The Prompt Desk Justin Macorin, Bradley Arsenault

Explore the current landscape and future possibilities of AI agents with machine learning experts Justin and Brad. They discuss the trade-offs between specialized and general-purpose agents, the importance of domain expertise, and the potential for agent aggregators. The conversation also covers the standardization of agent-to-agent communication and how organizations may adopt and integrate these technologies.

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Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.
Check out PromptDesk.ai for an open-source prompt management tool.
Check out Brad’s AI Consultancy at bradleyarsenault.me
Add Justin Macorin and Bradley Arsenault on LinkedIn.Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link

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As AI agents powered by large language models become more complex, developers often encounter erratic and unexpected behaviors during testing. From agents falling into infinite loops to models struggling with certain data formats, these issues can be tricky to diagnose and resolve. In this episode, Bradley Arsenault and Justin Macorin explore real-world examples of AI agents going off the rails. They discuss practical techniques like action governors, confusion matrix analysis, minimum task requirements, and targeted fine-tuning to create more robust and reliable agents. Tune in for valuable insights on taming unruly AI from two experienced practitioners at the forefront of prompt engineering and AI product development.
—Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.Check out PromptDesk.ai for an open-source prompt management tool.Check out Brad’s AI Consultancy at bradleyarsenault.meAdd Justin Macorin and Bradley Arsenault on LinkedIn.Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link

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[Bonus] This is a bonus episode. We had too many unreleased episodes in our backlog, so we decided to give you an extra treat this week! Hope you enjoy it!

Join the discussion on how AI agents can intelligently browse websites to retrieve specific information across links and pages. The hosts dive deep into techniques like embedding link text, URL paths, and accessibility attributes to compare against the desired information goal. They explore methods to filter and re-rank links through this embedding approach, accounting for factors like the total number of links per page and whether the target requires navigating across multiple sites.The conversation covers setting reasonable boundaries on recursive browsing, using a large language model for final relevance assessment, and the broader considerations of efficient agent design for web information retrieval tasks. With their combined 25+ years of AI engineering experience, the hosts provide insights into this emerging and complex challenge.

—Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.Check out PromptDesk.ai for an open-source prompt management tool.Check out Brad’s AI Consultancy at bradleyarsenault.meAdd Justin Macorin and Bradley Arsenault on LinkedIn.Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link

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Gain a better understanding of completion vs. chat completion methods for large language models. Get the scoop on why chat completions are great for building chatbots quick, but can sometimes go off the rails. Learn how to keep your model on track with slick moves like tool completions and throwing a "governor" into the mix.
---Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.Check out PromptDesk.ai for an open-source prompt management tool.Check out Brad’s AI Consultancy at bradleyarsenault.meAdd Justin Macorin and Bradley Arsenault on LinkedIn.Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link

Hosted by Ausha. See ausha.co/privacy-policy for more information.

[Bonus] This is a bonus episode. We had too many unreleased episodes in our backlog, so we decided to give you an extra treat this week! Hope you enjoy it!

Dive into the world of prompt engineering for large language models like GPT. This episode explores the important role that non-technical subject matter experts play in developing effective AI prompts and systems. The hosts discuss how domain experts across industries like food, real estate, and medicine are uniquely qualified to label training data, provide contextual knowledge, and design prompts that capture the right tone and style for their field.

The hosts argue that while engineering expertise is needed for certain technical aspects, most prompts should be designed collaboratively with non-technical experts leading the way. With over 25 years of combined AI and product experience, the hosts share insights on bridging the gap between technical and non-technical teams for successful prompt engineering.

—Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.Check out PromptDesk.ai for an open-source prompt management tool.Check out Brad’s AI Consultancy at bradleyarsenault.meAdd Justin Macorin and Bradley Arsenault on LinkedIn.Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link

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In this insightful episode, hosts Justin Macorin and Bradley Arsenault chat with AI expert Abi Aryan to dive deep into the challenges of measuring the business impact of large language model applications. Abby draws from her 8 years of experience deploying and productizing LLMs to provide a comprehensive framework for defining relevant metrics.She emphasizes the importance of bridging the gap between engineering and business objectives, highlighting that 76% of machine learning projects fail due to this disconnect. Abby shares practical advice on evaluating LLM performance through a combination of language skills assessment, task-specific metrics, human evaluation, and aligning with overarching business goals.The conversation covers key topics such as measuring the efficacy of retrieval versus generation components, incorporating user feedback beyond simple thumbs-up/thumbs-downs, detecting and mitigating hallucinations, and tying metrics to concrete business KPIs like sales funnels and revenue generation.---
Please check out Abi on LinkedIn at https://www.linkedin.com/in/goabiaryan/Visit her website here: https://abiaryan.com/Continue listening to The Prompt Desk Podcast for everything LLM & GPT, Prompt Engineering, Generative AI, and LLM Security.Check out PromptDesk.ai for an open-source prompt management tool.Check out Brad’s AI Consultancy at bradleyarsenault.meAdd Justin Macorin and Bradley Arsenault on LinkedIn.Please fill out our listener survey here to help us create a better podcast: https://docs.google.com/forms/d/e/1FAIpQLSfNjWlWyg8zROYmGX745a56AtagX_7cS16jyhjV2u_ebgc-tw/viewform?usp=sf_link

Hosted by Ausha. See ausha.co/privacy-policy for more information.