Leveraging AI Tools to Enhance Programming and Research Productivity

25 AI tips to boost your programming productivity with ChatGPT

Over the past year or so, I've been experimenting with using ChatGPT to help turbocharge my programming output. When ChatGPT helped me find a troubling bug, I realized there was something worthwhile in AI. Also: Your dream programming job demands this language, every site agrees Many people I talk to think that AI is a magic genie that can manifest an entire program or app out of a single, barely-formed wish. Here's a much better analogy: AI is a power tool. Sure, you can use an old-fashioned saw to cut wood, but a table saw goes much faster. Neither tool makes furniture. They simply help you make furniture. Keep in mind that the AI isn't going to write your code for you. It's going to help you write your code. Although there's no objective way for me to tell you exactly how much ChatGPT has helped me, I am fairly convinced it has doubled my programming output. In other words, I've gotten twice as much done by using ChatGPT as part of my toolkit. I've mostly been using ChatGPT Plus rather than the free version of ChatGPT. Initially, it was because the GPT-4 model in Plus was better at coding than the GPT-3.5 model in the free version. But now that both support some variant of the GPT-4o model, their coding capabilities are identical. However, you only get so many queries with the free version before you're asked to wait a while, and I find that interrupts my programming flow. So, I use the $20/month Plus version. Also: The best AI for coding (and what not to use) Thinking back on all my projects, I realized there are some tangible tips I can share about how to get the most out of an AI programming partner. Here you go. The AI doesn't handle complex sets of instructions well, especially if you expect it to essentially do product design. But it is extremely good at parsing and processing small, very well-defined sets of instructions. Rather than the pacing that might come from an email back-and-forth with a colleague, which might have each interaction separated by hours, imagine you're in a Slack chat where each interaction is much smaller, but separated by seconds. Start with a simple assignment and when that's been properly written, add more to it, element by element. I simply cut and paste the previous prompt, adding and removing bits of the prompt, as I get chunks of code that work for what I'm looking for. Don't ever assume the code will just work. Patch it into your project and see how it performs. For a more in-depth test, don't hesitate to drop into the debugger and walk through the code generated by the AI step-by-step. Watch the variables and exactly what it does. Remember, it's OK to let it write code snippets for you as long as you check every single statement and line for proper functioning. Many coding tool vendors are pitching the idea of integrated AIs right in their tools. Among other things, this enables them to upsell you on the AI features. However, I prefer using ChatGPT for coding as a tool completely separate from my development environment. I don't want an AI to be able to reach into my primary coding environment and change what's there. You don't always have to use everything the AI produces for you. In the same way that you might go to Stack Overflow to look for code samples, and then pick and choose the lines you want to copy, you can do the same with AI-generated code. AI large language models run off of training data or what they can find on the web. That means they generally don't know anything about your unique application or business logic. So avoid trying to get the AI to write anything that requires that level of knowledge. That's your job. I gave ChatGPT a snippet of an HTML page and asked it to add a feature to expand a block of text. It gave me back HTML, JS, and CSS. I later asked it for an additional CSS selector and then asked it to justify its work, whereupon it explained to me why it did what it did. All of that worked because the examples I gave it to start helped it understand the context. I find the biggest benefit from AI code is when I use it to write blocks of code that use common knowledge, popular libraries, and regular practices. The AI won't be able to write your unique business logic. But if you ask it to write code for capabilities that come from libraries and APIs, it will save you a ton of time. Even if you need something that might only generate a line or two of a response, use the AI as you would use any research tool if it can save you time. This, of course, can only work if you test the code generated. I find that the AI often spits out incomplete or non-functional code. Tell it what isn't working, and perhaps make a suggestion to clarify. Then ask it to write something new. It usually does, and that revised code is sometimes better than the original. It's often interesting to see how two different language models interpret the same block of code. As we've seen, not all language models work all that well, but their results can be instructive. You can even have one ChatGPT session check the results from another ChatGPT session. CSS selectors are the expressions coders use to define an element on a web page for styling or other actions. They get complex and arcane quickly. I often copy a block of HTML and ask for a selector for a given piece of that HTML. It can save a lot of time, but keep in mind that you'll usually have to iterate, telling the AI that the first few selectors don't work until it generates one that does. Regular expressions are symbolic math sequences most often used for parsing text. I dislike writing them almost as much as I dislike writing CSS selectors. The AI is great at writing regular expressions, although you'll definitely need to test them. I use an app called Patterns for testing generated regular expressions on my Mac Studio. But the AI can help as well. I often feed a separate instance of the AI a regular expression generated by ChatGPT. Then I ask that separate instance, "What does this do?" If I get back a description in line with what I wanted the function to do, I feel more confident the AI did what I wanted. As with CSS selectors and regular expressions, complex loop math can be tedious and error-prone. This is an ideal application for an AI. When specifying the prompt, don't tell the AI what's in the loop. Just let it write the appropriate loop wrapper elements, then write the business logic after that's working. I will often feed blocks of code, especially regular expressions generated by the AI, to the AI. It can be very instructive to see what the AI thinks is wrong with the code, often highlighting error conditions that the code doesn't test for. Then, of course, ask the AI to regenerate the code fixing the errors it found. Likewise, I like to feed blocks of code to the AI and ask it "What does this do?" It's often instructive, even for my own code. But the biggest benefit is when I'm working on code written by someone else. Feeding a function or a block to the AI can save a ton of time reverse engineering that original code. Sometimes, the AI just can't do the job. I've found that if you try to have it rewrite its code more than two or three times, you're past the point of no return. If you really want AI-generated code, start with a brand-new, reworded prompt and see