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The actor-producer Paul Reiser once said that producing is about figuring out what needs to be done and doing it. I think this also makes a good job description for software developers. Programmers are producers. We create something out of nothing at all, out of pure thought. Our skills are not just in writing code. […]

ChatGPT is a large-language model, a particular kind of AI program. Large-language models (LLMs) are not intelligent; they don’t learn and grow based on user interactions but learn through training.  Large language models are not conscious, nor will they become conscious, so we don’t have ethical or moral concerns, but others are working on AI

Legacy code is Software the Developers don’t wanna touch. It’s the code that industry uses to run the world and it is fit for its current purpose but developers find it hard to extend and that’s because legacy software is often written in a way that doesn’t support future changes, not because it can’t but

I’m an early adopter. I was a wiz with Alta Vista  (a predecessor to Google) back in the day. Actually, a full decade before that I was using one of the first networks that aggregated scientific papers called Dialog Information Services. It costs something like $100 an hour to connect and 25 cents per citation.

Put yourself in virtual shoes for a moment and see from Chat’s perspective. We often ask questions without providing any additional context and expect our AI to respond as though it could read our minds. To get good answers we have to provide background so I have conversations with Chat, invite their suggestions, and go

One everyday use case for ChatGPT is to explain a concept. This could be a part of common knowledge or something very obscure. This is a compelling capability that I’ve just begun to tap into. Let me give you some examples. Most people use this prompt to have Chat explain a complex or a difficult-to-understand

Note: I wrote the following blog post in August and then ran into technical issues. For more details see the note at the end of this post. I co-wrote the first draft of Prompt Engineering for Everyone using the free version of ChatGPT 3.5. I’ve used version 3.5 exclusively to write and edit the first

Assigning roles to ChatGPT is an important part of prompt engineering. It focuses responses to specific areas so that feedback is more relevant. When you ask ChatGPT to take a role by saying, “I want you to act as a marketing specialist,” or “Edit the following document for me,” it focuses ChatGPT into appropriate areas

I wrote Prompt Engineering for Everyone with the free version of ChatGPT 3.5, a major feat considering its memory constraints (which I’ll share with you in a future post). Due to these limitations, I could only write and edit about a page of text at a time with Chat.  But all that would change on

When the steam engine was first invented, people thought it would solve all humanity’s problems. It didn’t, but it definitely accelerated our growth.  And it did something else. It drove science to discover more efficient ways of measuring energy in closed system, which led to our understanding of quantum physics. Initially, I was skeptical about