Using ChatGPT to blocking IP address on WordPress

Anyone running a WordPress site will know that hackers using a wide range of IP addresses will be trying to log in to their account. You can use IP blocking Plugins to sort this out but the one I use, Limit Login Attempts, requires me to update the list of IP addresses regularly. To do this I need to copy the log of login attempts, extract the IP addresses from this logged data and then add them to the blocked list. The log itself includes other data as shown below.

August 06, 2023 08:30 admin (1 lockouts) wp_xmlrpc Unlock
August 06, 2023 07:53 admin (1 lockouts) wp_xmlrpc Unlocked
August 06, 2023 03:11 admin (1 lockouts) wp_xmlrpc Unlocked
August 06, 2023 02:34 admin (1 lockouts) wp_xmlrpc Unlocked
August 06, 2023 02:33 admin (1 lockouts) wp_xmlrpc Unlocked
August 05, 2023 21:43 admin (1 lockouts) wp_xmlrpc Unlocked
August 05, 2023 17:45 admin (1 lockouts) wp_xmlrpc Unlocked
August 05, 2023 17:44 admin (1 lockouts) wp_xmlrpc Unlocked

So I use ChatGPT to extract the IP address automatically. Here’s the exact Prompt

Extract the IP addresses in this data so that I can copy and paste it into an IP blocker in WordPress.

August 06, 2023 08:30 2a01:238:20a:202:1000::25 admin (1 lockouts) wp_xmlrpc Unlock August 06, 2023 08:30 admin (1 lockouts) wp_xmlrpc Unlock August 06, 2023 07:53 admin (1 lockouts) wp_xmlrpc Unlocked August 06, 2023 03:11 admin (1 lockouts) wp_xmlrpc Unlocked August 06, 2023 02:34 admin (1 lockouts) wp_xmlrpc Unlocked August 06, 2023 02:33 admin (1 lockouts) wp_xmlrpc Unlocked August 05, 2023 21:43 admin (1 lockouts) wp_xmlrpc Unlocked August 05, 2023 17:45 admin (1 lockouts) wp_xmlrpc Unlocked August 05, 2023 17:44 admin (1 lockouts) wp_xmlrpc Unlocked

and here’s the response


This makes blocking much easier, faster and more accurate. However, do be careful to make sure you don’t accidently block your own IP address at any appoint

SMEs Struggle to Understand and Deploy AI Tools

In the era of rapid technological advancement, artificial intelligence (AI) has emerged as a game-changer across various industries. Large enterprises have been quick to adopt AI tools, reaping significant benefits in terms of efficiency, productivity, and decision-making. However, the same cannot be said for small and medium-sized enterprises (SMEs). Despite the immense potential AI holds for SMEs, they often face significant challenges in understanding and deploying these tools. In this article, we explore the reasons behind this struggle and potential solutions to bridge the gap.

  1. Limited Awareness and Resources:

One of the main reasons for SMEs’ struggle with AI adoption is a lack of awareness about its capabilities and potential benefits. Many small business owners and managers have limited exposure to AI technology, don’t know what prompts are, or how to use AI in executive decision making such as pre-mortem analysis, leading to misconceptions or doubts about its applicability. Additionally, they may perceive AI as expensive and suitable only for larger companies with abundant resources, making them hesitant to invest.

Of course another huge factor for most SME managers is time shortage. It’s very apparent that no-one can keep up with the pace of AI developments anymore with reports on Twitter of well over 1,000 new AI products being launched every month (July 2023). So how do you as an SME keep up? You don’t even have the time to know where to look for new AI tools and services.

  1. Complex Terminology and Technical Jargon:

The field of AI is filled with complex terminologies and technical jargon, which can be intimidating for individuals without a technical background. SMEs often find it challenging to grasp the concepts behind AI, machine learning, deep learning, and related technologies, hindering their ability to make informed decisions about adopting AI tools.

