Technical Insights
Deep-dive whitepapers on synthesis optimization, power analysis, timing closure, and the future of EDA — written by engineers, for engineers.
How Chip Design Startups Are Using AI to Compete with Larger Semiconductor Companies
How AI-Native Workflows Are Helping Startups Cut Design Cycles in Half and Challenge Industry Giants
AI-powered EDA tools are enabling chip design startups to achieve 6-9 month tape-out cycles, autonomous RTL generation, and cloud-native flows that challenge Intel, AMD, and Nvidia on speed and cost.
LLMs in Chip Design: What Large Language Models Can and Cannot Do for EDA
A Practitioner's Guide to LLM Strengths, Limitations, and Agent-Driven Workflows in EDA
LLMs accelerate RTL generation, EDA scripting, and spec translation-but fall short on timing closure, physical design, and formal verification. Learn where AI adds value in chip design and where human expertise remains irreplaceable.
How AI Is Reducing Chip Design Costs for Fabless Semiconductor Companies
The End of the $50 Million ASIC: How AI is Slashing Chip Development Costs.
Chip design costs have hit $50M+ per ASIC, with 70% going to labor. AI-native tools cut team sizes by 50%, shrink 24-month cycles to 12, and replace $2M EDA licenses with cloud platforms. A cost breakdown and implementation strategy for fabless companies.
What is AI-Driven EDA? How Artificial Intelligence Is Transforming Chip Design
From Weeks to Hours: How ML Is Compressing the Chip Design Cycle
AI-driven EDA embeds machine learning into RTL generation, verification, and physical design, compressing chip development cycles, improving PPA, and enabling design teams to ship custom silicon faster without replacing existing tool flows.