Raw LLM Responses
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in
Using WALL-E as a futuristic reference for “taking care of all our problems” mis…
7465021757649…
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Haha this is quite funny actually. I think there is going to be a reality, as El…
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in
AI agents are programmed by humans and are not 100% autonomous. Numerous filters…
7463967613690…
in
One big question that stopped me while learning AI/LLMs: Till now, I understood …
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in
For entry level positions AI isxa big threat because their tasks are typically t…
7466051763377…
in
I thought AI slop online couldn't get any worse, proven wrong by this. If there …
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“The issue is not capability. It’s who benefits.” That’s the real AI conversatio…
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🚨 Silent UI Fragmentation: The legacy, single-tap TTS "Speaker" integration was …
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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."
}
```