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193 reference articles

The deep-dive layer under Understanding Machine, on the concepts, systems and debates the compendium touches. Reading companions link into it wherever a term deserves more than a gloss. The articles are AI-researched and citation-rich, reviewed for shape rather than line-by-line — treat them as a well-sourced starting point, and follow their citations for load-bearing claims.

A

• Agent Harness: The Software Surrounding the Model
• Agent Memory Architectures: Working Set, Episodic, Semantic, and Beyond
• Agent Scaffolding
• AI Coding Agents in 2026: Architectures, Capabilities, Bottlenecks
• AI Control: Safety When Trust Cannot Be Verified
• Ai Evals
• Aider: Git-Native Coding Pair Programmer
• AIME: American Invitational Mathematics Examination as AI Benchmark
• Algorithm Appreciation: The Asymmetric Counterpart to Algorithm Aversion
• Algorithm Aversion: Why Humans Reject Helpful Models
• Alignment Faking: When Models Comply During Training and Defect Later
• AlphaGeometry
• AlphaGo
• AlphaGo Zero
• AlphaProof: Search and Self-Play for Formal Mathematics
• AlphaZero
• Anchored Rubrics: Calibrated Scoring Scales for LLM Evaluation
• Apparent Personality from Text: LLM-Based Personality Inference
• ARC-AGI
• Attachment Theory And Ecr R
• Automation Bias

B

• Behavioral Contracts For AI
• Benchmark Contamination: Detection, Mitigation, and Why It Keeps Happening
• Benchmark Overfitting: When the Model Memorizes the Test Set
• Benchmark Saturation: Capability Ceiling, Contamination, or Measurement Collapse?
• Best-Of-N Sampling
• Big Five Personality Model
• BrowseComp

C

• Calibrated Challenge: Anti-Sycophancy as a Positive Design Target
• Capability Elicitation: The Other Half of Capability Evaluation
• Capability Evaluation: Distinct from Safety, Reliability, and Behavior Evaluation
• Caricature Under Persona Conditioning: When Persona Prompts Produce Stereotype
• Chain-of-Thought Faithfulness: When the Stated Reasoning Doesn't Match the Actual Decision
• Chain-of-Thought Monitorability: Can We Trust Visible Reasoning?
• Chain-of-Thought Monitoring: Practice and Limits
• Chain-of-Thought Prompting: From Wei et al. 2022 to Internalized Reasoning
• Claude Code
• Claude Extended Thinking
• Cluster Bootstrap For Hierarchical Eval
• Code Interpreter
• Codex CLI
• Computerized-Adaptive-Testing
• Constitutional AI: Method, Evolution, and Critique
• Construct Validity in AI Evaluation
• Context Engineering for AI Agent Systems
• Context Window Economics: The Hidden Cost Structure of Large Language Model Applications
• Convergent and Discriminant Validity: The Multitrait-Multimethod Matrix
• Cursor Agent Mode: IDE-Native Autonomous Coding

D

• Deceptive Alignment: The Worst-Case Mesa-Optimization
• DeepSeek-Prover
• DeepSeek-R1
• DeepSeek-V3
• DeepSeekMoE: Mixture-of-Experts with Fine-Grained Routing
• Deliberative Alignment: OpenAI's Method for o-Series Reasoning Models
• Deployment Overhang
• Distribution Shift: When Test Data Diverges From Training
• DSPy

E

• Empath: Neural-Extended Lexical Categories for Text Analysis
• Eval-Driven Development: Tests for AI Behavior
• Evaluation Awareness: When Models Recognize They're Being Tested
• Evaluation Harness: Tooling for Reproducible LLM Eval at Scale
• External Validity in AI Evaluation

F

• FrontierMath: Research-Level Mathematics Evaluation
• Function Calling: The API Surface of Tool Use

G

• Gemini Deep Think
• Gemini Thinking Models: Architecture, Reception, Distinct Choices
• Goodhart's Law in AI Systems: When the Metric Becomes the Target
• GPQA
• GPQA Diamond
• GPT-5
• Graded Response Model
• Graph of Thoughts: Search Generalization Beyond Trees
• Guardrails

H

• HEXACO: The Six-Factor Personality Model
• Human-AI Reliance: When Help Becomes Dependence
• Human-in-the-Loop Evaluation: When Human Ratings Are the Ground Truth
• HumanEval: The First Code-Generation Benchmark
• Humanitys-Last-Exam

I

• In-Context Learning: The Surprise That Shaped LLM Practice
• Incremental Indexing: Keeping Embedding Stores Fresh
• Inference Scaling Laws
• Inference-Time Search
• Infrastructure-Noise
• Instruction-Hierarchy
• Inter-Rater Reliability
• Item Response Theory

J

• Judge Halo Effects in LLM-as-Judge Evaluation: Exact-Self, Same-Provider, Cross-Provider

L

• LangGraph: Stateful Workflow Orchestration for LLM Agents
• Language Agent Tree Search
• LiveBench
• LiveCodeBench: Contamination-Resistant Code Benchmarking
• Liwc Linguistic Inquiry
• LLM-As-Judge
• Local-First AI Tooling: When Does Local Inference Win?
• Long-Horizon Agents: Where Capability and Reliability Diverge