  1. Lack of Expertise and Skills:

Implementing AI tools requires specialized expertise and skills. SMEs often struggle to find or afford qualified AI professionals who can help them understand their specific business needs, choose appropriate AI solutions, and integrate them seamlessly into existing workflows. AI FOMO (fear of missing out) is widespread too – the sense that everyone else is getting ahead and you are not. This could be true. As someone said, you won’t be put out of business by AI, but you could be put out of business by a competitor who uses AI.

  1. Data Limitations and Quality:

AI thrives on data, and the quality and quantity of data play a critical role in the success of AI applications. SMEs may not have access to large datasets required for training sophisticated AI models. Moreover, the data they possess might not be well-structured or of high enough quality to produce reliable results.

  1. Fear of Job Displacement:

A common fear among SMEs is that AI adoption might lead to job displacement, making employees resistant to change. This fear can be addressed through proper communication and the demonstration of AI’s potential to enhance productivity, allowing employees to focus on higher-value tasks rather than mundane ones.

  1. Complexity in AI Implementation:

Even with awareness and resources, the process of implementing AI tools can be complex and time-consuming. From choosing the right AI solution to integrating it into existing systems, SMEs may find themselves overwhelmed by the technical challenges, delaying or derailing their AI deployment plans.

Solutions and Recommendations:

To address the struggles faced by SMEs in adopting AI tools, several solutions and recommendations can be considered:

  1. Increasing Awareness and Education:

Government bodies, industry associations, and AI vendors should collaborate to conduct workshops, webinars, and training sessions to increase awareness among SMEs about AI technology, its benefits, and successful case studies.

  1. Simplifying AI Terminology:

AI vendors and experts must make a conscious effort to communicate in plain language, avoiding technical jargon whenever possible. This approach can make AI more accessible and less daunting for SMEs.

  1. Developing AI Tools for SMEs:

AI developers should create specialized tools that cater to the specific needs and budgets of SMEs. These tools should be user-friendly, easy to integrate, and affordable, promoting wider adoption.

  1. Encouraging Partnerships:

SMEs can form partnerships with AI service providers, startups, or educational institutions to access AI expertise and resources. Such collaborations can accelerate AI adoption and alleviate the burden of implementing AI solutions independently.

  1. Data Collaboration:

Government initiatives can encourage data sharing among SMEs, ensuring that smaller businesses can access diverse datasets for AI training. Data cooperatives and regulatory frameworks can facilitate secure and ethical data sharing.


The potential of AI to revolutionize business operations is undeniable, and SMEs stand to benefit greatly from its adoption. However, the struggle to understand and deploy AI tools persists due to challenges such as limited awareness, complex technicalities, and data constraints. To overcome these hurdles, SMEs must be supported through increased education, simplified AI tools, strategic partnerships, and data collaboration. By working collectively to bridge the knowledge gap, SMEs can harness the power of AI and embrace a more innovative and prosperous future.

One solution is to use AI consultancy firms like to help. Get in touch today.

Good prompting is not a sustainable advantage

As of April 2023, prompt writing has emerged as a valuable skill in the world of artificial intelligence. However, while it may a valuable skill, it isn’t be a complex skill that takes years to perfect and so its potential for providing a sustainable advantage in business is debatable. As the same time, a lack of prompt writing skills is rapidly going to be a distinct disadvantage. Business owner / managers that fail to learn even the basics of prompting will end up with an unsustainable disadvantage.

The learning curve for prompt writing involves understanding that poor prompts can be transformed into better ones, which can eventually lead to good prompts. Tools like ChatGPT and similar systems facilitate this process – you iteratively ask them how improve your prompts. So for example, if you want ask ChatGPT how to win more sales, instead of asking it how you can win more sales, ask it first what information it would need to provide you with the most actionable advice.

Example: “How can I increase my sales?”

