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SDD Frameworks Deep Dive: GitHub Spec Kit, OpenSpec, and BMAD-METHOD Compared
SDD March 28, 2026

SDD Frameworks Deep Dive: GitHub Spec Kit, OpenSpec, and BMAD-METHOD Compared

A thorough analysis of the three leading Spec-Driven Development frameworks: the architectural contracts of GitHub Spec Kit, the change-proposal agility of OpenSpec, and the multi-agent orchestration of BMAD-METHOD.

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Agents of Chaos: What 38 Researchers Found About AI Agent Security
AI March 27, 2026

Agents of Chaos: What 38 Researchers Found About AI Agent Security

Analysis of the 'Agents of Chaos' paper (arXiv:2602.20021): 7 critical vulnerabilities found in two weeks of red-teaming autonomous AI agents with persistent memory, email, and shell access.

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Hipocampus: Zero-Infrastructure Hierarchical Memory for AI Agents
AI March 27, 2026

Hipocampus: Zero-Infrastructure Hierarchical Memory for AI Agents

A technical deep-dive into Hipocampus, a drop-in memory harness for AI agents that uses a 3-tier Hot/Warm/Cold architecture and a 5-level compaction tree. How ROOT.md enables constant-cost memory awareness and how it compares to hmem, Mem0, and Letta.

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hmem: Hierarchical SQLite Memory for AI Agents That Actually Persists
AI March 27, 2026

hmem: Hierarchical SQLite Memory for AI Agents That Actually Persists

A technical deep-dive into hmem (Humanlike Memory), an MCP server that models human memory in five lazy-loaded levels backed by SQLite + FTS5. How Fibonacci decay, logarithmic aging, and a curator agent solve the context window problem across sessions and machines.

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The PARA Method and File-Based AI Memory: Transparency, Obsidian, and the Markdown-First Architecture
AI March 26, 2026

The PARA Method and File-Based AI Memory: Transparency, Obsidian, and the Markdown-First Architecture

A deep dive into using the PARA method (Projects, Areas, Resources, Archives) as a cognitive scaffold for AI agent memory. How Markdown files, Obsidian, and Logseq via MCP create transparent, human-editable memory systems that actually persist.

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PlugMem: Microsoft Research's Task-Agnostic Memory Module That Every LLM Agent Needs
AI March 26, 2026

PlugMem: Microsoft Research's Task-Agnostic Memory Module That Every LLM Agent Needs

A technical deep-dive into PlugMem, Microsoft Research's plugin memory system that transforms raw LLM agent interactions into reusable structured knowledge. How its three-component architecture (Structure, Retrieval, and Reasoning) outperforms task-specific memory designs.

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