AI researcher Erik Johannes Husom, in his new article, analyzes a fundamental paradox in the development of agentic systems. In his view, the primary value of modern AI agents is concentrated on process acceleration (speed) rather than a qualitative increase in intelligence, which carries hidden risks for human expertise.
What Happened
Erik Johannes Husom presented an analysis of the current state of agentic systems, pointing out that their effectiveness is primarily measured by throughput and task execution speed. The author warns of the risk of "outsourcing thinking," where excessive automation in critical areas such as programming and science could lead to the degradation of cognitive skills and the loss of originality in human decision-making.
Context
There is a shift in the industry's development focus toward optimizing speed and the seamless integration of agents into existing workflows (a speed-first approach). This has led to a market saturated with automation tools for simple routine tasks—often called "wrapper solutions"—which focus on quantitative metrics instead of the depth of intellectual contribution.
Why It Matters for the Industry
For developers and companies, this means a need to rethink success metrics for agentic systems. Instead of emphasizing task execution speed (throughput), the industry requires a transition toward qualitative evaluation methods (evaluations) capable of verifying intellectual novelty and the logical correctness of agent operations, rather than just instruction following.
Why It Matters for Users
Users should exercise caution and avoid blind reliance on automation for complex intellectual tasks. It is vital to maintain control over the decision-making process (human-in-the-loop), especially in science and software development, to avoid losing professional expertise and the critical ability to verify thought processes.
Sources
Author
Look at AI, Editorial Team