Increasing sales can be a complex process, but here are some tips that can help:

  • Increasing sales can be a complex process, but here are some tips that can help:
  • Understand your target market: Identify who your ideal customer is and what they are looking for in your product or service. This can help you tailor your sales strategy to meet their needs.
  • Improve your product or service: Make sure your product or service is of high quality and meets the needs of your target market. Gather feedback from your customers to identify areas for improvement.
  • Focus on customer service: Providing excellent customer service can help build customer loyalty and encourage repeat business. Make sure your customers feel valued and supported throughout the sales process.
  • Utilize social media: Use social media platforms like Facebook, Instagram, Twitter, and LinkedIn to reach your target market and promote your product or service.
  • Offer promotions and discounts: Offering discounts or promotions can incentivize potential customers to make a purchase. Make sure the discounts are attractive but also sustainable for your business.
  • Network and collaborate: Collaborate with other businesses or influencers in your industry to expand your reach and gain new customers.
  • Track and analyze your sales data: Keep track of your sales data to identify trends and areas for improvement. Analyzing your data can help you make data-driven decisions to improve your sales strategy.

What information do you need to improve on this response?

As an AI language model, I am always looking to improve my responses. In order to provide more tailored and specific advice for increasing sales, it would be helpful to have more context about the specific industry, product or service, target market, current sales strategy, and any previous sales data. This information would allow me to provide more customized and targeted suggestions for improving sales.

Ethan Mollick‘s statement on Twitter highlights how easy it is to learn to prompt well:

“A lot of companies are building products on top of GPT. The main source of advantage for many of them is their prompt… But it is really easy to get an AI to give you its prompt.”

This suggests that building a business moat, or a sustainable competitive advantage, based solely on prompt writing may not be viable.

It is important to note that this analysis is most applicable to businesses at the forefront of AI integration than to the majority of companies. One can draw a parallel to the effective use of Google searches, which, in theory, should not provide a competitive advantage since it is an easily acquired skill. However, not all users maximize the potential of Google Search, which means that expert users still maintain an advantage over non-experts, even if it is not theoretically a sustainable one.

The reality is though that most business owners lack the time to learn and apply prompt writing skills. While companies with a keen focus on AI tools are likely to invest in learning effective prompting techniques as a matter of priority, the majority of businesses may only scratch the surface of AI’s potential at this stage in its development. Such companies won’t gain a sustainable advantage through prompt writing, as they might not even understand the concept of a good prompt in the first place.

While Mollick’s comments are primarily directed at AI businesses built on good prompting techniques, the broader implication is that business owners who do not invest time in learning about prompt writing may find themselves at a competitive disadvantage compared to those who do.

The extent to which businesses are willing to invest time and resources into learning and applying prompt writing techniques may ultimately determine the competitive edge they gain in the evolving world of AI.

Small businesses need a “Prompts 101” to kick off the process and whilst any prompt skills may not result in a sustainable advantage, a lack of prompting skill will be a unsustainable disadvantage.

Regenerate Response

See the phrase “Regenerate response” at the bottom of an article? It is almost certain that someone created it using ChatGPT and the author hasn’t properly proof-checked it.

Enter a prompt into ChatGPT and it generates a response. At the bottom of its response is a button with the words ‘Regenerate response” on it. Clicking that button makes ChatGPT generate a new response to your original prompt. One way that people use the output of ChatGPT is simply to copy and paste it into their website or indeed into a document. If you do this by highlighting the complete response on a screen and copying and pasting, you can inadvertently get the submit button’s instructions included at the end of the text.

Regenerate response button screenshot ChatGPT4

If someone is in a hurry or just lazy, they can miss this and so “their” pasted article ends with that phrase. So if you do see that phrase, it can be quite revealing. People who use ChatGPT to generate a lot of copy are probably going to make this mistake quite often.

