u/ZookeepergameSafe429

[ Ai + human ] Vs [ Same Ai + skilled human ] - Engineering Perspective
▲ 1 r/rfelectronics+1 crossposts

[ Ai + human ] Vs [ Same Ai + skilled human ] - Engineering Perspective

https://preview.redd.it/hu7ja0l7jhug1.jpg?width=1024&format=pjpg&auto=webp&s=1238fbc3e956fc9b47533712bfe30964f1cd50bb

I recently received a technical specification for a 200kHz radio system (you will spot the problem instantly , but AI didn't ) . On the surface, the document looked flawless—properly formatted, full of industry jargon, and clearly generated by a high-end LLM.

But as an engineer with 27 years in the field, I spotted the "hollow" center within seconds.

The document was 1 page long, it never once mentioned a Link Budget. It didn't specify the Transmitter Power (e.g., 10dBm). It didn't account for path loss or the receiver's noise floor.

To a layman, the AI gave them a "complete" plan. To a seasoned RF engineer, it gave them a physical impossibility.

The Multiplier Effect: $Skill \times AI$

We often talk about AI replacing people, but we aren't talking enough about how AI amplifies the gap between the amateur and the expert.

The Unskilled + AI: They use AI to generate knowledge they don't have. They don't know that a 200kHz link is meaningless without a link budget, so they don't ask for it. The result is a "flat" specification—it looks like a plan, but it won't work in the real world.

The Skilled + AI: We use AI to accelerate the expertise we already possess. We don't ask the AI "what is a transmitter?" We tell the AI: "Calculate the link budget for a 200kHz system at 10dBm with a -110dBm sensitivity requirement in an urban noise environment."

AI is a Mirror, Not a Guru

The AI is not yet "ready" to tell a client their specification is incomplete. It is a tool that fulfills a prompt. If the prompt lacks the "engineering punch"—the specific constraints like power levels, impedance matching, or thermal limits—the AI will happily hallucinate a generic solution.

The "50 Missing Things":

In any professional specification, there are 50 nuances that only come from years in the lab with an oscilloscope and a VNA. If you don't know those 50 things exist, you can't prompt for them.

The Verdict

Skill doesn't just "matter" in the age of AI; it has become the ultimate differentiator.

If you are using AI to hide a lack of fundamental knowledge, the mask is paper-thin to anyone who actually knows the physics. But if you are an expert using AI to handle the heavy lifting, your "punch" becomes exponential.

True authority isn't about the tool; it’s about having the wisdom to know what’s missing from the output.
#RFEngineering #HardwareDesign #AI #EmbeddedSystems #TechLeadership #EngineeringExcellence #LinkBudget #ElectronicsEngineering

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▲ 1 r/robotics+1 crossposts

Sharing Enlightment: The experiment's results

https://preview.redd.it/4db513rjchtg1.png?width=1371&format=png&auto=webp&s=18e47c8b225141a0aef377fc52db2bda21f3436c

Most engineers simulate. Few build.

This week: a closed-loop velocity controller on an N20 encoder motor. Here's what two plots taught me that no simulation would.

📊 What I measured vs what I predicted:

The ripple in steady-state RPM (±2 RPM) looks like noise. It isn't. It's quantization — 363 counts/rev × 50ms sample window × 71 RPM = only 21 pulses per sample. One extra pulse = a visible RPM spike. Predictable from first principles. Fixable by design.

The motor settled at 71 RPM with PWM locked at 100% when the target was 140 RPM. Controller saturated. Motor physically couldn't deliver what was being asked. It kept trying anyway — because proportional control has no way to know it has hit a physical wall.

Two engineering lessons no simulation teaches: → Always log PWM alongside your process variable. A saturated controller looks identical to a broken one unless you do. → Quantization error is not random — it is deterministic and calculable before you build. Design your sample rate to your encoder resolution, not the other way around.

This is one step in a longer project: a complete motor position controller built from transfer functions and system identification, leading to a 3-axis position-holding underwater vehicle.

Every layer is built on measured reality, not assumed parameters.

That's the only kind of engineering I know.

#ControlSystemsEngineering #EmbeddedSystems #MotorControl #FirmwareDevelopment #RoboticsEngineering #HardwareEngineering #SystemsEngineering

https://preview.redd.it/xhtvd6klchtg1.png?width=1459&format=png&auto=webp&s=5ada8ab24f5977e93132c8aee4eeabf257387723

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u/ZookeepergameSafe429 — 6 days ago