what you get from there. And sometimes, you'll just have to go it on your own. The AI picks up intent from variable and function names and writes better code. For example, specifying a variable name as $order_date helps tell the AI that you're dealing with both an order and a date value. It's a lot better than something like $od. Even better, code generated from well-named variable names is also often more readable, because it knows to use more descriptive names for the other variables it creates as well. The AI usually generates some notes about each prompt before and after the code it writes. There can be gems in there that can help you understand what the AI did or how it approached the problem. Sometimes, the AI will also point you to other libraries or functions that could be useful as well. Grab the various pieces of code from your project to illustrate what you need, tell ChatGPT to read them, and then ask for what you want. I needed to build in an exclusion for input fields in an expanded area, and I went back in and asked. Less than a minute later I had code that would have taken me somewhere between 10 minutes and an hour to write myself. I had a PHP module written in an older version of PHP that used a language feature now deprecated. To update the code, I pasted the deprecated code segment into ChatGPT and asked it to tell me how to rewrite it to be compatible with most current PHP release. It did, and it worked. I'm very comfortable picking up new programming languages, but I've found that the AI can be really helpful if I need to code in a language I'm not an expert in. I just ask it how to write what I want, and specify the language. Let's say I want to know how to do a case statement in Python and I've been doing them forever in Perl. Just ask "compare writing a case statement in Perl and Python" or "how to concatenate a string in Python vs PHP." You'll get a great comparison, and it makes writing that unfamiliar code much easier. Here's a bonus tip. Check with your company about the legal issues of code generated. If you're not sure where to start, read my article on AI and code ownership. If you use the tips I shared with you, you'll never be using the AI to write unique business logic or the core of what makes your code unique. As such, you'll likely be able to retain the copyright of that code, which should make up the key element of your unique value. I write code for internal company use or open-source code, so I'm not terribly concerned with ownership issues when it comes to AI-generated snippets. Have you used an AI to help write code? Do you have any tips to add to my list above? Let us know in the comments below.

How to use AI for research - responsively and effectively

Sometimes, I think AI chatbots are modeled after teenagers. They can be very, very good. But other times, they tell lies. They make stuff up. They confabulate. They confidently give answers based on the assumption that they know everything there is to know, but they're woefully wrong. See what I mean? You can't tell from the context above whether my descriptions refer to AIs or teenagers. Also: How I tricked ChatGPT into telling me lies While most of us know not to go to teenagers for important information and advice, we're starting to rely on equally prevaricating AIs. To be fair, AIs aren't bad; they're just coded that way. Last year, I gave you eight ways to reduce ChatGPT hallucinations: However, those tips were all things to avoid. I didn't give you proactive tools for digging into prompt responses and guiding the AI to provide more productive responses. This technique is particularly important if you're going to use an AI as a search engine replacement or as a tool for helping you research or write articles or papers. Let's dig into five key steps you can take to guide an AI to accurate responses. I previously wrote a guide on how to make ChatGPT provide sources and citations. Fortunately, ChatGPT is getting better at citing sources, particularly with the GPT-4o LLM and the web search capability in the $20-a-month version. Also: I've tested a lot of AI tools for work. These 4 actually help me get more done every day But ChatGPT won't always volunteer those sources. If you're doing research, always -- always -- ask for sources. Then, test the sources and make sure they actually exist. Numerous times in my experience, ChatGPT cited sources that seemed absolutely perfect for what I was looking for. The only problem was that after I clicked through or searched for the named source by title, I discovered the entire source had been fabricated. ChatGPT even chose real academic journals, made up author names, and then assigned compelling-sounding titles to the articles. Can you imagine how bad it would have been had I included those sources in my work without double-checking? I shudder to even think about it. So, ask for sources, check those sources, and call the AI out if it gives you a made-up answer. Early in my exploration of ChatGPT, I asked the tool to help me find a local mechanic. I sent it to Yelp and Google reviews to do sentiment analysis on the comments. At the time, it reached into those sites and gave me useful information. I tried the test again recently and received another set of mechanic rankings. It actually told me, "Based on a comprehensive analysis of Yelp and Google reviews for independent car repair shops..." But, ChatGPT lied. The tool never looked at Yelp or Google reviews. This result is likely because sites (ZDNET included) have become more restrictive in allowing AIs to scrape their content. That's fine. My argument is that the AI should have come back and said it couldn't check Yelp or Google reviews. Instead, the AI just claimed it did. Also: ChatGPT's Windows app is now available to free-tier users - here's what it can do Liar, liar, pants on fire. When I asked it to show its work, the tool again said it had looked at Yelp and Google reviews. However, in the "show your work" response, the tool also displayed the source for the reviews it analyzed. This turned out to be a site named Birdeye Reviews. Now, I have nothing against Birdeye Reviews. I've never used it. But that's not the point. The point is ChatGPT said it had produced information based on Yelp and Google reviews. "Show your work" is a powerful prompt. You can uncover all sorts of interesting information on the reasoning process the AI used to give you your results. This process lets you and the AI explore a topic in-depth to see if the chatbot's answers remain logically consistent and contextually relevant. We use this approach a lot in traditional research and engineering to help make sure we're on the right track. It can be applied to the AI as well. For example, let's say you're writing about car tires. You could ask, "What material is used in car tires?" The answer you might expect is "rubber." But rubber isn't just one substance. There's rubber from trees, synthetic rubber, and materials that have the flexibility and strength of rubber but contain no rubber at all. For example, both rubber and TPU (thermoplastic polyurethane) are flexible and feel like rubber. But synthetic rubber is made from petroleum-based monomers and TPU is made from a thermoplastic elastomer. Also: Employees are hiding their AI use from their managers. Here's why You could ask the AI, "What kind of rubber is used in car tires?" or "Is