Update docs: CNN v2 weights loading fixed and validated

2 files changed, 10 insertions, 18 deletions

diff --git a/PROJECT_CONTEXT.md b/PROJECT_CONTEXT.md
index 2ed2b09..83bfef6 100644
--- a/PROJECT_CONTEXT.md
+++ b/PROJECT_CONTEXT.md
@@ -36,7 +36,7 @@
 - **Audio:** Sample-accurate sync. Zero heap allocations per frame. Variable tempo. Comprehensive tests.
 - **Shaders:** Parameterized effects (UniformHelper, .seq syntax). Beat-synchronized animation support (`beat_time`, `beat_phase`). Modular WGSL composition.
 - **3D:** Hybrid SDF/rasterization with BVH. Binary scene loader. Blender pipeline.
-- **Effects:** CNN post-processing foundation (3-layer architecture, modular snippets). CNNEffect validated in demo. CNN v2 complete: storage buffer architecture, binary weights (~3.2 KB), dynamic layer count, patch-based training (100 epochs, 3×3 kernels). TODO: 8-bit quantization.
+- **Effects:** CNN post-processing: CNNEffect (v1) and CNNv2Effect operational. CNN v2: storage buffer weights (~3.2 KB), 7D static features, dynamic layers. Validated and loading correctly. TODO: 8-bit quantization.
 - **Tools:** CNN test tool (readback works, output incorrect - under investigation). Texture readback utility functional. Timeline editor (web-based, beat-aligned, audio playback).
 - **Build:** Asset dependency tracking. Size measurement. Hot-reload (debug-only).
 - **Testing:** **36/36 passing (100%)**
diff --git a/TODO.md b/TODO.md
index a1ee9a2..3734ec6 100644
--- a/TODO.md
+++ b/TODO.md
@@ -31,26 +31,18 @@ Enhanced CNN post-processing with multi-dimensional feature inputs.
 **Design:** `doc/CNN_V2.md`
 
 **Status:**
-- ✅ Phase 1-5: All implementation phases complete
-- ✅ Storage buffer architecture (dynamic layer count support)
-- ✅ Binary weight format (header + layer info + f16 weights)
-- ✅ Training pipeline with live progress display
-- ✅ Complete validation tooling (`train_cnn_v2_full.sh --validate`)
+- ✅ Full implementation complete and validated
+- ✅ Binary weight loading fixed (FATAL_CHECK inversion bug)
+- ✅ Training pipeline: 100 epochs, 3×3 kernels, patch-based
 - ✅ All tests passing (36/36)
 
-**Features:**
-- 7D static feature input (RGBD + UV + sin encoding + bias)
-- Storage buffer weights (~3.2 KB for 3-layer, 8→4→4 config)
-- Dynamic layer count (not hardcoded)
-- Single compute shader with per-layer params
-- Patch-based training (harris detector, 32×32 patches)
-- Fast training config: 100 epochs, 3×3 kernels
+**Specs:**
+- 7D static features (RGBD + UV + sin + bias)
+- Storage buffer weights (~3.2 KB, 8→4→4 channels)
+- Dynamic layer count, per-layer params
+- <10 KB target achieved
 
-**Performance:**
-- Storage buffer overhead: ~10-20% vs constants (negligible @ 60fps)
-- Target achieved: <10 KB for 64k demo constraint
-
-**TODO:** 8-bit quantization for 2× size reduction (~1.6 KB). Requires QAT.
+**TODO:** 8-bit quantization (2× reduction, needs QAT).
 
 ---