Last May, I wrote a blog post titled As an Experienced LLM User, I Actually Don’t Use Generative LLMs Often as a contrasting response to the hype around the rising popularity of agentic coding. In that post, I noted that while LLMs are most definitely not useless and they can answer simple coding questions faster than it would take for me to write it myself with sufficient accuracy, agents are a tougher sell: they are unpredictable, expensive, and the hype around it was wildly disproportionate given the results I had seen in personal usage. However, I concluded that I was open to agents if LLMs improved enough such that all my concerns were addressed and agents were more dependable.
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A modern jet has an array of sensors to help it contend with bad weather. Magnetometers track the plane’s direction; gyroscopes help calculate its pitch and roll; accelerometers detect its changes in speed; Doppler radar measures the distance to the storm and how quickly it’s moving. In the early nineties, Larry Cornman developed a program that could sift through some of that sensor data to measure the air’s turbulence in real time. Atmospheric scientists call this the “eddy dissipation rate,” or E.D.R. It’s usually scored between 0 and 1—calm to severe.
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you: ghost commit -m "add user auth with JWT"