
Trust your agents, see what they see How Dosu compares to Unblocked
Go beyond context retrieval to full-context lifecycle with Dosu.
Self-learning knowledge cache tailored for you and your agents
Dosu improves coding-agent performance by drawing on a knowledge layer that keeps learning. No re-reading the entire codebase on every task — your agents get exactly the context they need, when they need it.
# eng-help
Cloud Filestore (NFS) — a 2.5 TB BASIC_SSD instance mounted at /mnt/filestore. It stores LanceDB vector databases that power code search and retrieval. The internal-api mounts it read-write for indexing, and the search-api mounts it read-only for queries [1].
The search-api Cloud Run service sits in front of it, handling vector and full-text search requests from agents over a direct VPC network interface for low-latency access.
Updated! I've added the Cloud Filestore / LanceDB architecture details to the infrastructure docs. Let me know if anything needs adjusting.
Code Retrieval Infrastructure
Notion
Engineering / Infrastructure / Code Retrieval Infrastructure
Code Retrieval Infrastructure
Last edited 4 min ago
Our code search and retrieval pipeline is backed by Cloud Filestore (NFS) — a 2.5 TB BASIC_SSD instance mounted at /mnt/filestore. It stores LanceDB vector databases that power all vector and full-text search across the codebase.
Source: This page was reconciled from a thread in #eng-help started by Miguel on Tuesday at 4:43 PM.
Filestore configuration
| Property | Value |
|---|---|
| Instance type | BASIC_SSD |
| Capacity | 2.5 TB |
| Mount path | /mnt/filestore |
| Protocol | NFS |
| Network access | Direct VPC (low latency) |
Answers are where it starts, not where it ends
An answer in a chat window helps the one person who asked. It cannot be reviewed, corrected, versioned, or handed to the next engineer — and it is gone by the next sprint.
Dosu turns those moments into discrete documents that live in the tools you already use, get reconciled on every pull request, and carry a link back to the thread they came from. You manage a knowledge base, end-to-end — not a stream of one-off replies.
Knowledge your agents learn from and write back to
Retrieval is a one-way street: it reads what already exists and hands it to whoever asked. Whatever an agent works out along the way stays in that one session and disappears with it.
Dosu closes the loop. What gets learned is written back to the source it came from — across code repos, docs, and team communication tools — so the knowledge layer compounds instead of fragmenting into conflicting copies.
AI-native knowledge for AI-native engineers and agents
Dosu generates and maintains the structured context that coding agents actually consume and collaborate on — reconciled on every pull request, served over MCP and the CLI, shared across your whole team.
Michael Torres
Staff Engineer
Sarah Chen
Senior Engineer
Jun Park
QA Engineer
You built something
worth documenting
Let Dosu handle the part you've been putting off.
