>>Pretty soon no one is going to read any of the code AI produces and that's a scary thought.

>This is a misconception. Have your favorite agent *summarize this video for you*: https://www.youtube.com/live/zcLPGC-tvgk?si=YR68aHlFESD053bh

I can't tell if you're joking here

▲ brlewis a day ago | parent [-]

I am not generally against using AI to reduce the amount of information you need to pay attention to, and I was not joking. There are multiple places in that interview with good articulation of the reasons why software fundamentals still matter, and what happens when you don't look at at least some of the AI-generated code.

▲ zahlman 14 hours ago | parent | next [-]

> There are multiple places in that interview with good articulation of the reasons why software fundamentals still matter, and what happens when you don't look at at least some of the AI-generated code.

Sure, I've seen the video before and remember many of the arguments. I don't agree with everything in Bob's approach, but I certainly agree with what he says about the value of looking at the code.

But that doesn't at all mean that people will do it.

▲ drawfloat a day ago | parent | prev [-]

Why don't you just quote them then? Or quote whatever the LLM you used gave.

▲ brlewis a day ago | parent [-]

Uncle Bob Martin and Matt Pocock discuss the risks of relying on AI agents without human oversight, emphasizing that unchecked code can lead to significant technical issues:

   - Accumulated Technical Debt: Uncle Bob notes that agents often leave behind "dog doo" (messy code) (05:13-05:18). If you don't clean it, the code becomes progressively worse as you build on it (11:06-11:10).
   - Loss of Agent Coherence: When code quality degrades, agents struggle to maintain direction (11:13-11:16). They may enter a loop of inadvertently breaking existing features while attempting to fix new ones, eventually leading to them failing entirely or giving up (11:22-12:04).
   - The "Trapped" Trajectory: Matt Pocock highlights the risk of a session's "trajectory" (23:18-23:45). Without intervention, an agent's initial messy approach or misaligned focus will continue throughout the entire session, reinforcing poor patterns instead of correcting them (23:35-24:00).
   - Hidden Hallucinations: Even though agents are fast, they are still prone to hallucinations and misalignment (25:09-25:18). Relying on them blindly without deterministic tools or human spot checks risks incorporating silent, logic-breaking bugs into the architecture (09:08-09:19).

	▲	zahlman 14 hours ago \| parent [-]
		Your comment got flagged and killed; I don't know whether automated systems attempt to detect AI-generated comments. I vouched for you because the content was explicitly solicited.