PrometheonOS — Architecture Design Document

An autonomous Solana execution-intelligence engine: it streams the network live, submits Jito bundles with dynamically-priced tips, tracks every transaction across all four commitment levels, classifies failures from real signals, and lets an AI agent own — and explain — the autonomous recovery decision. Proven on mainnet.

Coverage map (the bounty’s required sections)

Required area	Where it’s answered
System architecture	§5 System architecture & data flow
Key components	§6 Component breakdown
Data flow between services	§5 (diagram) · §7 Event flow · §8 AI decision pipeline
Infrastructure decisions	§15 Infrastructure decisions · §3 Design philosophy
Failure handling strategy	§11 Failure handling · §9 Lifecycle state machine · §10 Retry state machine
AI agent responsibilities	§8 AI decision pipeline · §3 Design philosophy
Operational understanding	§4 Lifecycle deep dive · §20 Lessons learned · §22 Operational Q&A
Proof it ran on real infra	§19 Cost · §21 Implementation status & live validation

1. Executive summary

On Solana, sending a transaction is the easy part. Landing a value-critical one — a liquidation, an oracle update, an arbitrage — during congestion is where money is lost: the transaction expires or gets crowded out, and the usual “retry” is a dumb loop that re-sends the same expired blockhash with the same too-low tip until it gives up.

PrometheonOS is an execution control plane. It streams live slot/leader data from Yellowstone gRPC, constructs and submits Jito bundles with dynamically-computed tips, tracks each transaction across Submitted → Processed → Confirmed → Finalized, classifies failures from real signals, and lets an AI strategist make and explain real operational decisions (tip sizing, submission timing, and the autonomous retry-with-fault-injection recovery). Landing is confirmed from the stream; RPC is only a cross-check.

2. System goals

Real protocol fidelity — no hardcoded shortcuts; correct commitment handling end to end.
Total observability — everything timestamped and measurable; every failure classified; every retry and AI decision justified and persisted.
Clean separation between the deterministic core and the AI layer.
Production-grade reliability — supervised reconnection, backpressure, graceful degradation.

3. Design philosophy — the AI is a strategist, not in the hot path

An LLM call (~0.5–3 s) cannot sit inside the leader-window catch loop. So the architecture splits in two:

The Rust core is the deterministic hot path — catch the leader window, build/submit bundles, track the lifecycle — and always runs on the latest policy the agent has set.
The TS AI agent is an asynchronous strategist — it reacts to telemetry (health snapshots, failure/retry events) to set policy (tip target, hold/go) and to reason about discrete, non-microsecond-critical events (failure → recovery decision).

If the agent is slow or unreachable, the hot path proceeds on the last cached policy and never blocks. This is the single most important design decision in the system.

PrometheonOS — Architecture Design Document

Coverage map (the bounty’s required sections)

1. Executive summary

2. System goals

3. Design philosophy — the AI is a strategist, not in the hot path

4. Solana transaction lifecycle — deep dive