feat(MAX-547): add memory reel proof pack

artifacts/MAX-547/README.md

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+# MAX-547 proof pack
+
+This folder contains the rebuilt content package for the /memory reel series under the correct target repo contract for `maxtechera/orchestrator`.
+
+Contents:
+- `package.json` — machine-readable placement schema for Content Engine
+- `variants.md` — five reel variants with three hooks each
+- `preview.html` — rendered review surface for screenshots
+- `rendered-markdown.html` — rendered markdown review surface
+- `*.png` — thumbnails and proof screenshots
+- `*.mp4` — five proof-of-concept reel exports

artifacts/MAX-547/package.json

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+{
+  "ticket_id": "MAX-547",
+  "content_type": "reel",
+  "target_repo": "maxtechera/orchestrator",
+  "brand": "max-techera",
+  "locale": "en",
+  "variants": [
+    {
+      "id": "v1-problem-agitate-solve",
+      "name": "Problem \u2192 Agitate \u2192 Solve",
+      "angle": "Make the pain visceral, then show /memory as the fix.",
+      "hooks": [
+        "Your AI agent forgot everything again.",
+        "You are not bad at prompting. Your agent is stateless.",
+        "If you re-explain your project every session, this is the bug."
+      ],
+      "script": "Problem clip: blank session. Agitate with the repeat-yourself loop. Solve by revealing /memory and the surviving context: project, last decision, current focus."
+    },
+    {
+      "id": "v2-contrarian",
+      "name": "Contrarian",
+      "angle": "The real problem is not the model, it is no memory architecture.",
+      "hooks": [
+        "Your agent is not dumb, it is just stateless.",
+        "Bigger models do not fix zero memory.",
+        "The real AI productivity leak is context reset, not model quality."
+      ],
+      "script": "Open with the contrarian line. Show a capable model still starting blank. Then show /memory preserving continuity after a fresh session."
+    },
+    {
+      "id": "v3-specific-number",
+      "name": "Specific-number",
+      "angle": "Quantify the loss: three things you repeat every session.",
+      "hooks": [
+        "3 things you keep re-explaining to your AI agent.",
+        "Three repeated context blocks are stealing your flow.",
+        "Every session reset costs you the same 3 explanations."
+      ],
+      "script": "Frame the pain as three repeated context blocks: project, last decision, current focus. Then show /memory carrying all three into the next session."
+    },
+    {
+      "id": "v4-insider-reveal",
+      "name": "Insider reveal",
+      "angle": "Reveal the architecture under the hood: HOT/WARM/COLD plus WAL.",
+      "hooks": [
+        "The trick is not chat history, it is memory architecture.",
+        "What actually makes an AI agent feel continuous? A 3-tier memory stack.",
+        "The secret is HOT, WARM, COLD plus a write-ahead log."
+      ],
+      "script": "Lead with the architectural reveal. Show HOT working state, WARM durable decisions, and COLD compiled wiki, with WAL surviving compaction."
+    },
+    {
+      "id": "v5-testimonial",
+      "name": "Testimonial",
+      "angle": "First-person workflow upgrade for indie hackers tired of daily resets.",
+      "hooks": [
+        "I got tired of re-explaining my project every morning.",
+        "The moment my agent stopped forgetting, my workflow changed.",
+        "This one install saved me from the daily context reset ritual."
+      ],
+      "script": "Tell it as a first-person before/after. Before: daily re-explaining ritual. After: new session already knows the project and active focus."
+    }
+  ],
+  "placements": {
+    "instagram_reel": {
+      "text": "Your AI agent forgot everything again.\n\nThat is not a prompting issue. It is a memory issue.\n\nEvery new session makes you re-explain the project, the last decision, and the one thing that matters now. `/memory` keeps that context alive across session compactions so the work keeps moving.\n\nDM MEMORY and I will send the free install guide.",
+      "cta": {
+        "action": "DM \"MEMORY\"",
