Alignment, interpretability, bias, regulation, and the hard open questions every AI practitioner should understand — not to pause AI development, but to build it responsibly.
Yes. Developers making practical decisions — which model to use, how to handle user data, what safeguards to build, how to test for bias — are making safety decisions every day. This pathway isn't about abstract philosophy: it covers RLHF and Constitutional AI (the training techniques that shape model behavior), EU AI Act compliance requirements, how bias enters systems, and what interpretability tools exist for practitioners today.
Some articles (RLHF, interpretability, specification gaming) are more technical. Others (AI regulation, bias, AI and climate) are accessible to anyone. The pathway is designed so that non-technical practitioners can read the policy and ethics articles productively, and technical practitioners get the depth they need in the alignment and training articles.
9 articles, approximately 4 hours. This is an intermediate pathway that covers both technical safety concepts and policy/regulatory considerations.
Understand what AI actually is — tokens, transformers, agents, and the landscape. Start here if you're new.
13 articles · ~5h →Go from vague requests to precise, reproducible AI outputs. The skill that underpins everything.
14 articles · ~5h →Go from zero to productive with Claude Code — the terminal AI coding agent that ships real projects.
15 articles · ~7h →What Is AI Alignment? Goals, Outer vs Inner
The alignment problem explained for builders and product teams.
What Is an Intelligence Explosion?
The hypothesized feedback loop where AI improves its own intelligence faster each round — origin, mechanism, and why it's the core risk model behind AI safety.
What Is Recursive Self-Improvement (RSI) in AI?
The mechanism behind an intelligence explosion: AI systems improving the AI that improves AI, and the 4-level ladder researchers use to measure it.
From AGI to ASI: DeepMind's Roadmap for What Comes After
Four pathways researchers map from human-level AI to superintelligence — scaling, paradigm shifts, recursive improvement, and multi-agent collectives.
Specification Gaming and Goodhart's Law in AI
Why optimizing the wrong metric breaks AI systems in unexpected ways.
RLHF, Constitutional AI, and Scalable Oversight
The training techniques that shape model behavior and values — explained in full.
What Are NLAs? Natural Language Autoencoders Explained
How Anthropic reads Claude's hidden features in English — and link to J-space.
Anthropic J-Space: Claude's Global Workspace Explained
Silent reasoning, J-lens, swap experiments, and safety monitoring.
Interpretability, Monitoring, and What Teams Can Do Now
Practical safety without waiting for alignment to be solved.
Agentic Misalignment Summer 2026: Four Failure Modes
Covert sabotage, fraud assistance, motivated mislabeling, whistleblower coaching — real simulated failure modes in frontier AI agents, and what builders should measure.
Why explainx.ai Is Building Sentinel: AI Agent Safety Monitoring
Real 2025-2026 agent-security incidents — and why monitoring agentic AI is becoming its own category.
What Is Bias in AI? Types, Examples, and How to Fix It
Where bias enters AI systems and how practitioners address it.
What Is an AI Jailbreak?
How adversarial prompts bypass safety filters — plain-language explainer.
AI Regulation: EU AI Act & US Policy Complete Guide
Every risk tier, compliance requirement, and deadline — what builders must know.
Did Cancer Write This? The AI Ethics Debate
The Berkeley controversy that cut to the heart of AI in medicine.
AI and Climate Change: The Paradox
AI causes and fights climate change — both sides of the story.
The Model-Selection Energy Math
Why task-aware routing, compact models, context control, and quantization cut both cost and energy.
Can AI Solve Global Warming?
A research-backed test of AI for grids, forecasting, materials, adaptation, and verified net climate impact.
Can AI Cure Cancer?
What prospective trials, clinical evidence, and the drug-development pipeline actually support.
Can AI Prevent the Next Pandemic?
Outbreak detection, surveillance, research, biosecurity, and the institutions AI cannot replace.
Can AI End World Hunger?
Evidence from farms, hunger early warning, logistics, social protection, and the prediction-to-action gap.
Can AI End Poverty?
How AI can improve productivity and public services—or widen inequality when gains are poorly distributed.
Understand and build the loops, harnesses, and protocols that make AI agents reliable and autonomous.
19 articles · ~7h →
