Platform State & Direction
Current Capabilities & Roadmap
We believe in presenting capabilities factually based on running code and test suites. Here is an honest accounting of what is currently implemented in v0.3.0, our architectural limitations, and our planned research experiments for v0.4.0.
Current Baseline
Current Release: v0.3.0 — Dynamic Orchestration
The platform currently demonstrates the following capabilities across 401 passing tests in the repository:
Dynamic Candidate Discovery
Agents dynamically register advertised capabilities and communication addresses. The orchestrator queries candidates at runtime rather than relying on hardcoded queues.
Availability & Heartbeat Liveness
Explicit runtime availability semantics (ready, busy, stale, offline) based on periodic agent heartbeats and configurable threshold policies.
Grounded Research Pipeline
Multi-stage research pipeline separating public-web retrieval, deterministic evidence evaluation, and evidence-conditioned language model synthesis with citations.
Routing Observability
Every task dispatch logs its decision context (candidate pool, availability states, selected target) in Redis, exposed live in the Prototype Console.
Clean Architecture
Inward dependency direction keeping domain logic completely decoupled from Redis, Docker, Tavily search, and Cloudflare Workers AI.
401 Automated Tests
Comprehensive test suite covering unit logic, domain invariants, application use cases, contracts, concurrent heartbeats, and web presentation deterministically without external services.
Engineering Honesty
Honest Limitations & Caveats
Understanding what an AI system cannot do is just as important as knowing what it can do. We explicitly document our known engineering boundaries:
-
Evidence ranking is not proof of truth. The
EvidenceEvaluatorapplies scoring heuristics (domain tier, keyword density, content length) to filter noise. It produces an ordered set of evaluated evidence, not factual ground truth. - Cross-domain keyword overlap is not semantic corroboration. Shared vocabulary between different websites often indicates shared talking points, syndication, or common terminology rather than independent verification.
- Retrieval quality is bounded by the search provider. The Research Agent's output is strictly limited by the snippets returned by the retrieval API (Tavily). If search returns irrelevant data, synthesis cannot fix it.
- Non-commercial experimental scope. This lab is designed to study distributed agent lifecycles, orchestration, and observability. It is not an enterprise product, marketing tool, or commercial SaaS.