diff --git a/crates/ml/examples/train_baseline_rl.rs b/crates/ml/examples/train_baseline_rl.rs
index c186cdd3c..be3d1516f 100644
--- a/crates/ml/examples/train_baseline_rl.rs
+++ b/crates/ml/examples/train_baseline_rl.rs
@@ -816,6 +816,7 @@ fn run_training(args: &Args) -> Result<Vec<RlTrainingResult>> {
         });
 
     // Try loading from fxcache
+    eprintln!("[DEBUG] fxcache_dir = {:?}", fxcache_dir);
     let fxcache_data = fxcache_dir.and_then(|cache_dir| {
         let symbol_dir = args.data_dir.join(&args.symbol);
         let default_mbp10 = PathBuf::from("test_data/futures-baseline-mbp10");
@@ -861,7 +862,8 @@ fn run_training(args: &Args) -> Result<Vec<RlTrainingResult>> {
             n, data_load_start.elapsed().as_secs_f64());
         (bars, cached.features)
     } else {
-        // Fall back to DBN loading
+        // Fall back to DBN loading — this is SLOW (148GB MBP-10 parsing)
+        eprintln!("[DEBUG] fxcache MISS — falling back to DBN loading (SLOW!)");
         info!("  Loading OHLCV bars from DBN files...");
         let bars = load_all_bars(&args.data_dir, &args.symbol)?;
         if bars.is_empty() {
diff --git a/crates/ml/src/trainers/dqn/trainer/training_loop.rs b/crates/ml/src/trainers/dqn/trainer/training_loop.rs
index d086bde3f..4093af169 100644
--- a/crates/ml/src/trainers/dqn/trainer/training_loop.rs
+++ b/crates/ml/src/trainers/dqn/trainer/training_loop.rs
@@ -286,11 +286,13 @@ impl DQNTrainer {
             };
 
             // ── Phase 2: GPU experience collection ──
+            eprintln!("[DEBUG] Phase 2: starting GPU experience collection (epoch {})", epoch);
             let phase2_start = std::time::Instant::now();
             let gpu_experiences_collected = self.collect_gpu_experiences(
                 training_data,
             ).await?;
             let phase2_ms = phase2_start.elapsed().as_secs_f64() * 1000.0;
+            eprintln!("[DEBUG] Phase 2: done in {:.1}ms, collected={}", phase2_ms, gpu_experiences_collected);
 
             // CUDA builds: GPU experience collector is MANDATORY
             if !gpu_experiences_collected {
@@ -315,9 +317,11 @@ impl DQNTrainer {
             }
 
             // ── Phase 3: Batched training from replay buffer ──
+            eprintln!("[DEBUG] Phase 3: starting training steps (epoch {})", epoch);
             let phase3_start = std::time::Instant::now();
             let train_step_count = self.run_training_steps(training_data).await?;
             let phase3_ms = phase3_start.elapsed().as_secs_f64() * 1000.0;
+            eprintln!("[DEBUG] Phase 3: done in {:.1}ms, steps={}", phase3_ms, train_step_count);
 
             // ── Phase 4: Epoch boundary + validation ──
             let phase4_start = std::time::Instant::now();
@@ -1169,11 +1173,13 @@ impl DQNTrainer {
         // #33 Saboteur state already set above (before collector borrow)
 
         // Zero-roundtrip GPU path — GPU PER is always active in CUDA builds
+        eprintln!("[DEBUG] collect_experiences_gpu: n_episodes={}, timesteps={}, starts_len={}", n_episodes, timesteps, episode_starts.len());
         let gpu_batch = collector.collect_experiences_gpu(
             features_buf, targets_buf, &episode_starts, &config,
         ).map_err(|e| anyhow::anyhow!(
             "GPU zero-roundtrip collection FAILED (no CPU fallback): {e}"
         ))?;
+        eprintln!("[DEBUG] collect_experiences_gpu: DONE, batch.n_episodes={}, batch.timesteps={}", gpu_batch.n_episodes, gpu_batch.timesteps);
 
         let count = gpu_batch.n_episodes * gpu_batch.timesteps;