Public Roadmap — Project Chimera (Phases 0 → 4)

[akarlaraytu]

Public Roadmap — Project Chimera

This is the single source-of-truth for Project Chimera's public roadmap. This document outlines the architectural evolution from a specialized agent into a general-purpose, verifiable AI governance ecosystem.

Related Project: Roadmap Board

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🗺️ The Grand Vision: "Verifiable Autonomy"

Project Chimera is evolving. We are no longer just building an agent; we are building the safety layer that allows agents to operate autonomously in high-stakes environments.

Core Philosophy: Trust is good, but mathematical verification is better.

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High-Level Phases

• ✅ Phase 1 — Strategic Depth & Optimization — COMPLETE
  • Theme: Developed the initial SymbolicGuardian architecture. Proved that Neuro-Symbolic agents outperform standard LLMs in e-commerce optimization.
• ✅ Phase 2 — Domain Agnosticism (Quant Finance) — COMPLETE
  • Theme: Decoupled the reasoning engine from the environment. Validated the architecture in the high-frequency, high-risk domain of Quantitative Finance.
• ✅ Phase 3 — The Governance Layer (Birth of CSL) — COMPLETE
  • Theme: Realized that standard Python logic is insufficient for safety-critical AI.
  • Achievement: Designed and released CSL (Chimera Specification Language)—a deterministic, formal verification language for AI policies.
• ▶️ Phase 4 — The Great Unification (Chimera v2.0) — IN PROGRESS
  • Theme: Re-architecting the Chimera Agent to run entirely on the CSL kernel. The agent becomes the "Reference Implementation" of our safety protocol.

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Current Milestone: Phase 4 — The Great Unification

Now that the CSL compiler is live, we are migrating the Chimera Agent's "Brain" to use this new language. Chimera will become the first "Native CSL Agent"—demonstrating how to build safe, auditable AI.

Phase 4 Objectives:

1. Policy Migration (Python → CSL):
   • Task: Replace hardcoded if/else safety checks in SymbolicGuardian with compile-time verified .csl policy files.
   • Goal: Achieve 100% deterministic runtime enforcement.
2. The "Supply Chain" Stress Test:
   • Task: Deploy the new CSL-powered Chimera Agent into a complex Supply Chain simulation.
   • Goal: Prove that CSL can govern complex, multi-step logistics decisions without hallucination.
3. Package Release:
   • Goal: pip install chimera-agent.
   • Vision: Any developer can download the agent, write a CSL policy, and deploy a safe AI worker instantly.

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Future Horizon

• Phase 5: Autonomous Causal Discovery
  • Concept: Moving beyond human-written rules.
  • Moonshot: The agent observes its environment, identifies new causal links, and writes its own CSL policies to adapt to changing market conditions—while remaining mathematically safe.

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🤝 How to Contribute

• ⭐ Star the repo to follow development.
• Build with us: Check out the CSL Core Repo.
• Join the discussion: See Discussions → Roadmap for architecture debates.
• Start coding: Look for good first issue tasks tagged with csl-migration.

[akarlaraytu]

🚀 Phase 4 Update — The Great Unification (v1.7.0)

✅ SymbolicGuardian migrated to CSL-Core
✅ E-commerce + Quant policies formally verified with Z3
✅ Backward-compatible wrapper — zero breaking changes
✅ All existing tests, backtests, and live trader verified

Next: Causal engine ↔ CSL feedback loops, per-agent policies in Colosseum,
temporal logic constraints.