Firmware
In embedded systems development, there's a particularly frustrating class of bugs that every developer encounters: code that works perfectly in debug mode but mysteriously fails when compiled for release. At Hoomanely, where we develop precision pet health monitoring devices with clinical-grade accuracy, this phenomenon has taught us valuable
AI
When an edge AI system starts to fail, it rarely fails all at once. Memory pressure creeps up. DMA stalls appear sporadically. Inference deadlines start slipping. Power draw spikes in ways the lab never showed. The question is not whether something will break in production — it’s what you choose
Hardware
In many embedded products, sensors are judged by their datasheet performance: resolution, noise floor, and accuracy. Yet in the field, sensor quality is rarely limited by the sensor itself. It’s limited by what the rest of the system is doing at the same time. Motors spin. Radios transmit. Displays
Software
A production RAG system feels “fast” when it’s consistent: answers arrive quickly, follow-ups don’t suddenly slow down, and costs don’t jump with traffic. The biggest lever to achieve that isn’t usually the model—it’s retrieval. When retrieval is engineered like a disciplined subsystem (with budgets,
Design
When users set up Everbowl for the first time, they are connecting a physical device to a digital experience. Unlike purely app-based onboarding, smart hardware onboarding introduces uncertainty. Users are often unsure whether the device is pairing correctly, connecting to WiFi, or functioning as expected. To address this, we designed
Firmware
Modern embedded systems demand efficient inter-task communication (ITC) mechanisms that balance performance with reliability. When building high-performance sensor systems, every microsecond counts—especially in real-time applications where hardware interrupts must trigger rapid processing pipelines. This exploration examines two fundamental FreeRTOS ITC approaches: traditional queues versus direct task notifications, revealing critical
Hardware
Most modern boards are not powered by a single supply. They are ecosystems of rails: high-current domains for motors or radios, quiet domains for sensors, always-on islands for state retention, and transient-heavy rails that only exist during specific modes. On paper, these rails look independent. In reality, they are tightly
Firmware
Introduction: The Paradox of Hardware-Dependent Firmware In the intricate world of embedded systems development, engineers face a persistent and often debilitating paradox: firmware is explicitly designed to control and react to physical hardware, yet the dependency on that very hardware often becomes the primary bottleneck in software velocity. This creates
AI
The Problem We Kept Chasing When we first rolled out alerts in production, the system technically worked - models were firing, dashboards were lighting up, notifications were flowing. And yet, something felt off. We were seeing too many alerts. Not because the world suddenly became chaotic, but because our inference
Technology, Insights and Ideas.
Software
The App Store Release Bottleneck You've just discovered a critical UX issue in your production app. The fix is simple, reorder two buttons, change a label, maybe adjust a layout constraint. Easy, right? Not quite. You're looking at a minimum two-week timeline: code the fix, test
Firmware
In embedded systems development, there's a particularly frustrating class of bugs that every developer encounters: code that works perfectly in debug mode but mysteriously fails when compiled for release. At Hoomanely, where we develop precision pet health monitoring devices with clinical-grade accuracy, this phenomenon has taught us valuable
AI
When an edge AI system starts to fail, it rarely fails all at once. Memory pressure creeps up. DMA stalls appear sporadically. Inference deadlines start slipping. Power draw spikes in ways the lab never showed. The question is not whether something will break in production — it’s what you choose
Hardware
In many embedded products, sensors are judged by their datasheet performance: resolution, noise floor, and accuracy. Yet in the field, sensor quality is rarely limited by the sensor itself. It’s limited by what the rest of the system is doing at the same time. Motors spin. Radios transmit. Displays
Software
A production RAG system feels “fast” when it’s consistent: answers arrive quickly, follow-ups don’t suddenly slow down, and costs don’t jump with traffic. The biggest lever to achieve that isn’t usually the model—it’s retrieval. When retrieval is engineered like a disciplined subsystem (with budgets,
Design
When users set up Everbowl for the first time, they are connecting a physical device to a digital experience. Unlike purely app-based onboarding, smart hardware onboarding introduces uncertainty. Users are often unsure whether the device is pairing correctly, connecting to WiFi, or functioning as expected. To address this, we designed
Firmware
Modern embedded systems demand efficient inter-task communication (ITC) mechanisms that balance performance with reliability. When building high-performance sensor systems, every microsecond counts—especially in real-time applications where hardware interrupts must trigger rapid processing pipelines. This exploration examines two fundamental FreeRTOS ITC approaches: traditional queues versus direct task notifications, revealing critical
Hardware
Most modern boards are not powered by a single supply. They are ecosystems of rails: high-current domains for motors or radios, quiet domains for sensors, always-on islands for state retention, and transient-heavy rails that only exist during specific modes. On paper, these rails look independent. In reality, they are tightly
Firmware
Introduction: The Paradox of Hardware-Dependent Firmware In the intricate world of embedded systems development, engineers face a persistent and often debilitating paradox: firmware is explicitly designed to control and react to physical hardware, yet the dependency on that very hardware often becomes the primary bottleneck in software velocity. This creates
AI
The Problem We Kept Chasing When we first rolled out alerts in production, the system technically worked - models were firing, dashboards were lighting up, notifications were flowing. And yet, something felt off. We were seeing too many alerts. Not because the world suddenly became chaotic, but because our inference