Regenerate response

Using ChatGPT for pre-mortems

A pre-mortem is a powerful business technique where you take a leap into a future where your project has failed and you discuss where it went wrong. It helps teams identify potential issues and develop solutions before the project has launched. It involves critical thinking and some degree of creativity. But it can also generate some insights that in extreme cases can stop you from working on your project any further. Using ChatGPT for pre-mortems is an very low cost method of doing this without the need to convene any management meetings

Using ChatGPT for Pre-mortems

ChatGPT-4, the latest iteration (as of April 2023) of OpenAI’s powerful language model, is an invaluable business asset that can help reduce project management disasters. By using the right prompts, project teams can simulate failures before a project has started and use the analysis to identify and proactively mitigate potential risks. This method not only saves time and resources but also fosters a wider business culture of proactive problem solving.

Example Pre-mortem Prompt 1 – Product launch

“Assume that our new product launch has been a failure. The product was designed to do x and we developed it because we thought it would sell profitably in the y market. List the top 5 reasons why this might have occurred and suggest ways to address each of these issues.”

Why this works: This prompt encourages ChatGPT-4 to analyze and generate potential reasons for failure, helping the team identify potential risks and their corresponding solutions. By addressing the top 5 reasons, the model provides a focused analysis, ensuring that the most critical aspects are considered. Additionally, the prompt asks for ways to address each issue, allowing teams to develop preemptive strategies for success.

You can also ask ChatGPT to rank the reasons for failure in terms of likelihood, cost impact and so on. Use your description of what the product does to give ChatGPT as much background information as you can. Ask it follow up questions too.

Example Pre-mortem Prompt 2 – Marketing campaign

Prompt: “Imagine our marketing campaign for our new product x failed to achieve the goals we set in terms of sales and customer engagement. Our marketing campaign consisted of social media promotion, geo-targeted Google Ads and local mailshots. Describe four possible flaws in our campaign strategy and provide recommendations on how to improve each of them.”

Why it works: This prompt targets a specific area of the project, the marketing campaign, and directs ChatGPT-4 to evaluate potential shortcomings. Asking for a specific number of possible flaws helps ChatGPT to provide ran analysis that will have four separate elements which you can then rank. The specific request for recommendations for improvement will accelerate the process of finding solutions and help ideation.

Both these examples focus on product launches which is an important business process but there are many other areas where pre-mortems are helpful. Let’s look at one about recruitment.

Example Pre-mortem 3 – Recruitment

Prompt: “Our recent hiring process resulted in a high employee turnover rate within the first six months. Identify four factors that might have contributed to this outcome and suggest improvements for each factor in our hiring process.”

Why it works: This prompt focuses in on the hiring process and its potential impact on employee retention. By asking ChatGPT-4 to explore four contributing factors, the model is encouraged to delve into various aspects of the hiring process that might have led to a high turnover rate. This comprehensive examination helps the HR team pinpoint areas in need of improvement. By requesting suggestions for each factor, the team can develop a more effective hiring strategy to ensure they attract and retain the right talent.

The cost of doing pre-mortems

A typical business pre-mortem involves a meeting of your project team and a lot of discussion which takes time and therefore costs money. Of course, it can also save a lot of money down the line if it results in actionable outcomes that boost the chances of the project’s success. Using ChatGPT and similar tools to do a pre-mortem takes a few minutes and whilst not necessarily as effective as a full-blown pre-mortem management meeting, it can deliver results extremely cheaply. These results may deliver actionable outcomes on their own but just as significantly, they can be used as a business accelerant by acting as briefing notes for your own pre-mortem. Don’t forget too that you can ask ChatGPT to regenerate its response to come up with more ideas and that you can ask it to explain more about any aspects of its answers.


By integrating ChatGPT-4 into pre-mortem exercises, businesses can unlock innovative and efficient ways to identify and address potential project failures for negligible cost. By formulating targeted and focused prompts, teams can extract valuable and actionable insights from the AI, which enables them to make better decisions and reduce implementation risks.