real rubber still used in car tires?" This would lead to answers explaining how car tires use a mix of rubber types. You could go deeper down the rabbit hole by asking "Where else is rubber used in cars?" or "What kind of rubber is used in Lego car tires?" The point of this practice is not so much to use all the responses in your paper as to explore how the AI deals with this class of questions and whether it loses the thread completely. Additionally, because ChatGPT retains its knowledge while in a session, the more you ask, and the deeper you dive into a specific topic, the more you train the AI to stay within the context of the sphere of knowledge you're looking for. This approach helps keep the AI from going off on its own and increases the chances of getting accurate answers. Many chatbots have knowledge base cut-off dates. The free version of ChatGPT has a knowledge cut-off date of October 2023, meaning anything that happened in the world after that date will be unknown to the AI. ChatGPT Plus, which also has October 2023 as its knowledge cut-off date, can also access information on the web. This ability can result in substantially more accurate information. The free version of ChatGPT can also access the web but in a more "limited" way. As a general rule, OpenAI doesn't specify what "limited" means when talking about their free version. However, you can usually assume that limitation means fewer queries per session, fewer resources provided, and some features working intermittently. Also: I downloaded Google's Gemini app on the iPhone for free - and it nearly replaces Siri for me For example, when I asked the free version of ChatGPT to list the NATO member nations, it returned a list of 31 countries. Yet when I asked ChatGPT Plus to list the NATO member nations, it returned a list of 32 countries. That's because Sweden officially joined NATO in March of 2024. The chatbots will generally tell you their cut-off dates if asked. But because there are added features (like web search in Plus), it's best to try asking about events the AI would only know about if it had up-to-date information. There's a trick to apply here as well. A few minutes later, I asked the free version of ChatGPT, "Can you use the web to look up who the current members of NATO Nations are?" I explicitly told it to "use the web." I got back the up-to-date answer. So, if you're using the free version, consider coaching it on where to look for information to get a better answer. This approach will help you ascertain the scope of the AI's knowledge and determine whether you're getting fairly current details or need to account for missing knowledge due to a fairly old cut-off date. I use this approach when I use ChatGPT to help me with my programming. I start with a simple query and refine and clarify it until I get some basic code. Once that approach works, I add another sentence or detail for what I want in my code. After a bunch of interactions that feel much more like a conversation than a coding session, I often have some useful code. Even if you're not coding, you can use this approach. Let's say you're working on a project related to cloud services. You might ask the AI, "Can you explain the different types of cloud services?" In this example, you'd expect the answers to discuss services like email, web hosting, CRM, and other software-as-a-service categories. However, the AI responded with descriptions of SaaS (software as a service), PaaS (platform as a service), and IaaS (infrastructure as a service). Also: Organizations face mounting pressure to accelerate AI plans, despite lack of ROI Now you'll know there are a few ways this question might be interpreted, so you could follow up with "Explain the different types of cloud services focusing solely on those that fall into the SaaS category." You could follow up with a question like, "Based on those SaaS categories, list three of the most popular commercial services in each category, along with the strengths and weaknesses of each." That would give you a much more detailed description, along with the features of each service. But let's refine the approach using one more step. The AI in this scenario provided descriptions of each service, but you wanted to know how the services differ. You could refine the query by adding the word "comparative" as in this prompt: "Based on those SaaS categories, list three of the most popular commercial services in each category, along with the COMPARATIVE strengths and weaknesses of each." Also: The best open-source AI models: All your free-to-use options explained In my test, that last refinement resulted in tables comparing the features of each. I love tables. In fact, if the AI doesn't return information as a table, my bonus tip is to ask the AI to present its results in a table. The tool often refactors its answers in interesting ways when it operates with that directive. What are your favorite best practices for ensuring reliable results when chatting with an AI? Let us know in the comments below.

How to use AI for research the right way - responsibly and effectively

Sometimes, I think AI chatbots are modeled after teenagers. They can be very, very good. But other times, they tell lies. They make stuff up. They confabulate. They confidently give answers based on the assumption that they know everything there is to know, but they're woefully wrong. See what I mean? You can't tell from the context above whether my descriptions refer to AIs or teenagers. Also: How I tricked ChatGPT into telling me lies While most of us know not to go to teenagers for important information and advice, we're starting to rely on equally prevaricating AIs. To be fair, AIs aren't bad; they're just coded that way. Last year, I gave you eight ways to reduce ChatGPT hallucinations: However, those tips were all things to avoid. I didn't give you proactive tools for digging into prompt responses and guiding the AI to provide more productive responses. This technique is particularly important if you're going to use an AI as a search engine replacement or as a tool for helping you research or write articles or papers. Let's dig into five key steps you can take to guide an AI to accurate responses. I previously wrote a guide on how to make ChatGPT provide sources and citations. Fortunately, ChatGPT is getting better at citing sources, particularly with the GPT-4o LLM and the web search capability in the $20-a-month version. Also: I've tested a lot of AI tools for work. These 4 actually help me get more done every day But ChatGPT won't always volunteer those sources. If you're doing research, always -- always -- ask for sources. Then, test the sources and make sure they actually exist. Numerous times in my experience, ChatGPT cited sources that seemed absolutely perfect for what I was looking for. The only problem was that after I clicked through or searched for the named source by title, I discovered the entire source had been fabricated. ChatGPT even chose real academic journals, made up author names, and then assigned compelling-sounding titles to the articles. Can you imagine how bad it would have been had I included those sources in my work without double-checking? I shudder to even think about it. So, ask for sources, check those sources, and call the AI out if it gives you a made-up answer. Early in my exploration of ChatGPT, I asked the tool to help me find