Raw LLM Responses
Inspect the exact model output for any coded comment.
Look up by comment ID
Random samples — click to inspect
in
That headline is doing work the study never asked for. The MIT “Your Brain on Ch…
7464304238295…
in
The honest version of the Microsoft / Uber story isn't "AI is too expensive." It…
7465622368929…
in
Maybe fire those ungrateful AI agents and replace them with human scab labor... …
7464070446263…
in
The shift from isolated tutorials to open-sourcing actual enterprise-grade, prod…
7463135266371…
in
Companies mentioned in connection with reduced, limited, or reassessed AI spendi…
7466260181161…
in
Biggest mistake I see people make... they test Claude with fake work. Use it on …
7464739542424…
in
Google I/O is a useful AGI checkpoint because DeepMind is packaging capability i…
7463549834189…
in
The SynthID expansion is the most underrated announcement here. Watermarking sol…
7463334105229…
Comment
This is the correction phase of the AI hype cycle that many experienced engineers expected. AI absolutely boosts productivity, but “replace engineers” was always a flawed framing. Engineering is not just code generation — it’s architecture, trade-offs, debugging ambiguous failures, domain understanding, operational ownership, and long-term maintainability. What many companies underestimated:• Token economics at enterprise scale• Context-window inefficiencies on large codebases• Human review overhead• Hallucination-driven rework• The cost of bad architectural decisions generated confidently at high speed The real winning model is likely to be:Small, highly skilled engineering teams + AI augmentation — not AI replacing teams entirely. The companies getting the best ROI from AI today are usually the ones using it as a force multiplier for senior engineers, not as a wholesale substitute for engineering judgment.
LinkedIn
Workplace & Jobs
Principal Software Engineer | Distributed Syste…
2026-05-26T15:4…
Coding Result
| Dimension | Value |
|---|---|
| Primary value | human_autonomy |
| Secondary value | none |
| Alignment target | workers |
| Stance | demanding |
| Emotion | approval |
| Value justification | The speaker emphasizes the importance of human engineering judgment and the limitations of AI in replacing engineers, highlighting the need for human autonomy in decision-making. |
| Target justification | The speaker is primarily concerned with the impact of AI on engineering teams and the importance of using AI as a force multiplier for senior engineers, indicating a focus on workers. |
| Coded at | 2026-06-11T08:17:50Z |
Raw LLM Response
```
{
"value_primary": "human_autonomy",
"value_secondary": "none",
"target": "workers",
"stance": "demanding",
"emotion": "approval",
"value_justification": "The speaker emphasizes the importance of human engineering judgment and the limitations of AI in replacing engineers, highlighting the need for human autonomy in decision-making.",
"target_justification": "The speaker is primarily concerned with the impact of AI on engineering teams and the importance of using AI as a force multiplier for senior engineers, indicating a focus on workers."
}
```