+        "reason_for_now": "because re-explaining context every session is killing momentum"
+      },
+      "hashtags": [
+        "#memory",
+        "#aiagents",
+        "#claudecode",
+        "#buildinpublic",
+        "#indiehacker",
+        "#opensource",
+        "#aiworkflow",
+        "#llm"
+      ],
+      "media": {
+        "mp4": "artifacts/MAX-547/v1-problem-agitate-solve.mp4",
+        "thumbnail": "artifacts/MAX-547/v1-problem-agitate-solve.png"
+      },
+      "hook_variants": [
+        "Your AI agent forgot everything again.",
+        "You are not bad at prompting. Your agent is stateless.",
+        "If you re-explain your project every session, this is the bug."
+      ],
+      "manychat_trigger": {
+        "keyword": "MEMORY",
+        "flow_id": "TBD_MAX_PROVIDES"
+      }
+    },
+    "tiktok": {
+      "caption": "Hot take: bigger models do not fix zero memory. `/memory` does. Comment install and I will send the repo link.",
+      "hook_variants": [
+        "Your agent is not dumb, it is just stateless.",
+        "Bigger models do not fix zero memory.",
+        "The real AI productivity leak is context reset, not model quality."
+      ],
+      "media": {
+        "mp4": "artifacts/MAX-547/v2-contrarian.mp4"
+      }
+    },
+    "youtube_short": {
+      "title": "3 Things You Re-Explain Every AI Session",
+      "description": "Most session resets cost you the same three explanations. This short shows how /memory keeps them across compaction.",
+      "media": {
+        "mp4": "artifacts/MAX-547/v3-specific-number.mp4"
+      }
+    },
+    "x_thread": {
+      "tweets": [
+        {
+          "text": "Your AI agent forgot everything again. That is not a prompting problem. It is a stateless workflow problem."
+        },
+        {
+          "text": "Most resets force you to re-explain 3 things: the project, the last decision, and the current focus."
+        },
+        {
+          "text": "/memory keeps that context through HOT working state, WARM durable notes, and a COLD compiled wiki."
+        },
+        {
+          "text": "If you want the free install guide, reply MEMORY or grab the repo: github.com/maxtechera/memory"
+        }
+      ],
+      "cta": {
+        "action": "Reply \"MEMORY\"",
+        "reason_for_now": "to get the free install guide before your next reset"
+      }
+    },
+    "linkedin_post": {
+      "text": "Your AI agent is probably not underperforming because of the model. It is underperforming because every new session starts blank.\n\nThe practical fix is a memory layer that survives session compaction and preserves three things: project context, the last decision, and the current focus.\n\nThat is the promise of `/memory`: HOT working state, WARM durable context, and a COLD knowledge layer that compounds over time.\n\nIf you are building with Claude Code or any agentic workflow, this is the difference between daily reset and continuous execution.",
+      "cta": {
+        "action": "DM \"MEMORY\"",
+        "reason_for_now": "to get the install guide and stop losing context every session"
+      }
+    },
+    "email": {
+      "subject_variants": [
+        "Your agent forgot everything again",
+        "Stop resetting your AI agent daily",
+        "Install /memory before your next session"
+      ],
+      "preview_text": "A quick fix for stateless AI workflows that lose context every session.",
+      "body_html": "<html><body style=\"font-family:Arial,sans-serif;max-width:640px;margin:0 auto;line-height:1.6;color:#111;\"><h1>Your AI agent forgot everything again</h1><p>Every new session should not feel like day one.</p><p>The root problem is not prompting, it is memory. <strong>/memory</strong> preserves project context, the last decision, and the current focus across session compactions.</p><p>If you want the free install guide, reply with <strong>MEMORY</strong> or grab the repo at <a href=\"https://github.com/maxtechera/memory\">github.com/maxtechera/memory</a>.</p></body></html>",
+      "utm": {
+        "source": "mailerlite",
+        "campaign": "max-547-memory-reel-series",
+        "medium": "email"
+      }
+    },
+    "blog_post": {
