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  <title>dcoach — prove a CPU model recalls its training · mindXtrain</title>
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    <h1>dcoach <span class="muted">— prove the training stuck</span></h1>
    <p class="lede">
      Imprint a persona onto a tiny model on <strong>CPU</strong>, then prove the model
      <em>recalls</em> it: the <strong>classroom</strong> measures recall before vs after
      training, the <strong>boardroom</strong> rules success or failure, and the verdict
      feeds the <strong>autotune feedback loop</strong> that tunes the next run. This is
      mindXtrain's first-run proof — and the on-ramp to decentralized training.
    </p>
  </header>

  <main class="dc-grid">
    <section class="dc-card">
      <h3>1 · Imprint &amp; Prove</h3>
      <div class="dc-row">
        <label for="dc-persona">Persona (the voice to imprint)</label>
        <select id="dc-persona"></select>
      </div>
      <div class="dc-row">
        <label>Skills (extra demonstrations, optional)</label>
        <div id="dc-skills" class="dc-skills"></div>
      </div>

      <details>
        <summary class="muted" style="cursor:pointer;font-size:0.85rem;">Advanced parameters</summary>
        <div style="margin-top:0.6rem;">
          <div class="dc-row">
            <label for="dc-base">Base model (the actor)</label>
            <input id="dc-base" type="text" value="HuggingFaceTB/SmolLM2-135M" />
          </div>
          <div class="dc-row">
            <label for="dc-board">Boardroom preset</label>
            <select id="dc-board">
              <option value="classic_triad">classic_triad</option>
              <option value="solo">solo</option>
              <option value="quintet">quintet</option>
            </select>
          </div>
          <div class="dc-row">
            <label for="dc-board-model">Boardroom model (blank = tally classroom verdict)</label>
            <input id="dc-board-model" type="text" placeholder="e.g. qwen3:0.6b" />
          </div>
          <div class="dc-row">
            <label for="dc-tokens">Recall generation length (max_new_tokens)</label>
            <input id="dc-tokens" type="number" value="48" min="8" max="256" />
          </div>
        </div>
      </details>

      <button id="dc-run" class="dc-run">Imprint &amp; Prove</button>
      <span id="dc-status" class="muted" style="margin-left:0.8rem;font-size:0.85rem;"></span>
    </section>

    <section id="dc-live" class="dc-card hidden">
      <h3>2 · Live proof loop</h3>
      <div id="dc-phases" class="dc-phases"></div>
    </section>

    <section id="dc-result" class="dc-card hidden">
      <h3>3 · Verdict</h3>
      <div class="dc-verdict">
        <div class="dc-metric"><div class="v" id="r-before">–</div><div class="k">recall before</div></div>
        <div class="dc-metric"><div class="v" id="r-after">–</div><div class="k">recall after</div></div>
        <div class="dc-metric"><div class="v" id="r-delta">–</div><div class="k">imprint Δ</div></div>
        <div class="dc-metric"><div class="v" id="r-persona">–</div><div class="k">persona kept</div></div>
        <div class="dc-metric"><div class="v" id="r-board">–</div><div class="k">boardroom</div></div>
        <div class="dc-metric"><div class="v" id="r-passed">–</div><div class="k">proof</div></div>
      </div>
      <p id="r-rationale" class="lede" style="margin-top:0.7rem;"></p>
      <p id="r-next" class="muted" style="font-size:0.82rem;"></p>
    </section>

    <section class="dc-card">
      <h3>How mindXtrain fits decentralized training (2026)</h3>
      <p id="dc-thesis" class="lede"></p>
      <table class="dc-fit">
        <thead><tr><th>Primitive</th><th>mindXtrain</th><th>Maps to</th></tr></thead>
        <tbody id="dc-fit-body"></tbody>
      </table>
      <h4 style="margin:1rem 0 0.5rem;font-size:0.9rem;">The networks</h4>
      <div id="dc-net" class="dc-net"></div>
      <p class="muted" style="font-size:0.75rem;margin-top:0.7rem;">
        Read-only. mindXtrain does not mine on these networks — every one is CUDA-first /
        hardware-gated. It exposes a verifiable, payable training surface compatible with
        their verification primitives. Source: <code>docs/decentralized-training-deep-dive-2026.md</code>.
      </p>
    </section>
  </main>

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