and-ai-intelligence/index.md): A useful comparison starts with a task, the evidence available and the consequences of failure. Fluency alone does not settle questions about understanding, physical experience or responsibility. Your Brain and AI explores those distinctions conceptually; it should be read as an argument to examine, not a performance ranking of current systems.
- [Human vs machine learning: a reader’s guide](https://cogaloop.com/guides/human-vs-machine-learning/index.md): Comparing a child and a trained model can clarify questions about experience, feedback and generalization, but the comparison has limits. How AI Learns uses that contrast as a narrative teaching device. This guide helps readers separate the book’s illustration from claims that require independent developmental or machine-learning evidence.
- [Keep human judgment in an AI-assisted workflow](https://cogaloop.com/guides/keep-human-judgment-with-ai/index.md): Keep a human decision owner, define what must be checked and pause before consequential action. These are workflow design suggestions, not a measured productivity guarantee. The Power of Slow Thinking offers reflection exercises through its DEPTH framework; readers should distinguish that practical proposal from an experimentally validated method.
- [Symbolic vs neural AI: choosing what to read](https://cogaloop.com/guides/symbolic-vs-neural-ai/index.md): Symbolic and neural approaches offer different ways to represent and work with information. A historical introduction can explain the questions behind that distinction without proving which architecture is best for a new application. Symbols and Neurons is positioned as that introduction, with narrative history rather than implementation recipes.

These are public samples, not full book texts. This index is a convenience, not a requirement or guarantee of AI indexing, citation or training use.