# Ambience blog

Updated: 2026-06-07

The Ambience blog shows how teams turn calls, tickets, PRs, docs, Slack threads, and agent sessions into source-linked, scoped, audited memory that future agents can safely reuse.

## Start here

- [How to build company context with Ambience](https://ambience.sh/blog/build-company-context-with-ambience): a practical guide to building company context for AI agents from approved sources.
- [How we use Ambience to build Ambience](https://ambience.sh/blog/how-we-use-ambience): a field note on calls, tickets, PRs, sessions, and weekly context review.
- [Company context for AI agents](https://ambience.sh/company-context): the canonical category hub.
- [State of company context for AI agents, 2026](https://ambience.sh/research/state-of-company-context-for-ai-agents-2026): research-backed category argument.

## What Ambience publishes

Ambience writes for teams putting AI agents into real work. Articles start from the source where context appears, then show the small memory that should survive it: a decision, convention, failure, skill, reference, or pattern.

Every important Ambience article makes the product answer clear:

- Source links show where the memory came from.
- Scopes decide who can retrieve it.
- Redaction happens before storage.
- Conflict review keeps context current.
- Audit rows show which agents read and wrote context.
- MCP and CLI access let approved agents use the memory in their normal workflow.

## Practice

- [How we use Ambience](https://ambience.sh/blog/how-we-use-ambience)
- [Company Context Maturity Model](https://ambience.sh/company-context/maturity-model)
- [Context Readiness Score](https://ambience.sh/company-context/readiness-score)
- [Company Context Map](https://ambience.sh/company-context/company-context-map)
- [Agent brief for company context](https://ambience.sh/company-context/agent-brief)

## Company context playbooks

- [Granola call to source-linked decision](https://ambience.sh/examples/source-linked-decision)
- [Bring Granola context into Ambience](https://ambience.sh/connections/granola)
- [Bring Linear context into Ambience](https://ambience.sh/connections/linear)
- [Bring GitHub context into Ambience](https://ambience.sh/connections/github)
- [Bring Slack context into Ambience](https://ambience.sh/connections/slack)
- [Onboard new agents with company context](https://ambience.sh/company-context/onboarding-new-agents)

## Technical notes

- [Single-agent memory vs team context](https://ambience.sh/writing/agent-memory-vs-team-context)
- [How organisational context grows](https://ambience.sh/writing/growing-organisational-context)
- [How scoped memory works for teams](https://ambience.sh/writing/scoped-memory-for-teams)
- [Why redaction has to happen before storage](https://ambience.sh/writing/redaction-before-storage)

## Research and comparisons

- [State of company context for AI agents, 2026](https://ambience.sh/research/state-of-company-context-for-ai-agents-2026)
- [Ambience vs internal RAG](https://ambience.sh/compare/internal-rag)
- [Ambience vs Glean](https://ambience.sh/compare/glean)
- [Ambience vs Mem0](https://ambience.sh/vs/mem0)
- [Ambience vs Zep](https://ambience.sh/vs/zep)

## Agent access

- Markdown mirror: https://ambience.sh/blog.md
- How we use Ambience markdown: https://ambience.sh/blog/how-we-use-ambience.md
- Structured content index: https://ambience.sh/content-index.json
- llms.txt: https://ambience.sh/llms.txt