Your agents start from
zero every session.
Rediscovery is the most expensive thing your agents do.
Every new session, the agent re-reads the repository, re-derives the structure, re-guesses the dependencies, and re-learns the architectural decision you explained last Tuesday. You pay for that in tokens, in latency, and in drift you won’t notice until it matters.
A deterministic map, produced once and queried forever — instead of a probabilistic one, re-derived every turn.
The model is doing the parser’s job, badly and repeatedly.
Bigger context windows made this cheaper to ignore. They did not make it stop.
Structure gets rebuilt from raw text.
Where a class lives, what depends on it, which call crosses an architectural boundary — all of it reconstructed from scratch, every session, by a model that is guessing.
Bigger bills, hallucinated edges.
Context spent on derived facts is context not spent on reasoning. Worse, the dependency graph the model “recalls” drifts from the one the compiler sees — quietly, and in the direction of confident wrongness.
Longer prompts, more pasting.
Hand-maintained context files and ever-larger prompt preambles are a memory system with a human as the storage layer. It goes stale the day you stop updating it.
Give the agents a map they didn’t have to imagine.
The ASE stack separates facts about your code from reasoning about your code, and keeps the facts.
Deterministic code intelligence.
Bo analyzes the repository into a stable contract — symbols, contracts, dependencies, boundaries, complexity, refactor pressure. Same input, same answer, every time, with no model in the loop.
A graph, not a transcript.
BogDB stores that map as a queryable graph agents reach through MCP, so an agent asks a question instead of reading a codebase to infer the answer.
Local-first memory drawers.
BogMem mines your repository into verbatim, searchable memory that stays on your machine — what was decided, what was tried, what was rejected.
The intent survives the session.
Versioned problem, architecture, and compliance definitions in ASE carry the why across runs, so a new agent inherits the constraints instead of rediscovering them the hard way.
From cold start to grounded start.
Indexing happens once. Every session after that begins already informed.
Index the repository
Bo derives the structural map deterministically and emits it as a stable JSON contract — no model involved, no variance between runs.
Store it as a graph
The map lands in BogDB, where it becomes queryable by any agent through MCP rather than re-parsed by each one.
Agents query instead of guess
A launched agent asks for the symbols, dependencies, and boundaries it needs and spends its context window on the actual problem.
Decisions accumulate
Run records, definitions, and memory drawers keep the reasoning, so the next constellation starts where the last one finished.
What your agents know before they start.
This is the state a new agent inherits on its first turn — not what it can eventually reconstruct.
- Structural map — symbols, contracts, dependencies, boundaries, and complexity, derived deterministically.
- Architectural intent — the versioned definitions describing what this system is supposed to be.
- Decision history — prior run records, claims, and verdicts on the same codebase.
- Memory drawers — verbatim, searchable local memory of what was decided and what was rejected.
- Token economics — context spent on reasoning rather than on re-deriving facts a parser already knew.
This one rarely shows up alone.
Stop paying to rediscover your own codebase.
Bring a repository and we’ll index it live — then let an agent answer questions about it from the graph.
Elevate Your Vibe with ASE Precision.