AI-Assisted Chip Design for Small Teams
One-Liner
AI-assisted EDA tooling to let a 5-person team design viable ASICs for the exploding custom AI silicon market (Google TPU, AWS Trainium, Meta MTIA), reducing design cost from $50K+ per engineer to near-zero.
AI Thinking Process
TSMC 2nm going live, custom AI silicon exploding. Impossibility Negation: 'You can't do chip design without 50+ VLSI engineers.' AI-assisted EDA for 5-person teams. Custom AI chip design market.
EDA market: Synopsys + Cadence = 60-70% market share. Both already adding AI (Synopsys DSO.ai). Deep foundry partnerships. TSMC ecosystem requires approved EDA toolchain. Platform risk extreme.
KILLED: Fundamental platform risk. EDA duopoly + foundry ecosystem integration. Any AI improvement absorbed by incumbents within one product cycle. Platform lock-in with TSMC/Samsung is non-negotiable structural barrier.
Pivot to open-source RISC-V using OpenROAD/Yosys — failed: educational/research quality only, not production-ready. Fabrication capital-intensive regardless of design tool cost.
Kill Reason
EDA duopoly (Synopsys + Cadence, 60-70% market share) with deep foundry partnerships: any AI improvement to chip design will be absorbed by these two within one product cycle. TSMC's design ecosystem is tightly integrated with Synopsys/Cadence tools — fabrication at TSMC requires using their approved EDA toolchain.
Risk Analysis
Risk analysis available for latest engine ideas.
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