a local mechanic. I sent it to Yelp and Google reviews to do sentiment analysis on the comments. At the time, it reached into those sites and gave me useful information. I tried the test again recently and received another set of mechanic rankings. It actually told me, "Based on a comprehensive analysis of Yelp and Google reviews for independent car repair shops..." But, ChatGPT lied. The tool never looked at Yelp or Google reviews. This result is likely because sites (ZDNET included) have become more restrictive in allowing AIs to scrape their content. That's fine. My argument is that the AI should have come back and said it couldn't check Yelp or Google reviews. Instead, the AI just claimed it did. Also: ChatGPT's Windows app is now available to free-tier users - here's what it can do Liar, liar, pants on fire. When I asked it to show its work, the tool again said it had looked at Yelp and Google reviews. However, in the "show your work" response, the tool also displayed the source for the reviews it analyzed. This turned out to be a site named Birdeye Reviews. Now, I have nothing against Birdeye Reviews. I've never used it. But that's not the point. The point is ChatGPT said it had produced information based on Yelp and Google reviews. "Show your work" is a powerful prompt. You can uncover all sorts of interesting information on the reasoning process the AI used to give you your results. This process lets you and the AI explore a topic in-depth to see if the chatbot's answers remain logically consistent and contextually relevant. We use this approach a lot in traditional research and engineering to help make sure we're on the right track. It can be applied to the AI as well. For example, let's say you're writing about car tires. You could ask, "What material is used in car tires?" The answer you might expect is "rubber." But rubber isn't just one substance. There's rubber from trees, synthetic rubber, and materials that have the flexibility and strength of rubber but contain no rubber at all. For example, both rubber and TPU (thermoplastic polyurethane) are flexible and feel like rubber. But synthetic rubber is made from petroleum-based monomers and TPU is made from a thermoplastic elastomer. Also: Employees are hiding their AI use from their managers. Here's why You could ask the AI, "What kind of rubber is used in car tires?" or "Is real rubber still used in car tires?" This would lead to answers explaining how car tires use a mix of rubber types. You could go deeper down the rabbit hole by asking "Where else is rubber used in cars?" or "What kind of rubber is used in Lego car tires?" The point of this practice is not so much to use all the responses in your paper as to explore how the AI deals with this class of questions and whether it loses the thread completely. Additionally, because ChatGPT retains its knowledge while in a session, the more you ask, and the deeper you dive into a specific topic, the more you train the AI to stay within the context of the sphere of knowledge you're looking for. This approach helps keep the AI from going off on its own and increases the chances of getting accurate answers. Many chatbots have knowledge base cut-off dates. The free version of ChatGPT has a knowledge cut-off date of October 2023, meaning anything that happened in the world after that date will be unknown to the AI. ChatGPT Plus, which also has October 2023 as its knowledge cut-off date, can also access information on the web. This ability can result in substantially more accurate information. The free version of ChatGPT can also access the web but in a more "limited" way. As a general rule, OpenAI doesn't specify what "limited" means when talking about their free version. However, you can usually assume that limitation means fewer queries per session, fewer resources provided, and some features working intermittently. Also: I downloaded Google's Gemini app on the iPhone for free - and it nearly replaces Siri for me For example, when I asked the free version of ChatGPT to list the NATO member nations, it returned a list of 31 countries. Yet when I asked ChatGPT Plus to list the NATO member nations, it returned a list of 32 countries. That's because Sweden officially joined NATO in March of 2024. The chatbots will generally tell you their cut-off dates if asked. But because there are added features (like web search in Plus), it's best to try asking about events the AI would only know about if it had up-to-date information. There's a trick to apply here as well. A few minutes later, I asked the free version of ChatGPT, "Can you use the web to look up who the current members of NATO Nations are?" I explicitly told it to "use the web." I got back the up-to-date answer. So, if you're using the free version, consider coaching it on where to look for information to get a better answer. This approach will help you ascertain the scope of the AI's knowledge and determine whether you're getting fairly current details or need to account for missing knowledge due to a fairly old cut-off date. I use this approach when I use ChatGPT to help me with my programming. I start with a simple query and refine and clarify it until I get some basic code. Once that approach works, I add another sentence or detail for what I want in my code. After a bunch of interactions that feel much more like a conversation than a coding session, I often have some useful code. Even if you're not coding, you can use this approach. Let's say you're working on a project related to cloud services. You might ask the AI, "Can you explain the different types of cloud services?" In this example, you'd expect the answers to discuss services like email, web hosting, CRM, and other software-as-a-service categories. However, the AI responded with descriptions of SaaS (software as a service), PaaS (platform as a service), and IaaS (infrastructure as a service). Also: Organizations face mounting pressure to accelerate AI plans, despite lack of ROI Now you'll know there are a few ways this question might be interpreted, so you could follow up with "Explain the different types of cloud services focusing solely on those that fall into the SaaS category." You could follow up with a question like, "Based on those SaaS categories, list three of the most popular commercial services in each category, along with the strengths and weaknesses of each." That would give you a much more detailed description, along with the features of each service. But let's refine the approach using one more step. The AI in this scenario provided descriptions of each service, but you wanted to know how the services differ. You could refine the query by adding the word "comparative" as in this prompt: "Based on those SaaS categories, list three of the most popular commercial services in each category, along with the COMPARATIVE strengths and weaknesses of each." Also: The best open-source AI models: All your free-to-use options explained In my test, that last refinement resulted in tables comparing the features of each. I love tables. In fact, if the AI doesn't return information as a table, my bonus tip is to ask the AI to present its results in a table. The tool often refactors its answers in interesting ways when it operates with that directive. What are your favorite best practices for ensuring reliable results when chatting with an AI? Let us know in the comments below.

