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Companies and agents alike are organizing around world models instead of hierarchies and pipelines. A world model isn't a pile of context, and it isn't a smarter archive. A world model is a living set of beliefs about reality — what the system thinks is true, why, how confident, what contradicts it, and what would change its mind.

Beliefs are the operational core of a world model: claims with confidence, evidence, and lifecycle. They are how the model stays accurate as reality changes.

1npm i beliefs

1import Beliefs from 'beliefs'
2
3const beliefs = new Beliefs({
4  apiKey: process.env.BELIEFS_KEY,
5  namespace: 'my-project',
6  writeScope: 'space',
7})
8
9// Before the agent acts — read current understanding
10const context = await beliefs.before(userMessage)
11
12// Run your agent with belief context injected
13const result = await myAgent.run({ system: context.prompt })
14
15// Feed the output — beliefs extracted, conflicts detected, state updated
16const delta = await beliefs.after(result.text)

That's the loop. Three calls per turn, regardless of which framework you ship on.

Works with your stack

1import { beliefsHooks } from 'beliefs/claude-agent-sdk'   // Anthropic Claude Agent SDK
2import { beliefsMiddleware } from 'beliefs/vercel-ai'     // Vercel AI SDK
3// React hooks + browser DevTools — coming soon

Or call beliefs.before() / beliefs.after() manually around any LLM (OpenAI, plain fetch, your own agent loop). See the Hack Guide for working recipes across frameworks.

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Why coding agents first

A codebase is already a compact world. It has laws (types, invariants), assumptions (architecture decisions, dependencies), history (commits, PRs), ownership, and contradictions (stale docs, drifted assumptions). Coding agents are already operating inside this world — but with short-lived context and weak memory.

The first world model thinkⁿ targets is the one your coding agent already lives in. Concrete beliefs the engine can hold for a repo:

1belief:    Authentication is enforced at the API middleware layer
2confidence: 0.82
3evidence:   middleware.ts, auth.test.ts, architecture.md
4contradicts: /api/internal/export bypasses middleware
5next move:  inspect route-level auth coverage before modifying export flow

The same machinery applies to research agents (claims about a market), analyst agents (beliefs about a customer or portfolio), or any system that needs to maintain a coherent picture of reality across many turns and many sources.