diff --git a/playbooks/gx10-outfit-privileged.yaml b/playbooks/gx10-outfit-privileged.yaml
index fd825ca..f8ff521 100644
--- a/playbooks/gx10-outfit-privileged.yaml
+++ b/playbooks/gx10-outfit-privileged.yaml
@@ -73,6 +73,18 @@ steps:
     shell: DEBIAN_FRONTEND=noninteractive apt-get install -y -qq cuda-toolkit
     when: "! test -x /usr/local/cuda/bin/nvcc"
 
+  - name: Install python3-dev + build-essential (Triton JITs C at RUNTIME)
+    # Triton compiles its CUDA-utils shim with gcc on FIRST USE and needs
+    # Python.h to do it. Without python3-dev, torch imports fine, the model
+    # loads fine, LoRA attaches fine -- and then the first training step dies
+    # with a CalledProcessError from gcc whose real message ("fatal error:
+    # Python.h: No such file or directory") is swallowed, because Triton
+    # sends the compiler's stdout to DEVNULL. Cost a probe run to find.
+    # Same shape as the dots-tts container needing a C compiler at runtime.
+    sudo: true
+    shell: DEBIAN_FRONTEND=noninteractive apt-get install -y -qq python3-dev build-essential
+    when: "! test -f /usr/include/python3.12/Python.h"
+
   - name: Install the NVIDIA Container Toolkit
     sudo: true
     shell: DEBIAN_FRONTEND=noninteractive apt-get install -y -qq nvidia-container-toolkit
@@ -101,6 +113,18 @@ verify:
     shell: sg docker -c 'docker run --rm --gpus all nvidia/cuda:13.0.0-base-ubuntu24.04 nvidia-smi -L' | grep -q GB10
     changed_when: "false"
 
+  - name: Triton can actually compile its runtime shim
+    # Asserting the effective behaviour. `dpkg -l python3-dev` would pass while
+    # the compile still failed for a missing header or library path.
+    shell: |
+      V=/home/infra-ops/ml/.venv/lib/python3.12/site-packages/triton/backends/nvidia
+      test -d "$V" || exit 0
+      gcc "$V/driver.c" -O3 -shared -fPIC -Wno-psabi -o /tmp/.tritoncheck.so \
+        -l:libcuda.so.1 -L"$V/lib" -L/lib/aarch64-linux-gnu \
+        -I"$V/include" -I/usr/include/python3.12
+      rm -f /tmp/.tritoncheck.so
+    changed_when: "false"
+
   - name: The userspace torch stack still sees the GPU
     # Guards against a toolkit install disturbing the working driver.
     shell: /home/infra-ops/ml/.venv/bin/python -c 'import torch;assert torch.cuda.is_available()'