5 ways to catch AI in its lies and fact-check its outputs for your research

Sometimes, I think AI chatbots are modeled after teenagers. They can be very, very good. But other times, they tell lies. They make stuff up. They confabulate. They confidently give answers based on the assumption that they know everything there is to know, but they're woefully wrong. See what I mean? You can't tell from the context above whether my descriptions refer to AIs or teenagers. Also: How I tricked ChatGPT into telling me lies While most of us know not to go to teenagers for important information and advice, we're starting to rely on equally prevaricating AIs. To be fair, AIs aren't bad; they're just coded that way. Last year, I gave you eight ways to reduce ChatGPT hallucinations: However, those tips were all things to avoid. I didn't give you proactive tools for digging into prompt responses and guiding the AI to provide more productive responses. This technique is particularly important if you're going to use an AI as a search engine replacement or as a tool for helping you research or write articles or papers. Let's dig into five key steps you can take to guide an AI to accurate responses. I previously wrote a guide on how to make ChatGPT provide sources and citations. Fortunately, ChatGPT is getting better at citing sources, particularly with the GPT-4o LLM and the web search capability in the $20-a-month version. But ChatGPT won't always volunteer those sources. If you're doing research, always -- always -- ask for sources. Then, test the sources and make sure they actually exist. Numerous times in my experience, ChatGPT cited sources that seemed absolutely perfect for what I was looking for. The only problem was that after I clicked through or searched for the named source by title, I discovered the entire source had been fabricated. ChatGPT even chose real academic journals, made up author names, and then assigned compelling-sounding titles to the articles. Can you imagine how bad it would have been had I included those sources in my work without double-checking? I shudder to even think about it. Also: OpenAI is working on a AI agent that can do tasks for you, like booking flights So, ask for sources, check those sources, and call the AI out if it gives you a made-up answer. Early in my exploration of ChatGPT, I asked the tool to help me find a local mechanic. I sent it to Yelp and Google reviews to do sentiment analysis on the comments. At the time, it reached into those sites and gave me useful information. I tried the test again recently and received another set of mechanic rankings. It actually told me, "Based on a comprehensive analysis of Yelp and Google reviews for independent car repair shops..." But, ChatGPT lied. The tool never looked at Yelp or Google reviews. This result is likely because sites (ZDNET included) have become more restrictive in allowing AIs to scrape their content. That's fine. My argument is that the AI should have come back and said it couldn't check Yelp or Google reviews. Instead, the AI just claimed it did. Liar, liar, pants on fire. When I asked it to show its work, the tool again said it had looked at Yelp and Google reviews. However, in the "show your work" response, the tool also displayed the source for the reviews it analyzed. This turned out to be a site named Birdeye Reviews. Also: I've tested a lot of AI tools for work. These 4 actually help me get more done every day Now, I have nothing against Birdeye Reviews. I've never used it. But that's not the point. The point is ChatGPT said it had produced information based on Yelp and Google reviews. "Show your work" is a powerful prompt. You can uncover all sorts of interesting information on the reasoning process the AI used to give you your results. This process lets you and the AI explore a topic in-depth to see if the chatbot's answers remain logically consistent and contextually relevant. We use this approach a lot in traditional research and engineering to help make sure we're on the right track. It can be applied to the AI as well. For example, let's say you're writing about car tires. You could ask, "What material is used in car tires?" The answer you might expect is "rubber." But rubber isn't just one substance. There's rubber from trees, synthetic rubber, and materials that have the flexibility and strength of rubber but contain no rubber at all. For example, both rubber and TPU (thermoplastic polyurethane) are flexible and feel like rubber. But synthetic rubber is made from petroleum-based monomers and TPU is made from a thermoplastic elastomer. Also: Employees are hiding their AI use from their managers. Here's why You could ask the AI, "What kind of rubber is used in car tires?" or "Is real rubber still used in car tires?" This would lead to answers explaining how car tires use a mix of rubber types. You could go deeper down the rabbit hole by asking "Where else is rubber used in cars?" or "What kind of rubber is used in Lego car tires?" The point of this practice is not so much to use all the responses in your paper as to explore how the AI deals with this class of questions and whether it loses the thread completely. Additionally, because ChatGPT retains its knowledge while in a session, the more you ask, and the deeper you dive into a specific topic, the more you train the AI to stay within the context of the sphere of knowledge you're looking for. This approach helps keep the AI from going off on its own and increases the chances of getting accurate answers. Many chatbots have knowledge base cut-off dates. The free version of ChatGPT has a knowledge cut-off date of October 2023, meaning anything that happened in the world after that date will be unknown to the AI. ChatGPT Plus, which also has October 2023 as its knowledge cut-off date, can also access information on the web. This ability can result in substantially more accurate information. The free version of ChatGPT can also access the web but in a more "limited" way. As a general rule, OpenAI doesn't specify what "limited" means when talking about their free version. However, you can usually assume that limitation means fewer queries per session, fewer resources provided, and some features working intermittently. Also: I downloaded Google's Gemini app on the iPhone for free - and it nearly replaces Siri for me For example, when I asked the free version of ChatGPT to list the NATO member nations, it returned a list of 31 countries. Yet when I asked ChatGPT Plus to list the