In this episode of The Mod Squad , hosts Paul Barnhurst, Ian Schnoor, and Giles Male continue their exploration of tools for financial modeling. This time, they test Melder, a tool designed to streamline financial modeling tasks in Excel. The hosts evaluate how it handles various financial exercises, such as creating formulas and generating a deferred revenue schedule. While the tool shows promise, the hosts identify areas where Melder has room to improve, particularly with bugs and user experience quirks. This episode also highlights the challenges of using tools still in beta. Expect to Learn A detailed review of Melder’s features for Excel-based financial modeling. How Melder compares to other tools previously tested by the team. Challenges faced when using Melder for tasks like building formulas and financial schedules. The pros and cons of using Melder, especially when it comes to its unique features and limitations. Insights into tools’ development process, especially when still in beta. Here are a few quotes from the episode: "I appreciate the confidence behind the bold statements, but at the end of the day, tools need to make sure they’re doing the job correctly." – Ian Schnoor "When tools go wrong, it’s not just about fixing the error; it’s about understanding what went wrong so we can avoid future issues." – Giles Male Melder offers some useful features for financial modeling, such as custom formulas and file handling, but it still faces challenges like data overwriting and slow performance. While it shows potential, especially in automating tasks, it needs further refinement to become a reliable tool for complex financial tasks. As it continues to evolve, we look forward to seeing how it improves and addresses these issues. Follow Ian: LinkedIn - https://www.linkedin.com/in/ianschnoor/?originalSubdomain=ca Follow Giles Male: LinkedIn - https://www.linkedin.com/in/giles-male-30643b15/ In today’s episode: [00:31] - What is Melder? [03:30] - Melder’s Website and Features [08:40] - Testing Melder on Financial Modeling Tasks [12:00] - Exploring Melder’s Formula Creation Capabilities [14:30] - Overview of the LLM Model and Google Gemini Models [19:43] - Testing the Trial Balance and Tool's Thought Process [24:08] - Understanding Overengineered Formulas [32:05] - Testing the PVM Use Case and Encountering Errors [41:51] - Final Thoughts and Melder’s Future Potential
