back_office_ops · saas · workflow
Dust builds synthetic filesystem navigation tools enabling AI agents to traverse company knowledge like a Unix filesystem
Dust's AI agents had no way to navigate company data by structure or hierarchy — they could only perform semantic search. When agents needed to locate a specific file by name or browse a folder's contents, they invented path-like query syntax as a workaround.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User query triggers agent
A user asks the agent a question about content in a specific section of company knowledge.
Tools used
listfindcatsearchlocate_in_tree
Outcome
Dust shipped five Unix-inspired filesystem commands (list, find, cat, search, locate_in_tree), now live as 'Advanced Search' in the Agent Builder, enabling agents to navigate organizational data as fluently as a Unix expert navigates a filesystem.
What failed first
Semantic search alone was insufficient when agents needed structure-based navigation — locating a specific entry in a meetings database by position rather than meaning cannot be reduced to a semantic query.
Grounding & classification
Source type: technical build writeup
19 fields verified against source quotes, 1 dropped as unverifiable.
agentic workflowenterprise searchknowledge searchragknowledge basebuilder submittedproduction runtime claimedtools describedworkflow describedsoftwareemployee productivitytechnical build writeupback office opsagentic task executionrag answering