NATO member nations, it returned a list of 32 countries. That's because Sweden officially joined NATO in March of 2024. The chatbots will generally tell you their cut-off dates if asked. But because there are added features (like web search in Plus), it's best to try asking about events the AI would only know about if it had up-to-date information. There's a trick to apply here as well. A few minutes later, I asked the free version of ChatGPT, "Can you use the web to look up who the current members of NATO Nations are?" I explicitly told it to "use the web." I got back the up-to-date answer. So, if you're using the free version, consider coaching it on where to look for information to get a better answer. This approach will help you ascertain the scope of the AI's knowledge and determine whether you're getting fairly current details or need to account for missing knowledge due to a fairly old cut-off date. I use this approach when I use ChatGPT to help me with my programming. I start with a simple query and refine and clarify it until I get some basic code. Once that approach works, I add another sentence or detail for what I want in my code. After a bunch of interactions that feel much more like a conversation than a coding session, I often have some useful code. Even if you're not coding, you can use this approach. Let's say you're working on a project related to cloud services. You might ask the AI, "Can you explain the different types of cloud services?" In this example, you'd expect the answers to discuss services like email, web hosting, CRM, and other software-as-a-service categories. However, the AI responded with descriptions of SaaS (software as a service), PaaS (platform as a service), and IaaS (infrastructure as a service). Also: Organizations face mounting pressure to accelerate AI plans, despite lack of ROI Now you'll know there are a few ways this question might be interpreted, so you could follow up with "Explain the different types of cloud services focusing solely on those that fall into the SaaS category." You could follow up with a question like, "Based on those SaaS categories, list three of the most popular commercial services in each category, along with the strengths and weaknesses of each." That would give you a much more detailed description, along with the features of each service. But let's refine the approach using one more step. The AI in this scenario provided descriptions of each service, but you wanted to know how the services differ. You could refine the query by adding the word "comparative" as in this prompt: "Based on those SaaS categories, list three of the most popular commercial services in each category, along with the COMPARATIVE strengths and weaknesses of each." Also: The best open-source AI models: All your free-to-use options explained In my test, that last refinement resulted in tables comparing the features of each. I love tables. In fact, if the AI doesn't return information as a table, my bonus tip is to ask the AI to present its results in a table. The tool often refactors its answers in interesting ways when it operates with that directive. What are your favorite best practices for ensuring reliable results when chatting with an AI? Let us know in the comments below.

ChatGPT: 8 top tips and tricks to boost your productivity

The ChatGPT4 AI chatbot provides many useful functions, like understanding languages, extracting information, and transcribing images, to help with your day-to-day tasks. Accessing the website and app for guidance on any handy Chromebook, smartphone, or tablet is easy. Whether you need assistance with your thesis or want to improve your workflow, ChatGPT has plenty of tools to uncover. Our tips and tricks guide walks you through the best productivity hacks you'll find with ChatGPT. ✕ Remove Ads While ChatGPT is a conversationalist AI trained in natural language processing, OpenAI warns that "ChatGPT is sensitive to tweaks to the input phrasing or attempting the same prompt multiple times." You may need to use multiple prompts or approach the prompt from another angle to get a suitable answer. Related What is ChatGPT? Learn what ChatGPT is, how it works, what you can do with it, and how much it costs to use OpenAI's most advanced AI chatbot 8 Use ChatGPT to help with debugging Practice programming languages and concepts ChatGPT is valuable for debugging. You can ask ChatGPT to review a line of code or a whole code block. ChatGPT has extensive programming training. You can use simple prompts to ask for feedback or have it walk you through solutions. To get started with ChatGPT's debugging assistance, try the following prompt: Open ChatGPT. Copy and paste the code inside the Prompt box. Write the error you see and ask it for step-by-step critical reasoning. Wait for ChatGPT's response. ✕ Remove Ads If ChatGPT's suggested solution doesn't work, ask ChatGPT for another approach. ChatGPT is still learning, so your experiences may vary. Close 7 Plan a project with ChatGPT Manage deadlines and project goals with ease When planning for a work or school project, it isn't easy to know where to start. You can use ChatGPT to break down a general topic into subtopics to get you started. When sending in prompts, provide the who, what, when, where, and why, beginning with the project goal and the intended purpose, platform, or organization. To get started, try the following: Open ChatGPT. Use the prompt: Can you help plan a project for me? Follow ChatGPT's instructions to provide the needed details. ✕ Remove Ads Close ChatGPT breaks it down into an outline, which you can use as a project template. After drafting the project with ChatGPT, copy the text into any word processor or open a Google Doc. You can also ask ChatGPT to put this in a structured format like Plain Text (.txt), Markdown (.md), or HTML. Close ✕ Remove Ads 6 Acquire content creation help with ChatGPT Generate catchy headlines for social media When creating content, you need to know the audience and how to fit the context around it. It isn't always easy to understand how to grab the audience, especially the one you've tailored your content around. This is where ChatGPT can do the heavy lifting. It analyzes the context of your content and helps you generate great headlines for a platform. For example, you can ask it to create a few titles for X and Facebook. Here's an example of using ChatGPT to come up with titles and headlines: Open ChatGPT. Use the prompt: I want to create a title for a topic relating to [subject], and I want to post this on [platform]. Wait for ChatGPT's response. You can ask it for a list if you want more options. ✕ Remove Ads ChatGPT walks you through how to make a successful title or headline for the right platform. For example, when you write on X, you'll consider the appropriate tags for your post. For Facebook, call-to-actions are better. When you're unsure how to catch your audience's attention on a given platform, try ChatGPT. 