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martín manén

T2 · manager / operator

Serial legal tech entrepreneur. Founded Derecho.com (1.2M clients, 80% automated), Abogado.com (lead gen), now launching Pacion AI (legal AI for SMEs). Early investor in Anthropic ($19B), Grock, via secondary markets. Board member at Factorial.

4 calls·4 names·75% bull·last heard 3 months ago·itnig
track record

no scored calls yet — needs a stated position or a categorical verdict, with a matured window vs SPY

top calls

highest conviction · one per company
1sthigh conviction
$ANTHROPICAnthropicposition

Anthropic secondary shares: passed at $8B, invested at $19B, now ~$90B; FTX liquidation created SPV chain risks

Anthropic is a foundational AI model winner-take-most market. Early secondary access via FTX liquidation (500M investment) yielded 165x paper returns. SPV chains create legal enforceability risks. Cursor acquisition for $60B in stock shows vertical integration into coding agents.

itnig2026-06episode →
2ndmedium conviction
$GROQGroqposition

Grock AI chip startup acquired by Nvidia for $20B (license + team); neocloud spinout Grock 2.0 raised $650M

Nvidia acquired Grock's team and non-exclusive license for $20B (antitrust structure). Grock retained neocloud inference data centers (Grock 2.0), raised $650M at high valuation. Martín invested via SPV, received dividends, reinvested. Neoclouds benefit from infinite inference demand.

itnig2026-06episode →
3rdmedium conviction
$HARVEYHarvey

Harvey and Legora target top law firms ($15K/seat), abandoning 80% SME market; Lexroom raises €50M for SMEs

Harvey/Legora focus on elite firms (30-40 lawyers, $15K/seat) leaving SME segment open. Lexroom (Italy) raised €50M, grew from €500K to ~€20M ARR targeting SMEs. Martín launching Pacion AI to compete in this whitespace with proprietary legal context/RAG.

itnig2026-06episode →

most discussed · click a bar to filter

  • $HARVEY
  • $LEXROOM
  • $ANTHROPIC
  • $GROQ

recurring themes

  • AI Applications1
  • AI Infrastructure1
  • AI Economics & Business Models1
4 total
$HARVEY
Harvey
MEDmartín manén·itnig·3 months ago·SpaceX a bolsa, THEKER levanta $85M y ANTHROPIC genera polémica | Tertulia de itnig
Harvey and Legora target top law firms ($15K/seat), abandoning 80% SME market; Lexroom raises €50M for SMEs
Harvey/Legora focus on elite firms (30-40 lawyers, $15K/seat) leaving SME segment open. Lexroom (Italy) raised €50M, grew from €500K to ~€20M ARR targeting SMEs. Martín launching Pacion AI to compete in this whitespace with proprietary legal context/RAG.
"Si tú te vas a Égora o a Harvey y dices, "Hola, soy un despacho español y tal." ¿Cuántos sois? 10. Muy bien. Encantado. Y se van a otro. Tienen tanta oferta, tanta, perdón, tanta…"
37:00
$LEXROOM
Lexroom
MEDmartín manén·itnig·3 months ago·SpaceX a bolsa, THEKER levanta $85M y ANTHROPIC genera polémica | Tertulia de itnig
Lexroom Italian legal AI raised €50M, targeting SMEs abandoned by Harvey/Legora
Lexroom demonstrates massive SME legal tech opportunity: grew from €500K to nearly €20M ARR in months by serving small firms ignored by Harvey/Legora. Validates Martín's thesis that 80% of market is underserved.
"Podemos llegar, podemos llegar a competir una legal italiana que hace 2 meses se levantaron 50 millones, ¿correcto? Y han pasado de 500,000 € a casi 20 millones de, o sea, están c…"
38:00
$ANTHROPIC
Anthropic
HIGHmartín manén·itnig·3 months ago·SpaceX a bolsa, THEKER levanta $85M y ANTHROPIC genera polémica | Tertulia de itnig· position
Anthropic secondary shares: passed at $8B, invested at $19B, now ~$90B; FTX liquidation created SPV chain risks
Anthropic is a foundational AI model winner-take-most market. Early secondary access via FTX liquidation (500M investment) yielded 165x paper returns. SPV chains create legal enforceability risks. Cursor acquisition for $60B in stock shows vertical integration into coding agents.
"Y al cabo de dos o tres semanas decía, "No, qué tonto, qué tonto, qué tonto." Y yo dije, "Esto es un patrón." Yo tengo la suerte de haber visto el patrón de internet, del móvil, d…"
56:00
$GROQ
Groq
MEDmartín manén·itnig·3 months ago·SpaceX a bolsa, THEKER levanta $85M y ANTHROPIC genera polémica | Tertulia de itnig· position
Grock AI chip startup acquired by Nvidia for $20B (license + team); neocloud spinout Grock 2.0 raised $650M
Nvidia acquired Grock's team and non-exclusive license for $20B (antitrust structure). Grock retained neocloud inference data centers (Grock 2.0), raised $650M at high valuation. Martín invested via SPV, received dividends, reinvested. Neoclouds benefit from infinite inference demand.
"Grock la de chips, inferencia que compró Nvidia por por 20 billion. Esto, la operación salió el 23 de diciembre del año pasado, compró una licencia no exclusiva por temas de monop…"
60:00
8
AI Applicationstailwind
Legal AI bifurcates: elite firms captured by Harvey/Legora ($15K/seat), 80% SME market wide open for vertical players
Harvey and Legora focus on top-tier firms with high-touch sales, leaving SME segment (millions of small firms) underserved. Lexroom (Italy) proved SME traction: €500K to ~€20M ARR in months. Martín launching Pacion AI with proprietary legal RAG/context to compete. Winner-take-most dynamics in each segment.
7
AI Infrastructuretailwind
Neoclouds and inference data centers emerge as critical layer; model companies vertically integrate compute
Grock 2.0 (neocloud) raised $650M for inference infrastructure. Anthropic acquired Cursor ($60B stock) partly for its compute/data center relationships. Google/Nvidia contracts with model companies are cancelable, creating revenue risk. SpaceX buying Cursor shows convergence of space/compute. Infinite inference demand drives neocloud valuations.
7
AI Economics & Business Modelsrisk
Secondary market SPV chains create enforceability risks; model distillation/cloning reduces dependency on frontier labs
Anthropic secondary shares traded via multi-layer SPVs (FTX liquidation → SL → SL → investor). Anthropic now refuses to recognize certain SPV titles, creating litigation risk at IPO. Cursor cloned Chinese model (likely DeepSeek) to replace Haiku, cutting cost and vendor risk. Fine-tuning open models for specific tasks beats training from scratch for most applications.