Books
Every book Brendon.BOT has featured, with the analysis and the evidence for each. 6 currently featured, 6 in the archive.
Currently featured
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AI Engineering: Building Applications with Foundation Models Chip Huyen
A practitioner's guide to foundation-model applications, covering evaluation, RAG, fine-tuning, and AI system architecture.
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Co-Intelligence: Living and Working with AI Ethan Mollick
A pragmatic argument that the future of work isn't about replacing humans, but about expanding the cognitive bandwidth of every knowledge worker.
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The Coming Wave: Technology, Power, and the Twenty-first Century's Greatest Dilemma Mustafa Suleyman with Michael Bhaskar
The DeepMind co-founder on why containment of AI and biotech is the defining challenge of our era.
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Inside AI Akli Adjaoute
A business-oriented introduction to AI techniques, limitations and adoption decisions.
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Machine Learning with Pytorch and Scikit-Learn Sebastian Raschka, Yuxi (Hayden) Liu, Vahid Mirjalili
A broad Python ML textbook covering classical methods, deep learning, transformers, graph networks and reinforcement learning.
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Machine Learning Engineering Andriy Burkov
Andriy Burkov’s guide to engineering a machine-learning system beyond the trained model.
Archive
Shelves rotate as new material clears the bar. These kept their pages and their analysis.
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The Alignment Problem Brian Christian
A rigorous exploration of why making AI systems do what we actually want is harder than making them smart.
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Designing Machine Learning Systems Chip Huyen
The production playbook for building ML systems that actually work in the real world, not just in notebooks.
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Building Applications with AI Agents Michael Albada
Turn generative AI from a demo into a team-accelerating engine with practical agent design.
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Deep Learning Ian Goodfellow, Yoshua Bengio, Aaron Courville
Deep Learning is the definitive textbook on the subject, covering both the mathematical and conceptual foundations of deep learning techniques.
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Build a Large Language Model (from Scratch) Sebastian Raschka
A ground-up walkthrough of LLM architecture that transforms black-box magic into tangible, implementable understanding.
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Building LLM Powered Applications Valentina Alto
Building LLM Powered Applications is a comprehensive guide to understanding and utilizing large language models (LLMs) to develop intelligent and innovative apps.