+      "slug": "/blog/your-ai-agent-forgot-everything-again",
+      "title": "Your AI Agent Forgot Everything Again, Here Is the Fix",
+      "meta_description": "Why stateless AI sessions keep breaking your flow, and how a 3-tier memory system fixes it.",
+      "hero_og": "artifacts/MAX-547/v4-insider-reveal.png",
+      "body_md": "# Your AI agent forgot everything again\n\nEvery new session starts with a tax: repeat the project, repeat the last decision, repeat the current focus. `/memory` fixes that with HOT, WARM, and COLD memory tiers that survive session compactions.\n\n## The bug\nStateless sessions feel smart for one conversation and useless in the next.\n\n## The fix\nInstall `/memory`, connect your working context, and let the agent reload what matters.\n\n## The architecture\nHOT = live working state. WARM = durable decisions and facts. COLD = compiled knowledge that compounds over time.",
+      "faq": [
+        {
+          "q": "What problem does /memory solve?",
+          "a": "It stops you from re-explaining durable context every new session."
+        },
+        {
+          "q": "Who is this for?",
+          "a": "AI/LLM developers, Claude Code users, and indie hackers tired of session resets."
+        }
+      ]
+    },
+    "landing_page": {
+      "slug": "/memory",
+      "hero": {
+        "headline": "Your AI agent forgot everything again",
+        "subhead": "/memory keeps project context, last decisions, and current focus alive across sessions.",
+        "hero_image": "artifacts/MAX-547/v5-testimonial.png"
+      },
+      "features": [
+        {
+          "name": "HOT working state",
+          "hero_image": "artifacts/MAX-547/v4-insider-reveal.png",
+          "diagram": "artifacts/MAX-547/v4-insider-reveal.png",
+          "demo_media": "artifacts/MAX-547/v4-insider-reveal.mp4"
+        },
+        {
+          "name": "WARM durable decisions",
+          "hero_image": "artifacts/MAX-547/v3-specific-number.png",
+          "diagram": "artifacts/MAX-547/v3-specific-number.png",
+          "demo_media": "artifacts/MAX-547/v3-specific-number.mp4"
+        },
+        {
+          "name": "COLD compounding wiki",
+          "hero_image": "artifacts/MAX-547/v2-contrarian.png",
+          "diagram": "artifacts/MAX-547/v2-contrarian.png",
+          "demo_media": "artifacts/MAX-547/v2-contrarian.mp4"
+        }
+      ],
+      "ctas": {
+        "primary": "DM MEMORY",
+        "secondary": "Comment install"
+      },
+      "tracking_events": [
+        "page_view",
+        "cta_click_primary",
+        "cta_click_secondary",
+        "video_play"
+      ],
+      "meta": {
+        "title": "/memory for AI agents",
+        "description": "Persistent context for agentic workflows.",
+        "og": "artifacts/MAX-547/v1-problem-agitate-solve.png",
+        "canonical": "https://github.com/maxtechera/memory"
+      }
+    }
+  },
+  "proof": {
+    "pr_url": "https://github.com/maxtechera/orchestrator/pull/13",
+    "preview_urls": [
+      "artifacts/MAX-547/preview.html",
+      "artifacts/MAX-547/rendered-markdown.html"
+    ],
+    "screenshots": {
+      "desktop": "artifacts/MAX-547/screenshot-desktop.png",
+      "mobile": "artifacts/MAX-547/screenshot-mobile.png",
+      "rendered_html": "artifacts/MAX-547/rendered-html-screenshot.png",
+      "rendered_html_preview": "artifacts/MAX-547/rendered-html-preview-screenshot.png",
+      "rendered_github_markdown": "artifacts/MAX-547/rendered-github-markdown-screenshot.png"
+    },
+    "mp4_attachments": [
+      "artifacts/MAX-547/v1-problem-agitate-solve.mp4",
+      "artifacts/MAX-547/v2-contrarian.mp4",
+      "artifacts/MAX-547/v3-specific-number.mp4",
+      "artifacts/MAX-547/v4-insider-reveal.mp4",
+      "artifacts/MAX-547/v5-testimonial.mp4"
+    ],
+    "thumbnail_pngs": [
+      "artifacts/MAX-547/v1-problem-agitate-solve.png",
+      "artifacts/MAX-547/v2-contrarian.png",
+      "artifacts/MAX-547/v3-specific-number.png",
+      "artifacts/MAX-547/v4-insider-reveal.png",
+      "artifacts/MAX-547/v5-testimonial.png"
+    ],
+    "deployed_url": "https://github.com/maxtechera/orchestrator/pull/13"
+  }
+}

