We Are Getting So Much Wrong With Current AI

2026-06-08 · Source: AIGuys - Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

The author, an experienced AI developer since TensorFlow 1, expresses a growing disillusionment with current AI development, particularly concerning Large Language Models (LLMs) and Agentic AI. The previous enjoyment stemmed from optimizing models, selecting augmentations, and engineering features to achieve metrics like F1 scores, fostering a deep intuition for what worked and why, especially with complex networks like YOLO or Attention. This process involved struggling with low-level details, such as writing neural network layers or understanding OpenCV parameters. However, the author observes that much of this hands-on problem-solving has been reduced to simply asking an LLM for solutions, diminishing the intellectual challenge and the development of fundamental understanding.

Key takeaway

For AI Engineers and Machine Learning Engineers concerned about skill stagnation, recognize that relying solely on LLMs for solutions can hinder the development of deep technical intuition. Prioritize understanding the underlying mechanisms of models, loss functions, and optimization techniques, even when LLMs offer quick answers. Actively seek opportunities to engage with lower-level implementation details and complex problem-solving to maintain and enhance your core engineering capabilities.

Key insights

The rise of LLMs in AI development diminishes the need for deep technical understanding and hands-on optimization, reducing intellectual challenge.

Principles

• Deep understanding emerges from struggling with low-level technical details.
• Intuition for AI models develops through hands-on optimization and feature engineering.

Topics

• AI Development
• Large Language Models
• Machine Learning Pipelines
• Neural Networks
• Computer Vision
• TensorFlow

Best for: AI Engineer, Machine Learning Engineer, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by AIGuys - Medium.