BootLoop Built an AI Agent That Writes Firmware and Tests It on Real Hardware

The Macro: Firmware Engineering Is the Hardest Software Job Nobody Talks About

I need to explain why firmware is different from every other kind of software, because the distinction matters for understanding why an AI firmware agent is both harder to build and more valuable than an AI web development agent.

Firmware is the code that runs directly on hardware. It controls the microprocessors in your car’s braking system, the sensor arrays in industrial robots, the communication modules in satellites, and the motor controllers in drones. When firmware has a bug, you cannot push a hotfix. The device might be sealed in an enclosure on the factory floor. It might be orbiting the Earth. It might be responsible for keeping a patient alive. The margin for error is essentially zero.

Writing firmware requires a combination of skills that is rare and getting rarer. You need to understand hardware schematics, read thousand-page datasheets from chip manufacturers, write code in C or C++ that operates under severe memory and timing constraints, and debug problems using oscilloscopes and logic analyzers. A firmware engineer needs to think about clock cycles, interrupt priorities, DMA channels, and voltage levels. A web developer thinks about none of those things.

The talent shortage is acute. There are roughly ten times more web developers than firmware engineers in the workforce. The semiconductor industry’s growth, the explosion of IoT devices, the rise of autonomous vehicles, and the push into space technology have all increased demand for firmware engineers while the supply has barely grown. Companies routinely wait six months to fill firmware roles. Defense contractors and aerospace companies offer signing bonuses that would make a Bay Area software engineer blush.

The tools have not helped. While web and mobile development got VS Code, GitHub Copilot alternatives, and sophisticated CI/CD pipelines, firmware development is still largely done in vendor-specific IDEs that feel like they were designed in 2005. Testing happens manually on physical hardware. There is no Vercel for firmware. There is no Netlify for embedded systems. The workflow is slow, error-prone, and expensive.

AI coding assistants have transformed web development but barely touched firmware. The reason is straightforward. Training data. There are millions of open-source web applications on GitHub. There are comparatively few open-source firmware projects, and the ones that exist are highly device-specific. An AI that can write a React component cannot write a SPI driver for a specific sensor connected to a specific microcontroller without understanding the hardware context.

The Micro: A SpaceX Firmware Engineer and an MIT Researcher Building the Tool They Needed

BootLoop is an AI agent that reads hardware documentation, writes firmware code, and tests it on real physical hardware. You give it datasheets, schematics, and design files. It generates production-ready embedded code in C, C++, or Rust. Then it validates that code using hardware-in-the-loop testing with oscilloscopes and logic analyzers.

Noah Pacik-Nelson is CEO and Chris Markus is CTO. They are based in San Francisco, part of Y Combinator’s Summer 2025 batch, with a three-person team. The founder credentials here are not just relevant, they are essential. Markus was the lead software engineer for SpaceX’s Starship booster catch system. He built Raptor engine firmware from first fire to flight. He also built FDA-authorized ventilator firmware. Pacik-Nelson researched AI agents at Accenture’s AI Refinery and neuromorphic computing at MIT Media Lab and holds patents in digital signal processing and energy harvesting.

This is a team that has written the kind of firmware that most engineers only read about in case studies. When they say the firmware development process is broken, they are speaking from the experience of building systems where firmware failures can result in a rocket exploding or a patient dying.

The hardware-in-the-loop testing is what separates BootLoop from any AI coding tool that can generate C code. Writing firmware that compiles is easy. Writing firmware that actually works when connected to physical hardware is hard. The signals need to be correct. The timing needs to be right. The interrupts need to fire in the right order. BootLoop connects to real test equipment and validates that the generated code behaves correctly at the electrical level. That is a fundamentally different level of verification than running unit tests in a simulator.

The ITAR compliance and on-premise deployment options signal that BootLoop is targeting defense and aerospace customers, which makes sense given the founders’ backgrounds. These are organizations that cannot use cloud-based coding tools for classified projects. They need software that runs entirely within their secure facilities. The zero data retention model addresses the same concern. If you are writing firmware for military hardware, you cannot have your code passing through external servers.

The pilot program approach with forward-deployed engineering support is the right go-to-market for this kind of product. Firmware development is too specialized and too high-stakes for a self-serve model at launch. You need engineers on-site who understand both the AI system and the customer’s hardware. That does not scale infinitely, but it builds trust and generates the case studies needed to expand.

The Verdict

BootLoop is building for one of the few remaining software domains where AI has not yet made a meaningful impact. The combination of sparse training data, hardware-specific constraints, and safety-critical requirements has kept firmware engineering largely manual. If BootLoop can generate firmware that passes hardware-in-the-loop testing consistently, they will have built something with no real competitor.

The closest comparisons are general-purpose AI coding assistants like Cursor, Codeium, or Tabnine, but those tools generate suggestions that a human evaluates. BootLoop generates complete firmware and validates it against physical hardware. That is a different product category. In the embedded space, PlatformIO modernized the build toolchain and SEGGER improved debugging, but neither generates code.

In thirty days, I want to know the scope of hardware platforms BootLoop supports. Can it write firmware for an STM32? A Nordic nRF52? An Espressif ESP32? The embedded world is fragmented across dozens of microcontroller families, and each one has different peripherals, registers, and toolchains. Breadth of platform support determines the addressable market. In sixty days, the question is how many iterations the AI needs before producing working code. If it generates correct firmware on the first attempt 80% of the time, teams will adopt it immediately. If it takes ten iterations of feedback from the test harness, it is a nice demo but not a productivity tool. In ninety days, I want to see whether the generated code is production-quality or prototype-quality. Code that works on a bench is one thing. Code that handles edge cases, error recovery, and worst-case timing constraints is another. The SpaceX pedigree suggests this team knows the difference. That is the bet.