Pre-mortem action point

Managers should do pre-mortems using AI tools like ChatGPT-4 as a matter of habit. Using ChatGPT for pre-mortems should be as habitualised as using Google for search used to be.

ChatGPT Prompt Engineering 101, an Introduction

Welcome to ChatGPT Prompt Engineering 101.

Crafting effective prompts for AI language models like ChatGPT has become an essential skill for professionals across many industries. Indeed very early on lawyers in the UK were advertising for prompt engineers. This article guides you through the fundamentals of prompt engineering, demonstrating how well-crafted prompts can unlock the full potential of AI-generated content as well as setting out where you can go wrong. Whether you’re a content creator, a customer service professional, or a curious learner, understanding the art and science of prompt engineering is vital to harnessing the power of AI and maximizing its benefits.

The good news is that whilst prompt engineering sounds technical, a key feature of products like ChatGPT is that you can use natural language to tell them what to do. At the time of writing the terminology that has evolved to describe the process of crafting these instructions is called prompt engineering which is quite a misnomer. It seems highly likely that this terminology will change over time because the whole point of tools like ChatGPT is that you can essentially talk to them rather than have to write any sort of code to instruct them. Unless you specifically want ChatGPT to generate software, something that it does remarkably well, you do not need any engineering skills whatsoever. ChatGPT and other systems came out of software and AI engineering labs which probably explains the derivation.

So put aside any concerns you had about not being an engineer or technically minded. It really doesn’t matter.

Definition of Prompt Engineering

Prompt engineering is the process of crafting effective prompts to guide the responses of AI language models like ChatGPT. It involves understanding the model’s behavior and tailoring inputs to achieve desired outputs.

Importance of Crafting Effective Prompts

Crafting the right prompts is crucial in obtaining useful and accurate responses from language models. An effective prompt ensures that the AI understands the user’s intent and provides relevant information or solutions.

Good Prompts Generate Good Responses

The Impact of Well-Crafted Prompts on ChatGPT’s Output

A well-crafted prompt helps ChatGPT provide more accurate, relevant, and coherent responses. It sets clear expectations for the AI and enables it to generate content that addresses the user’s needs.

Examples of Good Prompts and Their Corresponding Responses

By comparing prompts and their responses, we can observe the difference between effective and ineffective prompts. For example, a vague prompt like “tell me about climate change” might yield a broad response, while a more specific prompt like “explain the main causes of climate change and its effects on biodiversity” will generate a focused and informative answer.

Detailed Prompts Generate Better Responses

The Benefits of Providing Specific Information in Prompts

Detailed prompts enable ChatGPT to provide more accurate and relevant information. By including specific details, users can guide the AI to focus on particular aspects or perspectives, resulting in higher-quality responses.

Strategies for Creating Detailed Prompts

  • Specify the desired format or structure of the response
  • Include relevant context or background information
  • Ask for specific examples or case studies
  • Limit the scope of the topic to avoid overly broad answers

Examples of Detailed Prompts and Their Improved Responses

Consider the following prompt pairs:

Vague: “Write about healthy eating.”

Detailed: “Describe the benefits of a plant-based diet for heart health and provide three meal ideas.”

The detailed prompt leads to a more targeted and useful response by specifying the diet type, desired benefits, and request for meal ideas.

How to Upload Relevant Data for Use in the Generation Process

Uploading additional data to ChatGPT can improve the quality of its responses. Users can provide context or reference materials, such as articles or research papers, which the AI can then use to generate more informed answers.

