diff --git a/marketing/podcast/bin/fal-upscale.mjs b/marketing/podcast/bin/fal-upscale.mjs
new file mode 100644
index 0000000000..dd80a92db0
--- /dev/null
+++ b/marketing/podcast/bin/fal-upscale.mjs
@@ -0,0 +1,83 @@
+#!/usr/bin/env node
+// fal-upscale.mjs — super-resolution for the pals logos (or any image) via
+// fal.ai. AuraSR (default) is a clean 4× GAN upscaler ideal for graphic/logo
+// art; clarity adds invented detail (better for photos). Reuses the FAL_KEY +
+// queue pattern from pop/lib/fal-seedance.mjs.
+//
+// Usage:
+//   node bin/fal-upscale.mjs <in.png> [out.png] [--model aura-sr|clarity|esrgan] [--factor 4]
+//   node bin/fal-upscale.mjs out/pals/cf-sunset.png --model aura-sr
+
+import { readFileSync, writeFileSync } from "node:fs";
+import { resolve, dirname, basename, extname } from "node:path";
+import { fileURLToPath } from "node:url";
+
+const HERE = dirname(fileURLToPath(import.meta.url));
+const REPO = resolve(HERE, "..", "..", "..");
+
+function loadFalKey() {
+  if (process.env.FAL_KEY) return process.env.FAL_KEY;
+  const envFile = resolve(REPO, "aesthetic-computer-vault/.devcontainer/envs/devcontainer.env");
+  for (const line of readFileSync(envFile, "utf8").split("\n")) {
+    if (line.startsWith("FAL_KEY=")) return line.slice("FAL_KEY=".length).trim().replace(/^['"]|['"]$/g, "");
+  }
+  throw new Error("FAL_KEY not set and not in vault devcontainer.env");
+}
+
+const argv = process.argv.slice(2);
+const flag = (k, d) => { const i = argv.indexOf(`--${k}`); return i >= 0 ? argv[i + 1] : d; };
+const positional = argv.filter((a, i) => !a.startsWith("--") && argv[i - 1] !== `--model` && argv[i - 1] !== `--factor`);
+
+const inPath = resolve(process.cwd(), positional[0] || "");
+if (!positional[0]) { console.error("usage: fal-upscale.mjs <in> [out] [--model aura-sr|clarity|esrgan] [--factor 4]"); process.exit(1); }
+const modelName = flag("model", "aura-sr");
+const factor = Number(flag("factor", 4));
+const outPath = positional[1]
+  ? resolve(process.cwd(), positional[1])
+  : inPath.replace(new RegExp(`${extname(inPath)}$`), `.x${factor}.png`);
+
+const MODELS = {
+  "aura-sr":  { endpoint: "fal-ai/aura-sr",           input: (u) => ({ image_url: u, upscaling_factor: factor }) },
+  "clarity":  { endpoint: "fal-ai/clarity-upscaler",  input: (u) => ({ image_url: u, upscale_factor: factor, creativity: 0.2, resemblance: 0.9 }) },
+  "esrgan":   { endpoint: "fal-ai/esrgan",            input: (u) => ({ image_url: u, scale: factor }) },
+};
+const model = MODELS[modelName];
+if (!model) { console.error(`unknown model '${modelName}'. options: ${Object.keys(MODELS).join(", ")}`); process.exit(1); }
+
+const KEY = loadFalKey();
+const auth = { Authorization: `Key ${KEY}` };
+
+const buf = readFileSync(inPath);
+const dataUri = `data:image/png;base64,${buf.toString("base64")}`;
+
+console.log(`▸ upscaling ${basename(inPath)} ×${factor} via fal-ai/${model.endpoint.split("/").pop()} …`);
+// 1. submit
+let res = await fetch(`https://queue.fal.run/${model.endpoint}`, {
+  method: "POST", headers: { ...auth, "Content-Type": "application/json" },
+  body: JSON.stringify(model.input(dataUri)),
+});
+if (!res.ok) { console.error(`✗ submit ${res.status}: ${(await res.text()).slice(0, 300)}`); process.exit(1); }
+const job = await res.json();
+const statusUrl = job.status_url;
+const responseUrl = job.response_url;
+
+// 2. poll
+let status = job.status;
+const t0 = Date.now();
+while (status !== "COMPLETED") {
+  if (status === "FAILED" || Date.now() - t0 > 300000) { console.error(`✗ job ${status || "timeout"}`); process.exit(1); }
+  await new Promise((r) => setTimeout(r, 2500));
+  const s = await fetch(statusUrl, { headers: auth });
+  status = (await s.json()).status;
+  process.stdout.write(`\r  ${status} · ${((Date.now() - t0) / 1000).toFixed(0)}s   `);
+}
+process.stdout.write("\n");
+
+// 3. fetch result + download
+const r = await fetch(responseUrl, { headers: auth });
+const result = await r.json();
+const url = result.image?.url || result.images?.[0]?.url || result.output?.url;
+if (!url) { console.error(`✗ no image in result: ${JSON.stringify(result).slice(0, 300)}`); process.exit(1); }
+const img = await fetch(url);
+writeFileSync(outPath, Buffer.from(await img.arrayBuffer()));
+console.log(`✓ ${outPath}${result.image?.width ? ` (${result.image.width}×${result.image.height})` : ""}`);