The Prompt Engineering Bubble
Prompt engineering as a career is a bubble. As models improve, the skill becomes less valuable, not more....
Cutting through AI hype with practical observations. What works, what doesn't, and what the vendors aren't telling you.
39 articles
Prompt engineering as a career is a bubble. As models improve, the skill becomes less valuable, not more....
AI calendar assistants claim massive time savings, but rigorous research reveals a productivity paradox: tools that make you feel faster actually make you....
ASR accuracy claims are based on ideal conditions. Real-world performance with background noise, accents, and domain jargon drops 30-50%....
Knowledge workers spend 4.3 hours per week fact-checking AI outputs. 47% of enterprise users made major decisions based on hallucinated content....
Legal terminology, manufacturing jargon, call center scripts - each requires specialized training. The myth of 'one model to rule them all.'...
The AI wrapper economy mirrors dropshipping: low barriers to entry, no moat, platform dependency....
Gartner predicts task-specific AI models will be used 3x more than general-purpose LLMs by 2027. Why latency, cost, and privacy push enterprises toward SLMs....
Current AI agents don't learn - they retrieve. New research on reinforcement learning for memory could change that....
Drawing parallels between the 2000 dot-com crash and today's AI investment frenzy....
Multimodal AI sits at peak hype on Gartner's 2025 cycle. But 80% of pilots fail to scale beyond testing....
LLMs confidently say strawberry has two R's because they've never seen letters—only tokens. This tokenization blindness predicts where AI will fail....
ASR systems need training data. Training data contains sensitive audio. How federated learning solves the conflict between ML requirements and privacy laws....
