AI Archives - LDNDeveloper

From Innovation to Leadership: My 2024 Journey

As 2024 comes to a close, I want to take a moment to express my heartfelt gratitude to all of you—my readers, followers, and colleagues. Your engagement, feedback, and support have been a constant source of inspiration and motivation. Whether you’ve shared a comment, reached out with questions, or simply taken the time to read my work, I truly appreciate your presence in this journey. Thank you for being part of this year’s growth and discovery.

Reflecting on 2024, I’ve delved into various facets of software development, leadership, and emerging technologies. Here’s a recap of my key experiences and insights from the year:

Unleashing the Power of AI for Business Success

Staying competitive is paramount in the rapidly evolving business landscape. One way to ensure this is by harnessing the power of AI. This blog post will delve into how we can use AI to simplify tasks, make decisions, organize our day, and conduct research. I will also discuss the potential risks associated with using AI and how to mitigate them.

Simplifying Tasks with AI

AI can automate repetitive tasks, freeing our time to focus on more complex issues. But how does this work? AI tools like Taskade, Todoist, and TimeHero use algorithms to handle data entry, respond to basic customer inquiries, or sort and categorize emails. These tools learn from the data they process, improving their performance.

What is Jira Query Language (JQL)?

Jira Query Language (JQL) is a text-based query language used to extract specific data from the Jira database. Jira is a swamp of tickets that can weigh you down in the mud of ambiguity, but JQL can help you navigate once you know the syntax. With JQL, you can create structured queries to retrieve the desired issues based on various criteria.

Why Is JQL Essential?

Search for Issues: Use JQL to search for issues based on project name, issue type, status, assignee, priority, and more.
Operators and Functions: JQL supports a range of operators to compare values, combine conditions, and perform text matching.
Agile Project Management: JQL is particularly valuable for agile teams, as it maintains clarity and alignment among team members and stakeholders.
Quick Access to Information: JQL enables quick access to relevant information, allowing you to focus on essential tasks.

A Comprehensive Guide for Support Managers

Introduction

Being a new support manager or suddenly finding yourself responsible for the success of a support team is a little unnerving. There are plenty of resources online, but here is a summary of things I have learned while running a support team. I hope everyone else finds this helpful. Feel free to reach out to me on LinkedIn with your questions or concerns or even to be mentored; I love meeting new friends.

A Data Architect’s Guide to Database Design and Management

Introduction

Designing and managing databases is a critical task in data architecture. This blog post aims to provide insights into various aspects of database design, hosting, security, scalability, and the use of data for machine learning or AI.

Evaluating AI – Top 5 Security Considerations

Artificial Intelligence (AI) has become a game-changer in many industries, offering unprecedented opportunities for innovation and growth. However, as with any technology, it’s essential to consider the security implications when evaluating the use of AI. Here are the top five security considerations:

Data Privacy: AI systems often require access to vast amounts of data, including sensitive information. Ensuring that this data is handled securely and in compliance with privacy laws is paramount.
Robustness of AI Models: AI models should be robust against adversarial attacks where small, intentionally crafted changes to input data can lead to significant errors in output.
Secure AI Development Lifecycle: Security should be integrated into every stage of the AI development lifecycle, from the initial design to the deployment and maintenance stages.
Explainability and Transparency: Understanding how an AI system makes decisions can help identify potential security risks. AI systems should be transparent and provide clear explanations for their choices.
Regulatory Compliance: Depending on the industry and region, different regulations may apply to the use of AI. Ensuring compliance with these regulations is a crucial security consideration.

ChatGPT to Create Acceptance Criteria

Today’s Learning

Today, I took a business requirement and put it into ChatGPT. I created a couple of simple prompts. The first prompt created acceptance criteria to make the software developer successful. The second prompt was to create test cases.

Surprisingly enough, it generated some pretty accurate results.