Embedder and Joulescope Automate Firmware Power Optimization
Wearable battery life is won or lost in the milliseconds between sleep and active states, a transition that has long required manual, bench-bound tuning. Embedder and Joulescope are now closing that loop, pairing an AI firmware agent with high-precision current measurement to automate power optimization on real silicon.
The integration leverages the newly launched Joulescope JS320, which captures currents as low as 0.1 nanoamps. By connecting this hardware to Embedder’s AI coding agent, developers can automate the iterative process of firmware refinement. The agent ingests device datasheets and schematics to write code, then flashes the board to measure the exact energy cost of every operation. If a firmware modification fails to meet power targets, the system iterates autonomously until the budget is satisfied.
Beyond initial development, this setup acts as a persistent guardrail for hardware teams. Every new commit undergoes real-world power measurement, ensuring that regressions—such as a silent spike in sleep current—are caught before reaching production. Matt Liberty, creator of Joulescope, described the integration as a "cheat code" for battery life, while Embedder CTO Bob Wei noted that the partnership formalizes a workflow already gaining traction among startups and large enterprises. The platform currently supports over 500 hardware platforms and 3,600 peripherals, with the full integration available immediately via embedder.dev.
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