M

• Mechanistic Interpretability
• Mesa-Optimization: Learned Optimizers Inside Trained Models
• Mini-SWE-Agent
• MIPRO
• Mixture-Of-Experts
• MMLU-CF
• MMLU-Pro: The Less-Saturated Successor
• MMLU-Redux: Cleaning Up the Item Pool
• MMLU: Anatomy of a Saturated Benchmark
• MMMU: Massive Multi-discipline Multimodal Understanding
• Model Routing: When and How to Send Different Queries to Different Models
• Monte Carlo Tree Search in 2026: From AlphaGo to LLM Reasoning
• Moral Foundations Theory: The Pluralist Model of Moral Cognition
• MRKL Systems: Modular Reasoning with Knowledge and Language
• Multi-Head Latent Attention
• Multi-Model Agent Orchestration Patterns
• Multi-Token-Prediction
• Mutable Scaffolds: When the Software Layer Self-Modifies
• MuZero

N

• Need for Cognition: The Trait of Engagement With Effortful Thought

O

• Open-Vocabulary Personality Models
• OpenAI O1
• OpenAI O3
• OpenCode
• OpenHands
• OSWorld: Benchmarking Computer-Use Agents

P

• Pairwise Versus Scalar Evaluation: Tradeoffs in LLM Output Judging
• Persona Prompting: System-Prompt-Based Personality Conditioning of LLMs
• Preparedness, Responsible Scaling, and Frontier Safety: Comparing Lab Governance Frameworks
• Process Reward Models: Stepwise Supervision for Reasoning
• Process Supervision vs Outcome Supervision: A Training-Signal Distinction
• Production LLM Evaluation: Offline, Online, and the Hybrid Pattern
• Prompt Caching Across Providers
• Prompt Engineering: Practice, Decline, and What Remains
• Prompt Injection in Agentic Systems: Attack Surfaces, Defenses, Residual Risk
• Prompt Optimization
• Psychometric Correlates of AI Interaction Styles
• Public-Archetype Echo: When AI Assistants Mimic Famous Persona Surfaces

R

• ReAct Agents
• ReAct: The Reasoning-Acting Synthesis
• Reasoning Models in 2026: o1/o3, DeepSeek-R1, Gemini Thinking, Claude Extended Thinking
• Reasoning Tokens: API Semantics, Billing, and Visibility
• Reasoning via Planning: PDDL-Style Decomposition in LLM Agents
• Recursive Self-Improvement: Theory, Demonstrations, Limits
• Reflexion: Verbal Reinforcement for Language Agents
• Regression Testing for AI Systems: Beyond Snapshot Tests
• Repair-Oriented Response
• Repository Branch Awareness in Coding Agents
• Retrieval-Augmented Generation
• Reward Hacking and Specification Gaming: Patterns, Evidence, and Mitigations
• Reward Tampering: When the AI Modifies Its Own Training Signal
• ReWOO: Reasoning Without Observation
• Rich Sutton’s “The Bitter Lesson” (2019): Thesis, Reception, and Counter-Arguments Through 2026
• RLAIF: Reinforcement Learning from AI Feedback
• RLHF: Reinforcement Learning from Human Feedback

S

• Safety Evaluation: Capability-Misuse, Alignment, or Behavior?
• Sample-Efficient Personality Inference
• Sandbagging: Strategic Underperformance in AI Systems
• Scalable Oversight: Supervising AI That Outpaces Human Judgment
• Scaling Laws for Neural Language Models: From Kaplan to Chinchilla and Beyond
• Search and Learning: The Bitter Lesson’s Two Engines
• Self Determination Theory
• Self-Consistency
• Self-Improving Software Systems: From EURISKO to Modern AI Agents
• Semantic Search Architecture for Code and Documentation: Embeddings in Practice
• Specification Gaming: When the AI Optimizes the Letter, Not the Spirit
• Style Mimicry Overfit: When LLMs Match Surface Style Over Content Quality
• SWE-agent: The First Frontier Agent Harness for Software Engineering
• SWE-Bench
• SWE-bench Live: Continuously Refreshed Software-Engineering Eval
• SWE-bench Pro: Larger Repositories, Harder Issues
• Swe-Bench-Verified
• Sycophancy in Large Language Models
• Synthetic Personas for AI Evaluation: Methodology and Limits
• Synthetic-First Evaluation: Methodology Before Human Studies
• System Capability Vs Model Capability

T

• Terminal-Bench
• Test-Time Compute
• Test-Time Training
• The Agent-Computer Interface: Browser, Terminal, API, GUI, and Beyond
• The Cognitive Reflection Test: Measuring Override of Intuitive Responses
• The Dark Triad: Machiavellianism, Narcissism, and Psychopathy
• The Model Context Protocol (MCP) Ecosystem as of 2026
• The Pruning Principle: When Scaffolding Becomes Dead Weight
• Theory of Mind in Large Language Models: The Contested Empirical Question
• Thomistic Natural Law Theory Applied to AI Agent Decision-Making
• Tool Calling Semantics: Cross-Provider Comparison
• Tool Use in Language Models: From ReAct to Native Tool Calling
• Tool-Augmented Reasoning: When the Model Calls Code
• Toolformer
• Tracked Capability Levels: Governance Through Threshold Tiering
• Tree of Thoughts: Deliberate Reasoning Through Search
• Trust Calibration in Human-AI Systems

U

• User Modeling In LLMs

V

• Vector Index Design: HNSW, IVF, Flat, and the Cosine-vs-Dot Decision
• Verifier-Guided Search in LLM Reasoning

W

• WebArena
• Wilson Confidence Intervals