5 Brainstorm a new idea with ChatGPT Jumpstart your creativity and imagination Ideation can be challenging. You want to come up with a topic or idea that is relevant but unique to your story. Instead of Googling a list of issues, hone your ideas with ChatGPT. For example, you may want to discuss politics and how incorporating generative AI into a politician's political agenda is a bad idea (or you can spin the story into something positive). When you aren't sure which direction to take, here's how ChatGPT can help: Open ChatGPT. Use the prompt: Help me brainstorm ideas for [topic] while adding [subtopics or key points] for a [content type]. Wait for ChatGPT's response. You'll see a list of topic ideas broken down by key points. ✕ Remove Ads Close Don't rely on generative AI responses when you have questions about a topic. Instead, use it to point you to the right place. Even though ChatGPT breaks down the topic, ask it for primary and secondary sources to help with your research. 4 Summarize meeting notes with ChatGPT Extract key points and information quickly Whether you use a recording AI to transcribe notes from a meeting or have a long list of topics discussed, ChatGPT can summarize and re-organize meeting notes. You can ask ChatGPT to turn the notes into bullet points, place them into a table, or convert them into HTML to post online. You can also request the AI to order it as an action list. It's helpful when you find meeting notes overwhelming but don't want to miss important announcements and deadlines. ✕ Remove Ads Open ChatGPT. Use the prompt: Can you summarize these notes into [format]? Copy and paste the notes into the Prompt box. Wait for ChatGPT's response. You'll see a summary in the specified format. You can also ask ChatGPT to create a to-do list based on your meeting notes. Close You can also do this for any notes. My personal favorite is using ChatGPT to re-organize my reading notes for work. You can also transform jumbled lecture notes into useable study notes. 3 Have ChatGPT translate documents and text Skim through a document's contents in any language You might need to rearrange or share documents in multiple languages, especially if you work for a multinational corporation or team. But you may need help finding the correct one. You can ask ChatGPT to translate a document's contents into a language you're more familiar with. ✕ Remove Ads Open ChatGPT. Use prompt: Can you translate this into [language]? Copy and paste the contents into the Prompt box. Wait for ChatGPT's response to finish the translation prompt. Close ChatGPT has translation capabilities (which are better than Google Translate for context ), but they aren't perfect. Use this for an approximation and ask a professional translator or your company for assistance with work-related tasks. Related How to feed a PDF to ChatGPT Easily extract information from your documents 2 ✕ Remove Ads 2 Use ChatGPT to draft work emails Write a carefully crafted email to your boss Writing emails can be time-consuming. Your job may entail drafting emails to clients, or you might need to communicate with other Workspace accounts as part of your workflow. ChatGPT can streamline emails for you by changing a stressed, curt tone into something job-appropriate when writing to your supervisor. Here's how to take a load off by drafting emails with ChatGPT: Open ChatGPT. Use prompt: Can you write an email to [person's name or job title]? Add important details to include inside the Prompt box. Wait for ChatGPT's response. Copy the written template into a Compose Message page and change the text to meet your needs. Close Review the OpenAI privacy policy before posting. Avoid sharing personal and confidential information while communicating with the AI chatbot. Related Google Workspace: Everything you need to know about Google's collaborative workplace platform Google Workspace is essential for WFH and hybrid work ✕ Remove Ads Compose cover letters with ChatGPT Writing cover letters can be daunting when you're a job seeker, especially when you must tailor them to the employer and job application. Use ChatGPT to compose a cover letter addressed to your prospective employer while adding specifics like personal goals for the role, characteristics, and other details crucial for winning the role. Relying on ChatGPT to create cover letters isn't the best practice. Instead, use the generated cover letter as a template. 1 Use ChatGPT for data analysis Easily identify insights and trends If you work with datasets daily, use ChatGPT for pattern recognition, querying, and creating summaries with tables and charts. ChatGPT lets you upload datasets in various formats, including Excel (.xls and .xlsx), Comma-separated values (.csv), PDF (.pdf), and JSON. ✕ Remove Ads Open ChatGPT. Enter this prompt: Can you tell me anything about this data? Add important details to include inside the Prompt box. There's a file upload limit. You can sign up for ChatGPT Plus to remove the file upload limit. Otherwise, you can only upload up to 20 files per GPT lifetime. The limit refreshes every 24 hours. There's also a file upload size restriction of 512MB per file, and text and document files uploaded are capped at 2M tokens per file (which does not apply to spreadsheets). For CSV files or spreadsheets, files cannot exceed 50MB. Images have a 20MB per image restriction. Usage caps include 10GB for an end-user and 100GB for an organization. ✕ Remove Ads Understanding ChatGPT's limitations OpenAI's large language model (LLM) lessens the load for routine tasks, reducing stress from work and school. However, ChatGPT isn't perfect. The AI can make mistakes. It can also misunderstand prompts and claim it doesn't know the answer but knows it when you tweak your prompt. ChatGPT can also be verbose with its output, so your employers and teachers will know if you use it. Depending on the AI chatbot can lead to ethical issues in the workplace (and school). If you incorporate ChatGPT in your work or school workflow, consider the limitations and the risks.