Benefits of Data-Driven Prompt Engineering

  • Incorporating external data sources can help ChatGPT:
  • Produce more accurate and up-to-date information
  • Understand complex concepts or industry-specific terminology
  • Generate content tailored to the user’s specific needs and preferences

Best Practices for Data Integration

  • Choose reliable and reputable data sources
  • Upload data in a format that is easily readable by the AI
  • Include clear instructions for the AI to reference the uploaded data
  • Tips on Prompt Crafting

Essential Elements of Effective Prompts

Clarity: Ensure the prompt is easy to understand and free from ambiguity

Brevity: Keep prompts concise and focused on the main topic

Specificity: Include necessary details to guide the AI’s response

Techniques for Refining Prompts

Iterate and experiment with different phrasings or approaches

Review and analyze AI-generated responses to identify areas for improvement

Collaborate with others to gain new perspectives and ideas

The Iterative Process of Prompt Engineering

Prompt engineering is an ongoing process that involves testing, refining, and retesting prompts to optimize AI performance. Continual feedback and adaptation are key to successful prompt engineering.

The Role of Prompt Engineering in AI-Based Applications

Effective prompt engineering ensures that AI-generated content meets the needs of various applications, including customer service, content creation, marketing, and more. By crafting targeted prompts, users can harness the full potential of AI language models like ChatGPT.

Industry Applications of Effective Prompt Engineering

Prompt engineering skills are crucial in industries where AI-generated content plays a significant role, such as customer support, content marketing, medical research, and finance. Well-crafted prompts enable AI to generate valuable insights and solutions in these domains.

Industries Where Prompt Engineering Matters Most

Customer Service and Support

Prompt engineering helps customer service professionals create AI-driven responses that accurately address customer inquiries, improving efficiency and customer satisfaction.

Content Creation and Marketing

Content creators and marketers can use prompt engineering to generate engaging, relevant, and targeted content for various platforms, such as blog posts, social media updates, and email campaigns.

Healthcare and Medical Research

Healthcare professionals and researchers can leverage prompt engineering to obtain AI-generated summaries of complex medical literature or generate patient-specific health recommendations.

Education and Training

Educators can use prompt engineering to create personalized learning materials, develop engaging lesson plans, and generate AI-driven feedback for students.

Finance and Risk Management

Financial analysts and risk managers can use prompt engineering to generate AI-driven insights, analyze market trends, and forecast potential risks.

Learning to Write Effective Prompts

Resources for Prompt Engineering Education

Online courses and tutorials on AI and natural language processing

Blogs, articles, and case studies on prompt engineering best practices

AI communities and forums for networking and collaboration

Strategies for Self-Directed Learning

Experiment with various prompts and analyze the AI-generated responses

Seek feedback from peers or experts in the field

Continuously refine your prompt engineering skills through practice and iteration

Networking and Collaborating with Other Prompt Engineers

Join AI and prompt engineering communities or social media groups

Attend conferences, workshops, and webinars focused on AI and natural language processing

Collaborate on projects or challenges with other prompt engineers to learn from their expertise

Common Mistakes in Prompt Crafting

Using ambiguous or unclear language

Overloading the prompt with unnecessary details

Neglecting to specify the desired format or structure of the response

The Impact of Poorly Crafted Prompts on AI-Generated Content

Ineffective prompts can lead to AI-generated content that is:

  • Off-topic or irrelevant to the user’s needs
  • Inaccurate or lacking in detail
  • Difficult to understand or poorly structured

Strategies for Mitigating ChatGPT Prompt-Related Issues

Review and revise prompts based on AI-generated content and feedback

Consult resources and experts to improve prompt crafting skills

Experiment with different prompt styles and techniques to find the most effective approach

What is your App half-life?

App half-life is the time it takes for your app usage to halve. An immediate result of the rapid rollout of LLM tools like ChatGPT, ChatGPT-4 and Bard is that application development has accelerated. Acceleration leads to faster execution and, just as significantly, it leads to lower-cost execution. Anyone with an idea for an app can generate an app. Anyone with an idea for an app but with no money can also generate an app. Furthermore, you don’t need to know how to code. There’s a marketing arms race for attention and we are already at DefCon No-Code. But this is a problem for app half-life. What is the half life of your app going to be?

