Praveen Yerneni

Few Shot Prompting with CodeLlama, LangChain, and MySQL

Robot Llama

Generative AI has seen an unprecedented surge in the market, and it’s truly remarkable to witness the rapid advancements in technology. Just 11 months since the launch of ChatGPT, we’ve made tremendous progress. What’s particularly fascinating is the swift adoption of generative AI in the open-source community, resulting in the emergence of numerous Large Language Models (LLMs). These open-source LLMs are rapidly narrowing the gap between themselves and commercial counterparts like ChatGPT and Bard (source: https://www.semianalysis.com/p/google-we-have-no-moat-and-neither).

Among the open-source LLMs, two have captured my attention: Llama 2 and CodeLlama. What sets them apart is their accessibility, especially for users like me who can download and run their smaller models (e.g., 7B or 13B) on a CPU-only laptop. Admittedly, my gaming laptop boasts impressive specs, but it’s equipped with an AMD GPU, lacking CUDA support. While there are potential workarounds like DirectML and WSL, I chose not to delve into those complexities. Instead, I opted to work with my current setup, featuring 16 GB of RAM.

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From Engineer to Product Manager: Navigating the ‘How’ and the ‘When’

Agile Process

Welcome back dear readers to our final chapter of this blog series, where we complete this journey of transformation from an engineering mindset to becoming a proficient Product Manager. In our previous discussions, we’ve explored the ‘Why’, ‘Who’, ‘What’, and ‘Where’ stages, uncovering the fundamental pillars of effective product management. Today, we delve into the more actionable realms of the ‘How’ and the ‘When’, where strategy meets execution and timing plays a pivotal role.

As an engineer transitioning into Product Management, I found myself immersed in the ‘How’ stage almost instinctively. Years of technical expertise had conditioned me to focus on execution, yet I quickly learned that a strategic approach is essential to ensure the ‘How’ aligns with the bigger picture. Similarly, the ‘When’ stage became more than just timing; it evolved into a much better understanding of market dynamics, user readiness, and the significance of a roadmap. Let’s dissect these stages and plunge into the specifics.

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