ALL MAPS
AI Agents
Building blocks, patterns and frameworks for autonomous AI systems
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AI Coding Assistants
IDE plugins, agentic IDEs and CLI agents for developers
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Proprietary Models
AI labs and their flagship model families
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Open Source / Weights Models
Organizations releasing open-weights models and their flagship releases
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Cloud Managed AI
AWS, Google Cloud, Azure and Cloudflare AI platforms compared
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Dense vs MoE
How Dense and Mixture-of-Experts architectures process a token
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Quantization — Memory by Format
How numerical precision (FP32 → INT4) affects a 70B model's memory footprint
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RAG
Pipeline stages, components and tools for Retrieval-Augmented Generation
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DEEP DIVES
LLMs Are Not Truth Machines
Why asking an LLM for ground truth is the wrong mental model — and what RAG does instead.
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Use Case — Chat LLM (ChatGPT-like)
How a Chat LLM works end-to-end: prompt construction, optional RAG, inference, token generation, and the key mental models to avoid common mistakes.
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Use Case: Knowledge Search for Analysts
How a business analyst queries private document corpora with AI — architecture, governance, and practical trade-offs.
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Use Case: Agentic Coding
How an AI agent assists a developer beyond autocomplete — planning, editing, running tests, and iterating autonomously.
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Use Case: Ops Workflow Automation
How autonomous agents handle multi-step operational processes — incident triage, pipeline orchestration, and the human-in-the-loop model.
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MCP: The Standard for Connecting AI to Everything
What MCP is, how it works architecturally, and why it matters for AI agent development.
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RAG: Retrieval-Augmented Generation
How RAG works, when to use it, and trade-offs vs fine-tuning.
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REFLECTION
Meta-Reasoning: Teaching AI Agents to Know When They're Stuck
A 2026 study shows that agents capable of monitoring their own reasoning and switching strategies outperform standard agents by 31% — with open-source models benefiting the most.
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"Stop the Denial" — Laurent Alexandre on AI at the French National Assembly
Laurent Alexandre argues before the French National Assembly that AI already surpasses experts on cognitive tasks — and that downplaying it is a strategic mistake.
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Co-Intelligence: Living and Working with AI
Key lessons from Ethan Mollick's book on AI as a collaborative partner — practical frameworks for work, creativity and education.
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