Against this backdrop, app churn is going to go exponential. It’s too easy to create newer, better, faster, cheaper, shinier apps in an already crowded space and it’s getting harder to build moats: factors that protect you from competitors. The half-life of new app-based businesses is dropping, fast. ChatGPT and Bard have accelerated this trend.

If anyone can create an app then apps themselves, which are already fighting for attention-space in the app stores, are going to be impossible to defend from a marketing point of view unless they are supported by either extraordinary, existing brand power or by existing channels to market. Preferably both.

What this means for developers is that, even if you create an app that is outstanding in a given niche, it will be days or less before a competitor app does the same thing albeit with a little more magic dust sprinkled on it in terms of features. And there’s an app to spot new apps.

Two unstoppable forces are at play. The cost of app dev has plummeted. It’s effectively zero now and as apps are used to develop apps and apps develop apps that are themselves used to develop apps etc. there are parallels with the AI singularity. As a result, the number of functional apps vying for consumer attention is rocketing. But there is still a relatively fixed number of human attention minutes (HAMs) available. Consequence: an almost impossible to win, Pareto distribution, free-for-all fight. The cost of consumer attention, defined as the number of apps needed to get a single HAM is subject to almost Zimbabwean inflation.

Apps will need sophisticated, clever, fast-learning and intelligent marketing algorithms to get any significant attention at all. But there will be an app for that too, available to other apps. So developers are already in an attention-seeking arms race.

The second force is that app stores, already impossible to navigate easily, are crowded spaces and most apps, even excellent ones, are being crushed by sheer weight of competitor numbers.

With the cost of app development plummeting, app stuffing will be a growing problem. App stuffing, like keyword stuffing, is a brute-force method of gaining HAMs by developing large numbers of apps that operate in the same functional area. A consumer searching for a dieting app is already overwhelmed with options – I counted well over 100 diet apps before I got bored of counting – and if your 50 apps appear alongside 20 others from different developers, you stand the greatest chance of a download. App store curation does help of course but algorithms are busily analysing these too in order to game them.

A measure of how this is going is the half-life of an app as defined by the average number of days that pass before usage drops by 50%. There are, of course, many apps that never get used at all whilst others seem to dominate the market although they too are subject to decay.

So how to deal with this as an app marketer? You need to establish and build a brand. Successful companies know this and invest $millions in brand awareness etc. For individual developers, one method is to build a personal brand on Twitter.

If you are an individual and need to know how to do this, just ask ChatGPT. It’s a crowded space already.

Key concepts: App stuffing, App half life.

Mishcon de Reya GPT Legal Prompt Engineer

It’s extraordinary how quickly businesses are starting to adopt GPT technology to get a competitive edge. Professional services such as lawyers, accountants, consultants, actuaries will need to move fast if they are not going to be left behind. Much of the grunt work done by these firms, work that is typically charged out at pretty high fee rates and done by entry level staff, can now be done faster by AI tools and, as technology advances and improves exponentially, better and a great deal cheaper. In London, Mishcon de Reya have recently advertised for a Legal Prompt Engineer which is interesting not least in terms of how rapidly they’ve moved.

How then are the current fee levels going to hold up? Will the introduction of AI tools such as ChatGPT and now Bing with Chat finally start to deliver lower fees? Professional services have been notoriously resistant to downward pressure on fees but if a good legal prompt, especially when done in conjunction with an upload of key case documents, can deliver the sort of analysis in seconds traditionally done by junior lawyers in days, there’s some hope for buyers of legal services. It won’t stop senior lawyers charging a fortune but it may reduce billings from junior staff.

At vCAIO we can’t see professional services using the existing pyramidal structures of seniors supported by a broad base of lower tier professionals much longer because it won’t only be the lawyers who are using AI – their clients will be using AI too which means a lot of what they are currently paying for will be available to them directly from their own desktops. Once businesses master the use of prompts they’ll start to ask their professional advisers how much they rely on prompts to deliver the services they are paying for. This ultimately could lead to a reduction in the number of low and mid tier professionals whilst potentially enhancing fee rates for the most able senior partners. The days of charging huge fees for hours of work by junior staff could be coming to an end. Afterall, what is the hourly rate for ChatGPT?

