When the operator sets `APR_DISTILL_MAX_STEPS=N` (default unset), the
distill training loop runs at most N steps, prints a per-run summary,
and exits without writing a final output model. Lets operators
validate the cascade end-to-end in ~60 s before committing to a 30-50 h
Stage D production run.

The PMAT-704 cascade post-mortem found that the 7B vocab-aligned
500-step validation hung at step 0 for 1.5 h with no per-step output.
PMAT-705 (#1881) added ProgressCallback to surface per-step loss
during normal runs. PMAT-706 adds the complementary EARLY-BREAK so
operators don't have to wait through the full epoch budget to see if
something's wrong.

`crates/aprender-train-distill/src/pipeline.rs`:

* Reads `APR_DISTILL_MAX_STEPS` env var. Empty/unset = old behavior
  (no regression). N > 0 = run at most N steps then break. N = 0 or
  non-integer = early Err with clear message.
* Optional `APR_DISTILL_PROJECT_TO_STEPS` env var (default 50000)
  controls the projected-wall-time target in the summary.
* `train()` early-breaks the inner loop when step >= max_steps,
  prints two `[SMOKE]` summary lines (loss trajectory + projected
  wall time at the observed throughput), and returns empty weights /
  shapes via the normal Result path.
* `execute()` detects smoke mode (env var set) and short-circuits
  the export step — no `model.safetensors` / output.apr is written,
  so downstream tools (`apr eval`, `apr run`) can't accidentally
  consume a smoke result.

  [PMAT-706] smoke mode: APR_DISTILL_MAX_STEPS=N (early-break after N steps; no final output.apr written)
  ...
  [SMOKE] N steps in T.TTs: initial_loss=X.XXXX, final_loss=Y.YYYY, throughput=Z.ZZ step/s
  [SMOKE] projected full-run wall time (50000 steps): H.HHh / W.W min / S.Ss
  [PMAT-706] smoke mode: skipping export — no model.safetensors / output.apr written

`contracts/apr-distill-smoke-validation-v1.yaml`:

* 3 equations: early_break_condition (off-by-one tight), smoke_summary_format,
  no_side_effects.
* 4 falsifiers (FT-SMOKE-001..004) covering exact step count, no-regression
  when unset, summary line format, no output.apr written.
* 2 Kani harnesses (count is tight; 0 steps is degenerate, not panic).
* qa_gate F-SMOKE-001.
* Validates clean: `pv validate` 0 errors, 0 warnings.

`pipeline::tests::pmat_706_smoke_validation`:

  * `falsify_smoke_001_exact_step_count` — N=10 returns metrics.steps_completed == 10
  * `falsify_smoke_002_no_regression_when_unset` — unset → full epochs run
  * `falsify_smoke_004_no_output_in_smoke` — output_path empty + no model.* files
  * `smoke_zero_steps_returns_err` — N=0 returns Err

Tests share global env state; serialized via a Mutex (ENV_LOCK) so
they don't race in parallel threads. All 4 PASS.

This closes the diagnostic loop on the PMAT-704 cascade post-mortem
lesson. Per memory `feedback_a_priori_theoretical_falsification.md`:
30 min of math saves 8 h of GPU. PMAT-706 is the runtime analog:
60 s of smoke saves 8 h of staring at a silent process.

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

…#1888)

When the operator sets `APR_DISTILL_MAX_STEPS=N` (default unset), the
distill training loop runs at most N steps, prints a per-run summary,
and exits without writing a final output model. Lets operators
validate the cascade end-to-end in ~60 s before committing to a 30-50 h
Stage D production run.

The PMAT-704 cascade post-mortem found that the 7B vocab-aligned
500-step validation hung at step 0 for 1.5 h with no per-step output.
PMAT-705 (#1881) added ProgressCallback to surface per-step loss
during normal runs. PMAT-706 adds the complementary EARLY-BREAK so
operators don't have to wait through the full epoch budget to see if
something's wrong.

`crates/aprender-train-distill/src/pipeline.rs`:

* Reads `APR_DISTILL_MAX_STEPS` env var. Empty/unset = old behavior
  (no regression). N > 0 = run at most N steps then break. N = 0 or
  non-integer = early Err with clear message.
* Optional `APR_DISTILL_PROJECT_TO_STEPS` env var (default 50000)
  controls the projected-wall-time target in the summary.
* `train()` early-breaks the inner loop when step >= max_steps,
  prints two `[SMOKE]` summary lines (loss trajectory + projected
  wall time at the observed throughput), and returns empty weights /
  shapes via the normal Result path.
* `execute()` detects smoke mode (env var set) and short-circuits
  the export step — no `model.safetensors` / output.apr is written,
  so downstream tools (`apr eval`, `apr run`) can't accidentally
  consume a smoke result.

  [PMAT-706] smoke mode: APR_DISTILL_MAX_STEPS=N (early-break after N steps; no final output.apr written)
  ...
  [SMOKE] N steps in T.TTs: initial_loss=X.XXXX, final_loss=Y.YYYY, throughput=Z.ZZ step/s
  [SMOKE] projected full-run wall time (50000 steps): H.HHh / W.W min / S.Ss
  [PMAT-706] smoke mode: skipping export — no model.safetensors / output.apr written

`contracts/apr-distill-smoke-validation-v1.yaml`:

* 3 equations: early_break_condition (off-by-one tight), smoke_summary_format,
  no_side_effects.
* 4 falsifiers (FT-SMOKE-001..004) covering exact step count, no-regression
  when unset, summary line format, no output.apr written.
* 2 Kani harnesses (count is tight; 0 steps is degenerate, not panic).
* qa_gate F-SMOKE-001.
* Validates clean: `pv validate` 0 errors, 0 warnings.

`pipeline::tests::pmat_706_smoke_validation`:

  * `falsify_smoke_001_exact_step_count` — N=10 returns metrics.steps_completed == 10
  * `falsify_smoke_002_no_regression_when_unset` — unset → full epochs run
  * `falsify_smoke_004_no_output_in_smoke` — output_path empty + no model.* files
  * `smoke_zero_steps_returns_err` — N=0 returns Err

Tests share global env state; serialized via a Mutex (ENV_LOCK) so
they don't race in parallel threads. All 4 PASS.

This closes the diagnostic loop on the PMAT-704 cascade post-mortem
lesson. Per memory `feedback_a_priori_theoretical_falsification.md`:
30 min of math saves 8 h of GPU. PMAT-706 is the runtime analog:
60 s of smoke saves 8 h of staring at a silent process.

Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>