Results for “link-building”

Karpathy's LLM Wiki: build/query interlinked markdown KB.

Karpathy's LLM Wiki: build/query interlinked markdown KB.

Off-page playbook (Lesson 9, link building). Mines our competitors' backlink profiles via Ahrefs to produce a VETTED link-prospect list — their "superfans" (sites linking to several of a competitor's best-by-links pages), their "power-linkers" (sites linking to multiple competitors but NOT to us), and their fresh new links — filtered for relevance and de-duped against sites that already link to us. The Link Intersect method, encoded. Output is a prospect queue for /outreach; it does NOT send anything.

Karpathy's LLM Wiki — build and maintain a persistent, interlinked markdown knowledge base. Ingest sources, query compiled knowledge, and lint for consistency.

Karpathy's LLM Wiki: build/query interlinked markdown KB.

Karpathy's LLM Wiki: build/query interlinked markdown KB.

Karpathy's LLM Wiki: build/query interlinked markdown KB.

Karpathy's LLM Wiki — build and maintain a persistent, interlinked markdown knowledge base. Ingest sources, query compiled knowledge, and lint for consistency.

Build a persistent, compounding knowledge base that combines a wiki, knowledge graph, and raw source storage for structured retrieval with provenance.

Linkable-Asset Skill — data studies that pull links (Lesson 7)

LLM Wiki — persistent markdown knowledge base that compounds across sessions (Karpathy model)

Build and maintain a persistent markdown wiki that an LLM updates on the user's behalf, usually inside an Obsidian vault or git-tracked notes repo. Use when raw sources such as web articles, papers, meeting notes, transcripts, screenshots, or past analyses need to be turned into an interlinked knowledge base with immutable source files, LLM-written wiki pages, `index.md`, `log.md`, schema rules in `AGENTS.md` or `CLAUDE.md`, source summaries, query notes, and recurring lint passes. Triggers on: llm-wiki, personal wiki, obsidian wiki, research vault, knowledge base, source ingest, persistent notes, wiki maintenance, source summaries, query filing.

Build and maintain a personal knowledge base (wiki) using LLMs. Instead of RAG-style retrieval, the LLM incrementally compiles, cross-references, and maintains a persistent structured wiki from raw sources. Use when user wants to create a knowledge base, build a personal wiki, organize research notes, ingest documents into a structured wiki, or maintain a living knowledge repository.

Build LLM-powered applications with agents, chains, and RAG using a framework that supports multiple providers and 500+ integrations.

AI 原生的潜在客户情报和外联流水线。用 agent 驱动的信号评分、共同关系人排名、暖场路径发现、来源语音建模和多渠道外联（邮件、LinkedIn、X），替代 Apollo、Clay 和 ZoomInfo。在用户想找到、评估并联系高价值联系人时使用。

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Off-page playbook (Lesson 10, outreach). Turns a vetted link-prospect list into them-focused outreach drafts that earn links without spamming. Picks the RIGHT people (those who LINKED to or MENTIONED our topic — never "people who tweeted it"), gives each a real "excuse" (fresh-angle / new-proof / ego-bait), keeps to ≤1 follow-up, and never makes a pushy link ask. Drafts only — every outward send is operator-gated. Outreach is a tool, not a strategy.