How to build company context with Ambience.
Published 2026-06-07 - 12 min read
A practical guide to building company context for AI agents: source-linked memories from calls, tickets, PRs, docs, Slack threads, and agent sessions. This is the practical playbook for going from cold agents to a shared context harness your team can trust.
Company context is not a transcript archive or a wiki dump. It is the current, source-linked, permissioned memory an agent needs before it acts.
- Capture decisions, patterns, skills, conventions, failures, and references instead of saving whole transcripts.
- Attach source, scope, type, redaction status, and audit evidence to every durable memory.
- Use the agent connections people already approved to propose memories, then ask what should be included before seeding Ambience.
What you are building
Company context is the governed memory layer between approved AI agents and the work a business has already done. It tells an agent what the team decided, what constraints matter, which conventions are current, and where the evidence lives.
Ambience gives that context a working form: typed memories, source links, redaction before storage, personal/team/project/org and sensitive scopes, conflict review, and audit. The result is not a new wiki. It is the context harness agents use before, during, and after real work.
Source-linked
Permissioned
Reusable
Start with sources your agents already reach
The fastest path is not asking every company to connect every app directly to Ambience on day one. Most people already run agents with approved access to Granola, Linear, GitHub, Slack, Google Docs, Notion, local repositories, or files on their machine.
Ambience can use that approved agent access to run a permissioned app sweep: inspect what is available, show the candidate sources, ask what should be included, then propose source-linked memories for review.
Granola
Meeting notes
Decision: launch onboarding uses permissioned app sweep.
Project
Linear
Issues and roadmap
Constraint: desktop routing must keep localhost preview stable.
Project
GitHub
PRs and repo
Convention: expose new workflows through UI, MCP, and CLI.
Team
Slack
Threads via agent access
Pattern: save only durable decisions, not chat history.
Team
Choose the first durable memories
A durable memory should change future work. It should help an agent avoid a bad assumption, follow the team's current convention, or find the right source without rereading a whole transcript.
Decision
A choice the team should follow later.
Meeting discussion that never resolved.
Convention
How the team likes work to be done.
One person's temporary preference.
Pattern
A reusable implementation or operating approach.
A one-off status update.
Failure
A mistake worth avoiding next time.
Blame, venting, or unresolved frustration.
Skill
A repeatable workflow an agent can perform.
A task that still needs human judgement only.
Reference
A source future agents should consult.
A large document saved without a reason.
Attach source, scope, and type
A memory becomes trustworthy when it carries its provenance. This is the difference between "the agent remembered something" and "the team can see why this context exists."
Use a permissioned app sweep during onboarding
When a user installs Ambience, the agent inspects available MCPs and local sources, shows candidate apps, and asks what may be included before proposing memories.
Granola call: onboarding review, June 2026.
Redact before storage
The safe boundary is before persistence. Secrets, credentials, private customer data, and unnecessary personal details should be stripped before a memory becomes durable company context.
Source link
Every accepted memory points back to the call, issue, PR, doc, thread, or session that produced it.
Scope
Personal, team, project, org, and sensitive scopes decide who can retrieve the memory.
Redaction
Secrets, credentials, private customer data, and unnecessary personal details are removed before storage.
Audit
Reads, writes, access changes, redaction outcomes, and conflict decisions become visible events.
Seed the first context set
Pick one active project, one team, and one recent week of work. Ask the agent to propose 10 to 20 candidate memories from the approved sources, grouped by type and scope.
Granola call -> product decision
Linear issue -> delivery constraint
GitHub PR -> engineering convention
Slack thread -> team operating rule
Google Doc -> reference memory
Agent session -> failure or pattern
Teach agents how to use it
The context only compounds if agents read and write it during real work. At session start, load relevant Ambience memories. During work, search Ambience before making decisions. At the end, save durable takeaways with source, type, scope, and redaction state.
The operating loop is simple: read context, do the work, save only what should survive.
Run a weekly context review
A weekly review keeps company context healthy. Resolve conflicts, remove stale memories, promote personal notes that became team practice, narrow over-broad scopes, and turn repeated workflows into skills.
The review should be short and evidence-based. If a memory cannot name its source, owner, or current scope, it should be corrected before agents depend on it.
Measure the compounding effect
The right metrics are practical: how often agents reuse source-linked decisions, how many repeated questions disappear, how many onboarding tasks start with the right project context, and whether risky memories were redacted or scoped correctly.
Source-linked decisions reused
Repeated questions avoided
Risky memories scoped or redacted
A 90-minute setup plan
0-15 min
Install Ambience
Connect the agent runtime and confirm the user can view the memory dashboard.
15-35 min
Review available sources
Let the agent inspect approved MCPs and local sources, then choose which apps are allowed for the first sweep.
35-60 min
Approve candidate memories
Accept only the decisions, conventions, patterns, failures, skills, and references that will help future work.
60-75 min
Run one agent task
Start a real session with the seeded context and verify the agent uses the right project decisions.
75-90 min
Review proof
Check source links, scopes, redaction status, and audit rows before expanding the sweep.