spec(ml-alpha): stacked Mamba2 -> CfC amendment

Mid-execution architecture revision: Mamba2 stays as a sequence
encoder; CfC becomes the layer on top (replacing the Phase 1d.3 MLP
stacker). Gate becomes 'stacked AUC >= Mamba2-only stacker AUC at
every horizon' — proves the CfC layer is additive, rather than CfC
alone beating Mamba2 alone.

Plan 1 kernels (cfc_step, heads, projection, BCE, AdamW, Graph A)
are unchanged. Only CfcTrunk's forward path gains a Mamba2 prefix
that consumes the snapshot stream and emits a 128-dim h_mamba which
CfC reads. The Mamba2 kernel (mamba2_alpha_kernel.cubin) is already
in the build.

Option B (parallel + fused dual-stream) is documented as the Plan 2
fallback if the stacked gate fails.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

docs/superpowers/specs/2026-05-16-ml-alpha-cfc-ppo-design.md

@@ -1,9 +1,24 @@
 # ml-alpha — Greenfield CfC + PPO Trading System Design
 
 **Date**: 2026-05-16
-**Status**: Approved (all 7 sections + ISV-driven auto-tuning addition)
+**Status**: Approved with **2026-05-16 stacked-architecture amendment** (see Section 2.5 below)
 **Supersedes**: `2026-05-16-alpha-ppo-trainer.md` (the earlier DQN-port plan, abandoned per user direction to rebuild from first principles)
 
+## 2026-05-16 Amendment: Mamba2 → CfC stacked perception (Option A)
+
+The original spec framed CfC as a *replacement* for Mamba2 at the perception trunk, with a hard gate requiring CfC AUC ≥ Mamba2 AUC at every horizon. Mid-execution of Plan 1, the architecture was revised to a **stacked design** where Mamba2 stays in the system as a frozen-or-jointly-trained sequence encoder feeding into CfC. The CfC layer learns per-cell time-constants over the SSM output.
+
+**Why the change**: Phase 1d.3 already validated `Mamba2 → MLP stacker`. Replacing the MLP stacker with CfC strictly extends the validated path rather than swapping a known-good encoder for an unvalidated one. The gate now proves "the CfC layer is additive" rather than "CfC alone beats Mamba2 alone."
+
+**Affected sections**:
+- Section 2 — `Perception trunk` reads: Mamba2 SSM (input → 128-dim h_mamba) → CfC cell (128-dim h_mamba → 128-dim h_cfc) → multi-horizon heads + projection
+- Section 4 — Gate: `stacked AUC ≥ Mamba2-only AUC at every horizon` (with the Mamba2-only AUC measured from a comparable stacker-MLP architecture for fairness)
+- Section 7 — Param count: ~50K trainable (15K Mamba2 + 35K CfC stack)
+
+**Fallback path (Option B — parallel + fused)**: if the stacked gate fails, fallback is dual-stream (Mamba2 + CfC read snapshots in parallel; outputs concat → projection → heads). Documented as a Plan-2 amendment if A's gate fails; not implemented in Plan 1.
+
+The CfC kernels (`cfc_step.cu`), heads, projection, BCE, AdamW, and Graph A are unchanged. Only the trunk's forward path adds a Mamba2 prefix.
+
 ## TL;DR
 
 A clean greenfield rebuild of `ml-alpha` as a full closed-loop alpha trading system for ES.FUT on IBKR with $35k starting capital. Three components: (1) a Rust model library that owns a CfC perception trunk + 5 multi-horizon alpha heads + a CfC actor-critic policy, (2) an offline training binary, (3) an `AlphaPpoStrategy` integration in the existing `trading_agent_service` for live runtime. Everything GPU-resident on the hot path. Online learning with EWC anchoring + replay buffer (80% offline / 20% live) + kill-switch on σ-band metric deviations. Hyperparameters that vary during training are ISV-driven (signal-driven controllers, no magic numbers). Reuse the existing IBKR adapter, data ingestion, execution engine, and risk manager.