March 28, 2026
Fake it till you ship it
The risk of AI isn't making us lazy, but making "lazy" look productive
If it ships and stays up, who cares who sweated — or are we rewarding fake hustle
TLDR: A developer used AI chatbots to rapidly learn electronics and speed up coding while keeping human oversight. Commenters split between results-over-effort, fears of performative productivity, and excitement about AI as a learning superpower, signaling a culture shift in how we value work and expertise.
One maker used an AI chatbot to tear down a guitar pedal, rebuild the design, and basically teach themselves a mini–electronics course in a week. Then they described a “human-in-the-loop” coding style: AI drafts, they review, no slop shipped. The community? Absolutely buzzing. The loudest camp is pure results-first: “If the bridge stands, who cares how many hours you suffered?” cheered one commenter, echoing the author’s vibe that AI is a 24/7 tutor that turns “someday” into “done.” Another crowd went philosophical-spicy: if AI makes you look busy, is that… the same as being productive? Cue the existential eye-twitch. One poster even declared that “looking productive” and “being productive” will blur into one — cue the popcorn.
On the wholesome side, folks loved using AI to decode dense books and papers, calling it an “unbelievable boost” for understanding. Others took the middle path: go deep on what matters, skim fast with AI on the rest, a choose-your-own-effort adventure. The memes flew: “vibe coding,” “fake it till you ship it,” and “AI is your TA that never sleeps.” Meanwhile, guitar nerds nodded at the shout-out to the Surfy Industries Stereomaker, politely asking, “ok but does it slap in mono?” In short: AI as cheat code or cosplay? The internet can’t decide — but they’re definitely shipping things faster.
Key Points
- •The author reverse engineered a Surfy Industries Stereomaker pedal that creates stereo from mono using a five‑stage all‑pass filter without delay.
- •They used ChatGPT to learn audio circuit concepts, including transformers, JFET soft‑switching, ground lifts, diode bridges, TS/TRS handling, transformer phase, and adding a 10 dB attenuation switch.
- •They moved from PCB analysis to implementing a custom cascade design in KiCad, editing netlists and reasoning about capacitor values with AI support.
- •The process enabled a self‑directed, intensive learning sprint completed in about a week, making a previously deferred project achievable.
- •For software, they employ a disciplined AI workflow via Gemini chat and copy‑pasted code to resolve Pylance issues, build a CSS/HTML toggle switch, and clarify Python context managers while maintaining quality control.