artifacts/MAX-547/preview.html

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+<!doctype html><html><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><title>MAX-547 Preview</title><style>body{font-family:Inter,Arial,sans-serif;background:#0b1020;color:#f7f8fc;margin:0;padding:40px}h1{font-size:44px;margin:0 0 10px}p.lead{max-width:900px;color:#c7d2fe}.grid{display:grid;grid-template-columns:repeat(auto-fit,minmax(320px,1fr));gap:20px;margin-top:28px}.card{background:#121937;border:1px solid #2c3a7a;border-radius:20px;padding:22px;box-shadow:0 20px 50px rgba(0,0,0,.35)}.eyebrow{text-transform:uppercase;letter-spacing:.12em;font-size:12px;color:#8fb3ff}ul{padding-left:20px}code{background:#1d2753;padding:2px 6px;border-radius:6px}</style></head><body><h1>MAX-547, /memory Reel Series</h1><p class="lead">Five proof-first reel variants packaged for Instagram Reels, TikTok, YouTube Shorts, X, LinkedIn, email, blog, and landing-page reuse. CTA stack: DM <code>MEMORY</code>, comment <code>install</code>, or hit the repo/course link.</p><div class="grid"><section class='card'><div class='eyebrow'>Variant 1</div><h2>Problem → Agitate → Solve</h2><p>Make the pain visceral, then show /memory as the fix.</p><ul><li>Your AI agent forgot everything again.</li><li>You are not bad at prompting. Your agent is stateless.</li><li>If you re-explain your project every session, this is the bug.</li></ul><p><strong>Script spine:</strong> Problem clip: blank session. Agitate with the repeat-yourself loop. Solve by revealing /memory and the surviving context: project, last decision, current focus.</p></section><section class='card'><div class='eyebrow'>Variant 2</div><h2>Contrarian</h2><p>The real problem is not the model, it is no memory architecture.</p><ul><li>Your agent is not dumb, it is just stateless.</li><li>Bigger models do not fix zero memory.</li><li>The real AI productivity leak is context reset, not model quality.</li></ul><p><strong>Script spine:</strong> Open with the contrarian line. Show a capable model still starting blank. Then show /memory preserving continuity after a fresh session.</p></section><section class='card'><div class='eyebrow'>Variant 3</div><h2>Specific-number</h2><p>Quantify the loss: three things you repeat every session.</p><ul><li>3 things you keep re-explaining to your AI agent.</li><li>Three repeated context blocks are stealing your flow.</li><li>Every session reset costs you the same 3 explanations.</li></ul><p><strong>Script spine:</strong> Frame the pain as three repeated context blocks: project, last decision, current focus. Then show /memory carrying all three into the next session.</p></section><section class='card'><div class='eyebrow'>Variant 4</div><h2>Insider reveal</h2><p>Reveal the architecture under the hood: HOT/WARM/COLD plus WAL.</p><ul><li>The trick is not chat history, it is memory architecture.</li><li>What actually makes an AI agent feel continuous? A 3-tier memory stack.</li><li>The secret is HOT, WARM, COLD plus a write-ahead log.</li></ul><p><strong>Script spine:</strong> Lead with the architectural reveal. Show HOT working state, WARM durable decisions, and COLD compiled wiki, with WAL surviving compaction.</p></section><section class='card'><div class='eyebrow'>Variant 5</div><h2>Testimonial</h2><p>First-person workflow upgrade for indie hackers tired of daily resets.</p><ul><li>I got tired of re-explaining my project every morning.</li><li>The moment my agent stopped forgetting, my workflow changed.</li><li>This one install saved me from the daily context reset ritual.</li></ul><p><strong>Script spine:</strong> Tell it as a first-person before/after. Before: daily re-explaining ritual. After: new session already knows the project and active focus.</p></section></div></body></html>

artifacts/MAX-547/rendered-markdown.html

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+<!doctype html><html><head><meta charset="utf-8"><meta name="viewport" content="width=device-width, initial-scale=1"><title>MAX-547 Rendered Markdown</title><style>body{font-family:system-ui,Arial,sans-serif;max-width:900px;margin:40px auto;padding:0 24px;line-height:1.65;color:#24292f} h1,h2,h3{line-height:1.25} pre{background:#f6f8fa;padding:16px;border-radius:8px;overflow:auto} code{background:#f6f8fa;padding:2px 5px;border-radius:6px} .muted{color:#57606a}</style></head><body><h1>MAX-547 Memory Reel Series</h1><p class="muted">Rendered markdown proof surface for review.</p><h2>Core angle</h2><p><strong>Your AI agent forgot everything again. <code>/memory</code> fixes that.</strong></p><h2>Proof-first structure</h2><ol><li>Show the blank session.</li><li>Show the repeat-yourself tax.</li><li>Show <code>/memory</code> preserving project, decision, and focus.</li><li>Show the HOT/WARM/COLD architecture.</li></ol><h2>Package coverage</h2><p>Instagram Reel, TikTok, YouTube Short, X thread, LinkedIn post, email, blog post, and landing page are all represented in <code>package.json</code>.</p></body></html>

artifacts/MAX-547/v1-problem-agitate-solve.txt

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+Problem clip: blank session.
+Agitate with the repeat-
+yourself loop. Solve by
+revealing /memory and the
+surviving context: project,
+last decision, current focus.

artifacts/MAX-547/v2-contrarian.txt

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+Open with the contrarian line.
+Show a capable model still
+starting blank. Then show
+/memory preserving continuity
+after a fresh session.

artifacts/MAX-547/v3-specific-number.txt

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+Frame the pain as three
+repeated context blocks:
+project, last decision,
+current focus. Then show
+/memory carrying all three
+into the next session.

artifacts/MAX-547/v4-insider-reveal.txt

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+Lead with the architectural
+reveal. Show HOT working
+state, WARM durable decisions,
+and COLD compiled wiki, with
+WAL surviving compaction.

artifacts/MAX-547/v5-testimonial.txt

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+Tell it as a first-person
+before/after. Before: daily
+re-explaining ritual. After:
+new session already knows the
+project and active focus.