TickerTain
TickerTain
NewsroomShortsPortfolioConvergence
NewsroomShortsPortfolioConvergence
$ANTHROPIC·$MA····$INTC····$BLUE-ORIGIN·$SPCX····$CRWV····$CRM····$MSFT····$NVDA····$ORCL····$CURSOR·$AAPL····$OPENAI·$AMZN····$UBER····$GOOGL····$META····$TSLA····$DATABRICKS·$PERPLEXITY·$LYFT····$NBIS····$TSM····$LITE····$ANDURIL·
$ANTHROPIC·$MA····$INTC····$BLUE-ORIGIN·$SPCX····$CRWV····$CRM····$MSFT····$NVDA····$ORCL····$CURSOR·$AAPL····$OPENAI·$AMZN····$UBER····$GOOGL····$META····$TSLA····$DATABRICKS·$PERPLEXITY·$LYFT····$NBIS····$TSM····$LITE····$ANDURIL·
←

garry tan

T2 · manager / operator

Garry Tan is the CEO of Y Combinator. He founded Posterous (YC 2008, acquired by Twitter for ~$20M) and later rebuilt it as Posthaven. He co-founded Initialized Capital (now run by Brett Gibson). After a 13-year coding hiatus, he returned to building using AI coding agents (Claude Code, Codex, OpenClaude), shipping hundreds of thousands of lines of code while running YC full-time. He built Garry's List (political advocacy platform), G Stack (agentic engineering framework), and G Brain (open-source personal AI).

2 calls·2 names·100% bull·last heard 2 months ago·Y Combinator
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
$EMERGENTEmergent

Emergent hits nine-figure revenue in eight months with 15-person team

Emergent demonstrates the new physics of AI-native companies: achieving $100M+ ARR with only 15 people by leveraging AI agents as a workforce rather than autocomplete, breaking historical revenue-per-employee records across all industries.

Y Combinator2026-08episode →
2ndhigh conviction
$RETAILRetail

Retail reaches $60M ARR with 40 people in winter 24 batch

Retail exemplifies the AI-native company model: $60M annualized revenue with ~40 employees, validating that the fastest-growing YC founders treat AI as a workforce multiplier across all functions, not just coding.

Y Combinator2026-08episode →

most discussed · click a bar to filter

  • $EMERGENT
  • $RETAIL

recurring themes

  • AI Economics & Business Models5
  • Open Source AI4
  • AI Coding Agents3
  • AI Infrastructure3
  • AI Agents2
2 total
$EMERGENT
Emergent
HIGHgarry tan·Y Combinator·2 months ago·Garry Tan: The Future of AGI Is Personal
Emergent hits nine-figure revenue in eight months with 15-person team
Emergent demonstrates the new physics of AI-native companies: achieving $100M+ ARR with only 15 people by leveraging AI agents as a workforce rather than autocomplete, breaking historical revenue-per-employee records across all industries.
"Emergent out of our summer 24 batch went from public launch to nine figures of revenue in eight months. When they crossed $15 million in annualized revenue, they were 15 people. T…"
22:10
$RETAIL
Retail
HIGHgarry tan·Y Combinator·2 months ago·Garry Tan: The Future of AGI Is Personal
Retail reaches $60M ARR with 40 people in winter 24 batch
Retail exemplifies the AI-native company model: $60M annualized revenue with ~40 employees, validating that the fastest-growing YC founders treat AI as a workforce multiplier across all functions, not just coding.
"Retail winter 24 hit 60 million annualized with about 40. That revenue per person did not exist before. Not in software, not in oil, not in railroads. And these aren't freaks of n…"
22:25
9
AI Coding Agentstailwind
Garry Tan achieves 400x coding leverage directing 15 AI agents via markdown skills
Garry Tan describes a new 'agentic engineering' paradigm where a single builder directs dozens of AI agents (Claude Code, Codex, OpenClaude) through markdown-based 'skills' that act as harnesses, achieving 400x logical lines of code vs 2013 baseline. The workflow combines deterministic testing (80-90% coverage) with LLM latent space for judgment, enabling solo builders to ship production systems at unprecedented velocity.
9
AI Agentstailwind
Garry Tan: Personal AGI agents compound daily as owned workforce, not rented subscriptions
Personal AGI agents running on user-owned infrastructure with proprietary context compound value daily, unlike corporate AI which only improves when the vendor ships updates. The leverage comes from context and harness, not model weights.
9
AI Coding Agentstailwind
Garry Tan: 8-400x coding productivity gains from agents; fastest YC founders treat AI as workforce not autocomplete
Founders using agents as a full workforce (not autocomplete) achieve 8-400x productivity multipliers across all knowledge work. YC data shows AI-generated codebases correlate with fastest-growing, most profitable batches.
9
AI Coding Agentstailwind
Garry Tan demonstrates 400x personal coding leverage via agents
Tan quantifies personal productivity gains from coding agents (400x raw, 8-100x after penalties) and shows YC portfolio data: 25% of W25 batch had 95% AI-generated codebases and became fastest-growing batch. The leverage comes from context/harness quality, not model weights, making agent orchestration tools the key differentiator.
9
AI Agentstailwind
AI agents as workforce not autocomplete drives 100x founder leverage
The highest-leverage founders treat AI agents as a managed workforce — giving them owned context, deterministic tooling, and recurring skill files — rather than as chat assistants, producing 8-400x personal productivity gains and unprecedented revenue-per-employee metrics.
9
AI Infrastructuretailwind
Personal AGI architecture: rented model + owned context + harness = compounding asset
Tan defines Personal AGI as a three-layer stack: frontier models (commodity, rented), personal context library (unique, owned), and harness/skill files (owned). He argues model improvements increase the value of owned context, creating a moat. Investment implication: the infrastructure layer for personal context management and skill orchestration is a new investable category.
9
AI Economics & Business Modelstailwind
Revenue per employee explodes as AI-native companies break historical scaling laws
AI-native startups like Emergent ($100M ARR, 15 people) and Retail ($60M ARR, 40 people) achieve revenue-per-employee ratios impossible in software, oil, or railroads, because one founder plus agents replaces entire functional departments, fundamentally rewriting unit economics of knowledge work.
9
Enterprise AI Adoptiontailwind
Context engineering and artifact recording enable organizational superintelligence
Recording all meetings, transcripts, and artifacts creates a shared organizational brain. Agents that meta-prompt on this corpus (dream cycles) continuously improve skills — e.g., YC's two-sentence pitch skill now outperforms individual partners. This compounding loop is the micro-mechanism for building superintelligence inside companies.