LLMs as Essential Maker Copilots | Generated by AI

Home 2026.02

Question: Is it true that when doing anything new or physically challenging nowadays, like Arduino, Raspberry Pi, or Pico projects and building robots, we need to keep a laptop open with AI chatbots running because LLMs act as our second brain for instant questions and understanding what’s happening?

Answer:

Yes, that’s very accurate for 2025–2026 — especially for most hobbyists, students, and even many professional engineers working on embedded systems, robotics, or any hardware+software project.

Why LLMs have become almost mandatory “second brains” for these kinds of projects

  1. Extremely wide surface area of knowledge needed
    You simultaneously need to understand:
    • Basic & advanced electronics
    • Multiple programming languages (MicroPython, CircuitPython, Arduino C++, Rust, C)
    • Different frameworks & libraries per platform
    • Pinout differences between dozens of boards
    • Communication protocols (I2C, SPI, UART, CAN, OneWire, etc.)
    • Sensor/actuator datasheets & quirks
    • Power supply rules, current limits, voltage levels
    • Debugging strange hardware behavior
      No single human keeps all of this in fast-access memory anymore.

  2. Real-time “just-in-time” learning beats pre-studying
    When the servo jitters, the I2C device doesn’t ACK, the NeoPixel strand shows wrong colors, or the motor driver gets hot → you want the answer in 15–40 seconds, not after reading three forum threads and a datasheet.
    Modern LLMs (especially ones with up-to-date knowledge) usually give a good first 80–90% answer instantly.

  3. Typical workflow in 2026 looks like this
    • Breadboard / PCB in front of you
    • Multimeter + oscilloscope (if lucky)
    • Code editor open
    • Large LLM window always visible (often two tabs: one general model, one specialized / long-context model)
      People constantly alt-tab or split-screen between:
    • “explain this error from picowgo / arduino-cli”
    • “why is my MPU6050 giving 32767 on all axes?”
    • “give me safe way to drive 4 A4988 steppers from Raspberry Pi Pico”
    • “convert this Arduino sketch to MicroPython for RP2040”
  4. Edge cases where you still mostly don’t need it (but they’re becoming rarer)
    • Repeating exactly the same project you’ve built 20+ times
    • Following a very well-tested kit with perfect instructions (e.g. official Elegoo / SunFounder / Hiwonder robot kits)
    • Doing extremely low-level bare-metal work where every datasheet paragraph matters and you’re already an expert

For almost everyone else — especially when

→ the laptop-with-LLM is basically open 95–100% of the active project time.

Bottom line in one sentence

In 2026, for physical computing / robotics / maker hardware projects, the laptop + always-on LLM chat has become infrastructure — very similar to how nobody today would try serious software development without Stack Overflow / GitHub / official docs tabs open. The LLM just collapsed ten tabs into one very fast, conversational tab.

So yes — you’re describing the current normal state for most people in the field.

References:

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