It’s currently 19 cents and is available 24/7.

Chief AI Officers will become key C-Suite executives

Virtual Chief AI Officers will be key C-Suite members in successful businesses for 3 reasons.

  1. AI will be exploited in all business departments from marketing to production, from accounting to legal, from HR to strategy, from capital allocation decisions to mergers and acquisitions.
  2. Business will need to do things better, faster and cheaper to survive and remain competitive.
  3. Those that exploit AI most effectively will be the winners.

Utilising AI tools to maximum effect will demand Board level representation to make sure its adoption is sponsored across the organisation.

Will there be a conflict with IT? Yes. But smart CTOs will already have recognised the importance and value of AI as a code-writing accelerator, as a security enhancer and as client support agent that will reduce the demands made on expensive staff whilst freeing them up to focus on higher value activities.

Crafting effective ChatGPT prompts

As an AI language model, ChatGPT is designed to understand and respond to human language in a way that is as natural and intuitive as possible. However, the accuracy and relevance of the responses generated by ChatGPT depend largely on the quality and specificity of the ChatGPT prompt provided by the user. In other words, the more detailed and specific a prompt is, the better ChatGPT can understand the user’s needs and provide more relevant and helpful respon§ses.

One of the main reasons why specificity is so important is that natural language is inherently ambiguous and context-dependent.

For example, a simple prompt like “What is the weather like?” can be interpreted in many different ways depending on the user’s location, the time of day, the season, and other contextual factors. If the prompt is too vague or generic, ChatGPT may struggle to provide a response that is accurate or relevant to the user’s specific needs.

On the other hand, if the prompt is more specific and detailed, ChatGPT can leverage its deep learning algorithms and vast knowledge base to generate responses that are tailored to the user’s unique circumstances. For example, a prompt like “What is the weather like in New York City right now?” provides ChatGPT with a much clearer context and allows it to generate a response that is more accurate and relevant to the user’s needs.

Another reason why specificity is so important is that it helps to reduce ambiguity and confusion in the communication process. When prompts are too general or vague, ChatGPT may generate responses that are not entirely relevant to the user’s needs, leading to frustration and confusion. By providing more specific and detailed prompts, users can ensure that ChatGPT is better equipped to understand their needs and provide responses that are more accurate and helpful.

Moreover, the specificity of the prompt is crucial when it comes to complex or technical topics. For instance, if a user is seeking medical advice, a prompt like “What should I do if I have a headache?” may not be sufficient to provide them with the information they need. However, a prompt like “What are the possible causes and treatments for migraines?” can provide ChatGPT with a much clearer context and allow it to generate more detailed and accurate responses.

Prompt Specificity

The specificity and detail of prompts are essential for the effectiveness of ChatGPT. The more detailed and specific the prompt is, the more accurate and relevant the responses generated by ChatGPT will be. By taking the time to provide specific and detailed prompts, users can ensure that ChatGPT understands their needs and provides them with the most helpful responses possible.

Incidentally, the fact that ChatGPT can understand highly specific English language prompts is often overlooked as a major leap forward in AI. The internet is abuzz with arguments about the quality of ChatGPT’s output but what in many ways is just as remarkable is how well it deals with inputs. ChatGPT’s ability to comprehend complex, highly specific prompts is a totally new phenomenon. We will be chatting with ChatGPT very shortly – beats the hell out of Siri.

Prior to AI tools like ChatGPT it used to be the case with computers that “garbage in, garbage out”. In other words, if you put in bad data or write bad programs or construct bad searches, you get bad outputs. Consequently you had to craft your instructions with a lot of thought and care. As this article about Chat GPT and GIGO explains, this no longer applies.