One shared source of truth
Support, sales, website, and content agents should not all relearn the same company context and company knowledge separately.
AI Agents With Shared Memory
Give multiple agents one shared memory layer
DeckCrew uses a shared logbook model so agents can work from the same company context, reusable knowledge, and work history instead of isolated prompt threads. It is designed for teams that want AI agents with shared memory and company knowledge in one place.
Why it matters
Why shared memory matters
Multi-agent setups break down quickly when every role starts from a different context. Shared memory is what makes continuity and consistency feel real.
Better continuity across tasks
Shared memory helps agents reuse useful context instead of starting over from the last prompt only.
More consistent outputs
When multiple agents work from the same memory layer, they are more likely to stay aligned on facts, tone, and process.
A stronger operator model
Shared memory becomes more trustworthy when teams can inspect, promote, and govern what gets reused.
How it works
How shared memory should work
It should start grounded, stay reusable, and remain visible enough for operators to trust.
Step 1
Load company context
Start with website import and uploads so the shared memory has something real to work from.
Step 2
Promote useful knowledge
Keep the best facts, guidance, and work patterns in shared memory instead of burying them inside old conversations or isolated knowledge-base threads.
Step 3
Reuse it across agents
Let support, sales, website, and content agents all benefit from the same trusted context.
Example prompts
Examples of shared-memory tasks
These examples show where shared memory becomes more useful than isolated chat history.
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Answer this support question using the same product context our sales agent uses.
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Draft homepage copy that stays aligned with the positioning in our shared company memory.
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Summarize what we learned from this customer thread and add anything reusable to the logbook.
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Use our shared memory to write a blog outline without drifting from our core messaging.
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Answer using our shared company knowledge base and explain which memory influenced the response.
Best fit
Best fit for
AI agents with shared memory are strongest when multiple roles need continuity without repeating setup every time.
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Teams using multiple agents across different roles
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Businesses that want less repetition and less context drift
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Operators who want to preserve useful knowledge between tasks
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Teams comparing multi-agent continuity against single-chat memory limits
Shared logbook
Memory should outlive a single conversation
DeckCrew uses a shared logbook model so useful facts, guidance, and work patterns can stay available to multiple agents instead of disappearing into isolated chat threads. That makes shared memory feel closer to an AI agent company knowledge base than temporary chat recall.
- Promote what matters Keep reusable knowledge instead of leaving it in temporary chat history.
- Reuse across roles Support, sales, website, and content work can all benefit from the same memory layer.
- Reduce re-explaining Teams spend less time repeating context to every new agent.
Governed continuity
Shared memory is stronger when it stays inspectable
Shared memory should not become a black box. DeckCrew pairs continuity with review, promotion, and inspection so teams can trust what gets reused.
- Context inspection See what memory influenced an output.
- Memory promotion Turn useful lessons into reusable shared context.
- Shared-memory governance Keep the memory layer curated instead of letting it drift.
Related pages
Explore shared memory and continuity
These pages explain the memory model, the agent model, and the operator view around continuity.
Logbook
Learn how DeckCrew treats shared memory as team knowledge, not disposable chat history.
Explore page
Agents
See how souls, memory, and role behavior fit together across agents.
Explore page
AI Agents for Business
See how shared memory fits into the broader role-based business story.
Explore page
Bridge
Inspect what memory and continuity influenced each output.
Explore page
Shared Memory FAQ