25 verified solution paths
Start from the symptom you are seeing and trace it to evidence, mechanism, chapter and repository diagnostic.
Find a solution →Read complete books on the web, understand the mechanisms from first principles, and apply them to real code through verified solutions and AI diagnostics.
Programmer.ie is organized around books rather than publication dates. Each book is available as a structured web edition now, with ebook and video editions built from the same source.
Evidence, distributed execution, reliability, authority, durable workflows, replay, security, verification and explicit control planes.
Read 46 chapters → 10 Agent systemsPlanning, structured actions, tools, state, memory, search, revision and external verification assembled into a working agent architecture.
Read 10 chapters → 59 Simulation and artificial lifeCells, elementary rules, simulation, quantitative behavior analysis, rule-space search, continuous artificial life, Lenia, neural cellular automata and reproducible experimental tooling built as executable Python systems.
Read 59 chapters → 01 Digital life and artificial lifeAn evidence-first exploration of emergence, persistence, computation, artificial life, learning, inheritance, evolution and cumulative improvement in computational systems.
Read 1 chapters → 09 Model architectureScorers, value functions, policies, hierarchical state, recursive compute and model selection through explicit architectural decomposition.
Read 9 chapters → 11 FoundationsTensors, autograd, neural networks, data pipelines, attention, training diagnostics and a small language model from first principles.
Read 11 chapters →The books explain the mechanisms. The solution library turns those mechanisms into problem-first diagnostics, and the AI prompts let you apply them directly to your own repository.
Start from the symptom you are seeing and trace it to evidence, mechanism, chapter and repository diagnostic.
Find a solution →Every book remains fully navigable as a free web learning path with chapter progress and connected application material.
Open learning paths →Evidence-driven repository prompts turn the material into audits for PyTorch, model design, agents and production AI systems.
Browse AI prompts →Cellular Automata From First Principles 58: Capstone — Discover, Measure and Explain a New System The book began with one tiny rule applied to one tiny neighborhood. We end with a …
Read →Cellular Automata From First Principles 57: Build a Cellular Automata Laboratory We now have enough pieces to stop thinking in terms of isolated scripts. A useful cellular-automata …
Read →Cellular Automata From First Principles 56: Generate Figures and Animations Cellular automata are visual systems. That makes figures and animations unusually important. But a …
Read →Cellular Automata From First Principles 55: Run Parameter Sweeps and Benchmarks Once experiments are reproducible, we can stop treating parameters as one-off choices and start …
Read →Cellular Automata From First Principles 54: Make Experiments Reproducible By this stage the book contains many systems whose behavior depends on parameters, seeds and …
Read →Cellular Automata From First Principles 53: Build a Reusable Cellular Automata Engine Across this book we repeatedly rebuilt the same pieces: state neighborhood rule step loop …
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