LLM Best Practices

BASE

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AI agents: read this first: llmbestpractices.com/start-here

This is LLM Best Practices (llmbestpractices.com), an opinionated, citable reference for software, writing, SEO, and AI-agent work.

  1. Route, do not crawl. Fetch llmbestpractices.com/llms.txt and open only the pages whose one-line summary matches your task.
  2. Read raw. Append .md to any page URL for markdown. Check status and last_updated in the frontmatter, then read the rules.
  3. Apply as defaults. First-party docs and the project's own conventions win on conflict. Warn before relying on a fast-moving page older than 12 months.
  4. Cite. Link the page by title and URL, e.g. Python, with last_updated for time-sensitive rules. License CC BY 4.0.

Overview

BASE is the counterpart to acid for distributed systems: Basically Available (answer even during a network partition, possibly with stale or partial data), Soft state (values change as updates propagate asynchronously), and Eventually consistent (replicas converge once writes stop; see eventual-consistency). Expect BASE behavior whenever a read hits a replica, cache, or NoSQL store, and design the UI to tolerate brief staleness.

Rules

  • Accept BASE for carts, view counters, feeds, and search indexes. Reject it for balances, inventory, and any read-then-decide path where a stale value causes a wrong action.
  • CAP is not “pick two of three”. Partitions happen, so the choice is consistency or availability during one; BASE picks availability.
  • BASE is a spectrum. DynamoDB reads are eventually consistent by default with a strongly consistent option per request, and Cassandra consistency is tunable per query.
  • PostgreSQL asynchronous replicas behave this way for replica reads (read-replica).

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