Brick 1
Framework-as-Diagnostic Overlay
Greg's 7-tactic framework overlaid on Yuri's current infra: | Tactic | Greg's framework says | We have | Verdict | |---|---|---|---| | 1. MCP server as sales team | Publish to Smithery/MCPT/OpenTools for $0 CAC discovery | Zero — neither BizBuilder/KPDD nor Solacian have an MCP server | **REAL GAP** — but applicability depends on whether the product answers a queryable question; Solacian (Maze-dissolving AI) plausibly does, KPDD (PMF discovery) plausibly does | | 2. Programmatic SEO at 10K-page scale | Next.js + Firecrawl + AI content for "best X for Y" patterns | Zero programmatic pages; KPDD/Solacian don't have SEO surface | **REAL GAP** for both; needs a keyword pattern decision before any code | | 3. Free tool as top of funnel | Grader/analyzer/calculator, instant value, share-driven loop | KPDD itself is arguably a discovery tool but is gated by signup, not free-tool-grade | **PARTIAL GAP** — KPDD could expose a free analyzer slice; Solacian could expose a free "Maze diagnostic" | | 4. AEO (Answer Engine Optimization) | Top-20 questions + FAQ schema + monitoring via Otterly/Profound | Zero structured FAQ surface on either product site | **REAL GAP** for bo…
Source: src/lib/bricks/sources/greg-isenberg-bootstrap-distribution.md
Brick 2
Strategy 2: Programmatic SEO (10,000 Pages)
The thesis: create 10,000 SEO pages in 48 hours via keyword patterns + structured data + AI-generated unique content. Math model: - 10,000 pages × 30 visits/month each = 300,000 monthly visitors - 2% conversion = 6,000 conversions/month - $10 each = **$60,000/month from pages built once** - Caveat: 30 visits/month doesn't happen overnight; SEO compounds over time Critical: content must not feel like AI. Lots of optimization needed. Start with a few pages, scale once quality is right. "Press one button" myth is rejected explicitly. Playbook (start this week): 1. Pick a keyword pattern: `[product type] for [niche]` or `[service] in [city]`. Examples: "CRM for dentists", "roofing in Miami" 2. Build dataset via Firecrawl (scrapes + clean structured data) or existing databases 3. Create page template in your framework: Next.js, Webflow, WordPress — pick what you use 4. Use AI to generate unique paragraphs per page (not variable swaps; high-quality content) 5. Human-in-the-loop editing on a sample 6. Publish 100 pages as MVP 7. Monitor indexation 8. Scale once indexed Applies to: services, SaaS, apps, boring businesses, agencies. Programmatic SEO is still under-tapped.
Source: src/lib/bricks/sources/greg-isenberg-bootstrap-distribution.md
Brick 3
Strategy 5: Viral Artifacts (Make Outputs Shareable)
The thesis: Spotify Wrapped gets 100M shares every December. Everyone shares it. It says something about their identity. Build the equivalent for your product. Examples in the wild: - GitHub contribution graph → devs brag about green squares on Twitter - Stripe Atlas incorporation milestone → founders tweet "just incorporated" / "5 years ago today" - Duolingo daily streak → users brag about 365-day streaks - (Snapchat streaks were arguably the original) Look at social products for design psychology, then bring it into whatever you're building. Playbook (start this week): 1. Identify the output or milestone your user would screenshot and share 2. Make it beautiful, shareable, branded — logo subtle but present (big logo = no one shares someone else's logo; it should feel about THEM) 3. Add a share button that prefills the post with the artifact 4. Every share = free impressions to your exact target audience B2B works too. B2B are people. They share in Slack or Teams. Just ask: what would they share with the group you want more of?
