Every task an agent runs is grounded in what your organization already knows: your code, your prior decisions, and your reference material. Retrieved by meaning, cited in the work, and never invented.
Most retrieval systems return text chunks and hope the model figures out the rest. FAFO Memory returns symbols, dependencies, prior decisions, and reference excerpts that an agent can act on directly.
Agents search your codebase by intent, not string match, retrieving whole functions and symbols, and tracing dependencies and blast-radius before they change anything. The map is built from real edges; the model reads it, it never invents it.
Every decision, discovery, and fix is recorded and searchable. Agents don't re-debug a solved bug or re-litigate a settled choice. The institutional record is part of the work, not lost in a transcript.
What one agent learns grounds the next. Approved patterns and failure modes accumulate across the fleet and survive engineer turnover. The system gets smarter the longer it runs, with no retraining.
Code, observations, and references each have their own pipeline and their own enrichment, but agents reach them through one API and one set of tools.
Your working source, AST-chunked and embedded with a real symbol graph behind it: calls, called-by, implements, imports.
Every decision, discovery, fix, and outcome an agent records, banked as an immutable timeline of why the system looks the way it does.
External material that grounds the work: SDK source, PDFs, API specs, crawled sites, all enriched with summaries and section anchors.
When a worker proposes a change, AgentOS does not trust the description of the change. It traces the actual symbols through the actual code graph and classifies the blast radius from the impacted set. The classification decides whether the team has authority to ship, or whether the change escalates.
The worker names the files, symbols, and paths it intends to touch. Description only; no edits yet.
search_code finds the real implementation for each named symbol. The worker's description is now grounded in code, not memory.
trace_symbol_dependencies walks the call graph: who calls this, who does this call, who implements this, who imports it. Sub-second, no LLM.
The set of symbols and modules that move when this change ships becomes a blast-radius class: local, module, system, or estate. The class is evidence-backed, not narrated by the model.
If the class stays inside the team's envelope, the work continues. If it crosses, AgentOS escalates before any code is written. The model never gets to claim "it's a small change" when the graph says otherwise.
Memory has to keep up with a fleet of agents that all want grounding at the same time. The substrate is built for concurrent retrieval, not single-user assistant patterns.
FAFO Memory is part of AgentOS. Become a design partner and put it to work on yours.