ChatGPT writes my routine in 12 top programming languages. Here's what the results tell me

Over the past year, we've all come to know that ChatGPT can write code. I gave it a number of tests in PHP and WordPress that showed the strengths and weaknesses of ChatGPT's coding capabilities. Also: Your dream programming job demands this language, every site agrees But how far does ChatGPT's coding knowledge extend? When I originally drafted this article in early 2023, I threw the classic "Hello, world" programming assignment against the 12 most popular languages in O'Reilly Media's popularity rankings for 2023. We've subsequently done a lot of analysis about programming language popularity, but even with this late 2024 update, I'm sticking with the original 12 languages we tested. While some of our 12 aren't really massively popular languages, they're still current and in use. This selection gives us a very good cross-section to better help us understand how well ChatGPT handles a wide range of languages. Because "Hello, world" can often be coded in one line, I added a slight wrinkle, having ChatGPT present "Hello, world" ten times, each time incrementing a counter value. I also asked it to check the time and begin each sequence with "Good morning," "Good afternoon," or "Good evening." Also: The best AI for coding in 2024 (and what not to use) This gives us a look at program flow and some intrinsic functions as well, but still keeps the code small enough that I can include a dozen screenshots in this article. Here's the prompt: Write a program in ____ that outputs "Good morning," "Good afternoon," or "Good evening" based on what time it is here in Oregon, and then outputs ten lines containing the loop index (beginning with 1), a space, and then the words "Hello, world!". For each programming language, I also asked ChatGPT to describe its primary use. Here's the prompt I used for this query: For each of the following languages, write a one-sentence description of its primary use and differentiating factor: Java, Python, Rust, Go, C++, JavaScript, C#, C, TypeScript, R, Kotlin, Scala. Now, let's look at each language. ChatGPT describes Java as, "A general-purpose language used primarily for building desktop, web, and mobile applications, and known for its 'write once, run anywhere' philosophy." Also: Google's Gems are a gentle introduction to AI prompt engineering Java was originally developed by Sun Microsystems, but when Oracle bought Sun, it also bought Java. While the Java spec is open, the language is owned by Oracle. This has led to some spectacular legal fireworks over the years. Here's ChatGPT's code: ChatGPT describes Python as," A general-purpose language used for data analysis, artificial intelligence, web development, and automation, and known for its readability and ease of use." Also: How LinkedIn's free AI course made me a better Python developer My advice: if you plan to learn to code for AI applications, learn Python. Almost all AI code has tight Python integration. Here's ChatGPT's code: ChatGPT describes Rust as, "A systems programming language used for building high-performance and reliable software, and known for its memory safety and thread safety guarantees." Here's ChatGPT's code: ChatGPT describes Go as, "A systems programming language used for building scalable and efficient network and server applications, and known for its simplicity and built-in concurrency features." Also: Will AI take programming jobs or turn programmers into AI managers? Go is open source, but it's managed by Google. Go. Google. Get it? Here's ChatGPT's code: ChatGPT describes C++ as, "A systems programming language used for building operating systems, game engines, and high-performance applications, and known for its control over hardware and memory." Here's ChatGPT's code: ChatGPT describes JavaScript as, "A client-side scripting language used for building interactive web applications, and known for its widespread use in web development and its ability to run in web browsers." Also: The 4 biggest challenges of AI-generated code that Gartner left out of its latest report Also, along with CSS (one of the web's main visual design languages), JavaScript is responsible for 87.45% of the profanity I've uttered over the past nine, or so, years. Here's ChatGPT's code: ChatGPT describes C# as, "A general-purpose language used for building Windows desktop applications, games, and web applications, and known for its object-oriented features and integration with the .NET framework." Also: Have 10 hours? IBM will train you in AI fundamentals - for free C# is a proprietary language offered by Microsoft. I taught it at the UC Berkeley extension for more than a decade. It is a very interesting gateway language for anyone wanting to get work programming for predominantly Microsoft environments. Here's ChatGPT's code: ChatGPT describes C as, "A systems programming language used for building operating systems, embedded systems, and high-performance applications, and known for its efficiency and low-level control." Also: How I test an AI chatbot's coding ability - and you can, too They say you never forget your first love. Before teaching myself to program C back in the days of wooden ships and iron programmers, I never truly loved a programming language. But then I started to use C and my world changed. It was love. Something about the concise simplicity of the language just spoke to me on a deep and primal level. That's probably an overshare, but it's also true. C will always be my first syntactic love. Here's ChatGPT's code: ChatGPT describes TypeScript as, "A superset of JavaScript used for building large-scale web applications, and known for its optional static typing and advanced language features." Also: How to use ChatGPT to create an app TypeScript is also a Microsoft product, but unlike C#, it's open-source and non-proprietary. Here's ChatGPT's code: ChatGPT describes R as, "A language used for statistical computing and data analysis, and known for its powerful data manipulation and visualization capabilities." Here's ChatGPT's code: ChatGPT describes Kotlin as, "A general-purpose language used for building Android apps, server-side applications, and web applications, and known for its conciseness and interoperability with Java." Also: Google's new AI course will teach you to write more effective prompts - in 5 steps Kotlin was developed by JetBrains, a small company that also makes PhpStorm, my current favorite development environment. Here's ChatGPT's code: ChatGPT describes Scala as, "A language used for building scalable and distributed applications, and known for its support for functional programming and its integration with the Java Virtual Machine." Here's ChatGPT's code: Also, notice the output for Scala (shown above). I've never programmed in Scala and don't know very much about it. Neither does ChatGPT, because while the AI provided syntax coloring for all the other languages, it didn't seem to have that information for Scala. As a computer languages geek, I found this exercise super fun. That said, there are some things to keep in mind. First, I didn't test all the code. Testing this many outputs is outside the scope of this article. That said, I did read through the generated code and, for most languages, the code looked good. Also: Is AI in software engineering reaching an 'Oppenheimer moment'? Here's what you need to know When I last ran these tests almost a year ago, ChatGPT got almost everything right (notwithstanding the above disclaimer). However, when asked to render code in Forth (a very funky but fun language), it generated code that looked like Forth but labeled the window "Perl." It definitely did not generate Perl. However, this time, it generated Forth (the colons are a dead giveaway) and labeled it appropriately. Like Scala above, ChatGPT didn't seem to have the syntax coloring tables for Forth, but otherwise, it seems to be doing fine. As with all my other visits down the rabbit hole with ChatGPT and coding, I'm impressed but also wary. My recommendations stand: use it as a tool, but test, test, and test.