Source: src/lib/bricks/sources/greg-isenberg-bootstrap-distribution.md
Brick 4
1.3 Code-Generated Ad Creatives (Cody Schneider method)
Source: [[../knowledge-env/synthesized/marketing-machine-10-parallel-agents.md]] **When to use**: zero budget for design, need to test messaging variations (not visual polish), finding the winning angle/pain point before investing in production **Process**: 1. Pick a reference ad format (Facebook Ads Library for competitor research, or "before/after" template) 2. Claude Code builds the ad as a React component (1080x1080px) 3. Research pain points via Perplexity API (scrape Reddit, YouTube, Twitter for ICP language) 4. Bulk-generate text variations: titles + paragraphs mapped to pain points 5. html-to-canvas converts React components to PNG 6. Download as zip, bulk upload to Facebook Ads API as drafts 7. Run $3-5/day per variation, 3-5 days 8. Analyze CPM/CPC via data warehouse (Graph MCP or CSV export) 9. Kill high-CPM losers via Facebook Ads API 10. Winners get promoted to dedicated ad set with CPA budget **Two schools of thought on creative quality**: - School A: "Scroll-stopping creative first" - use Nana Banana Pro / Kling AI for visuals - School B: "Messaging first, visuals later" - ugly code-generated ads that speak to pain points, find the 1-3 winning …
Source: src/lib/bricks/sources/perf-marketing-playbook.md
Brick 5
1.5 Competitor Creative Mining + AI Tagging (Apify pipeline)
Source: [[competitor-creative-mining-apify-pipeline.md]] **When to use**: entering a niche, no creative ideas, need to know what's working in competitor ads RIGHT NOW. Pre-step before §1.3 (code generation) — gives you the parameter library to remix from. **Process**: 1. Apify actor `curious_coder/facebook-ads-library-scraper` ($0.20-0.75 / 1K ads) pulls competitor ads from Meta Ads Library by search URL or competitor page list 2. Edit node computes `days_running = (end_date - start_date) / 86400` — proxy for performance (winners run 30+ days, losers killed in <7) 3. Download creatives to Google Drive or Supabase 4. GPT-4o vision analyzes each image, returns structured JSON: `ai_hook`, `ai_offer`, `ai_cta`, `ai_psychology`, `ai_utp`, `ai_jtbd`, `main_object`, `main_color`, `ai_description` 5. Code node validates JSON schema (one column = one property) 6. Merge node joins AI tags with metadata 7. Google Sheets append: one row per ad with image, params, days running, reach, est. spend 8. **Spend hack**: `est_spend = reach × avg_CPM_in_geo`; rank by `est_spend × days_running` to find competitor hero creatives 9. Output sheet feeds downstream creative-generation a…
Source: src/lib/bricks/sources/perf-marketing-playbook.md
Brick 6
Strategy 4: Answer Engine Optimization (AEO)
The thesis: be the source AI cites. Old SEO (30,000-word blog posts, backlink building, keyword stuffing) is declining; zero-click searches growing. AEO in 2026 = SEO in 2010. First movers will own niches for years. Goal: get cited by ChatGPT and Perplexity via structured direct answers, FAQ format, schema markup, comparison tables that AI can parse. Evidence: Peter Levels' AI referrals jumped from 4% to 20% in one month. Expected to keep increasing across e-commerce, SaaS, apps. Playbook (start this week): 1. Google the top 20 questions your customer asks 2. Write definitive structured answers for each — NOT 3,000-word fluff. Clear, direct, citation-worthy 3. Add schema markup and FAQ blocks 4. Publish on a domain with authority (or build authority through other strategies) 5. Monitor citations via Otterly, Profound, or manual testing Why Peter Levels wins faster: domain authority compounded over time. No better moment to start building authority than now.
Source: src/lib/bricks/sources/greg-isenberg-bootstrap-distribution.md
Brick 7
B043 — Record your process → transcribe → that's the lead magnet
Record your process → transcribe → that's the lead magnet. **Note:** Manual by design — requires founder's attention. Cut-adjacent for platform.
Source: _reference/bricks/README.md