AI/ML Engineering Knowledge Base — Overview

Evolving synthesis of everything in the wiki. Updated by wiki-ingest when sources shift the understanding.

Current Understanding

This knowledge base contains 220 pages spanning the full stack of modern AI/ML engineering. The strongest concentration is in AI Agents (85 pages), covering multi-agent orchestration, agent harnesses and launchpads, memory systems, and trading agents — reflecting the rapid maturation of agentic architectures in 2026. The AI Coding section (51 pages) documents the emerging ecosystem of AI-powered coding assistants (Claude Code, Codex, Cursor, Aider) and the workflows that surround them.

Dev Tools (30 pages) and AI Models (23 pages) round out the technical core, covering CLI tooling, MCP servers, container infrastructure, and the latest model releases from OpenAI, Anthropic, Google, and open-source providers. The Productivity and Multimedia sections capture adjacent domains — workflow optimization, speech AI, and creative tools — while Mobile AI and Personal Knowledge Base represent emerging frontier areas with focused but growing coverage.

The wiki is heavily oriented toward practical, tool-centric knowledge: specific GitHub repos, configuration patterns, and real-world workflows rather than theoretical foundations. Tags like mcp, claude-code, and openclaw dominate, indicating a practitioner’s perspective focused on building and deploying AI systems.

Key Themes

MCP (Model Context Protocol): The dominant integration pattern — appears across agents, coding, and tools
AI Coding Assistants: Claude Code, Codex, Cursor, Aider and the agentic coding revolution
Multi-Agent Orchestration: Coordinating multiple AI agents in workflows and platforms
Local AI & Privacy: Self-hosted models, on-device inference, and privacy-preserving architectures
Agent Harnesses & Launchpads: Wrappers, dashboards, and management platforms for AI agents
CLI-First Tooling: Command-line tools and automation scripts for AI workflows
Open Source Ecosystem: Community-driven tools, repos, and frameworks
Speech & Multimedia AI: Voice cloning, TTS/STT, and creative AI applications

Category Distribution

Category	Pages	Key Topics
AI Agents	85	claude-code, multi-agent, mcp, automation, openclaw
AI Coding	51	claude-code, cli, automation, anthropic, codex
AI Models	23	llm, local-ai, macos, research, ollama, exo
Dev Tools	30	github, trending, cli, daily, security, python
Productivity	10	macos, speech-ai, stt, notion, meeting
Multimedia	6	speech-ai, stt, cloning, elevenlabs-alternative, microsoft, asr
Mobile AI	2	ios, reverse-engineering, decompiler, security-analysis, mach-o, redyne
Misc	13	openclaw, karpathy, research, ai-trading, autonomous, hyperliquid

Open Questions

Mobile AI coverage is thin (1 page) — needs expansion as on-device inference grows
Personal Knowledge Base has a single page — opportunity to document more PKB/Memex patterns
AI Safety & Evaluation — limited dedicated coverage of benchmarks, evals, and alignment
Data Engineering for AI — no dedicated pages on RAG pipelines, vector DBs, or data prep workflows
MLOps / Deployment — missing coverage of model serving, monitoring, and production infrastructure
2 pages have no tags — need categorization pass

Key Entities / Concepts

Top concepts by tag frequency and cross-reference:

claude-code (66 pages)
multi-agent (22 pages)
llm (21 pages)
openclaw (19 pages)
mcp (16 pages)
macos (15 pages)
anthropic (12 pages)
github (11 pages)

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Overview