How AI Is Changing FPGA Design
AI-assisted development is changing more than turnaround time in FPGA and embedded vision design — it's changing how much verification is realistically possible within a given project timeline. Concurrent EDA has spent the past several months integrating AI coding tools into its engineering workflow and has seen the impact firsthand.
A Compiler-Level Shift
The last comparable inflection point in software and hardware design was the shift from hand-assembled machine code to compiled high-level languages, a change that allowed engineers to work at a higher level of abstraction while a compiler handled translation into executable instructions. AI coding assistants represent a similar leap: A detailed specification can now generate a working implementation directly. The scale is not insignificant. Concurrent EDA's engineering team produced roughly 600,000 lines of code in a single month using these tools, a volume that would take conventional hand-coding far longer to reach.
Testing and Validation Payoff
Faster code generation isn't the most consequential part of this shift though; more thorough testing is. Development has traditionally leaned on functional verification: confirming a design behaves correctly under expected conditions and then moving on. AI-assisted workflows go further by checking that every line and every logical branch of a design have been exercised during testing. That level of coverage analysis used to demand more engineering time than most schedules allowed. Now, it's a standard part of the process.
For engineering teams evaluating a custom camera or embedded processing project, AI-assisted workflows mean faster, more rigorously tested FPGA development, which allows Concurrent EDA to move a high-data-rate application from concept to a reliable, deployed solution faster and at lower engineering cost — without cutting corners on the testing that real-time, high-speed systems demand.
Need to solve data challenges fast? Watch the full Manufacturing Matters Podcast episode with Ray Hoare here. Have a project where AI-assisted design and rigorous testing could help? Contact Concurrent EDA to talk through your idea.
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