Experiments With Gen AI, Knowledge Graphs, Workflows, and Python
May 9, 2025
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Raymond Camden, a developer evangelist focused on APIs and AI, shares his adventures in Python and innovative projects. He discusses building a generative AI resume review system and an automated sentiment analysis tool using Diffbot's knowledge graph. Raymond dives into the challenges of learning Python, the importance of documenting his journey, and how he integrates his streaming content with his blog. The conversation also highlights the creative uses of AI in coding, emphasizing collaboration and thoughtful implementation to enhance user experiences.
Raymond Camden emphasizes the importance of practical application in mastering Python, having transitioned from various programming languages to embrace its unique features.
His recent projects showcase the versatility of Python, particularly in developing tools like a resume review system using Generative AI and Flask.
Camden highlights the role of developer relations in fostering effective communication and documentation, crucial for enhancing user experience and technology adoption.
Deep dives
Raymond Camden's Journey with Python
Raymond Camden's programming journey began in the early 1980s with BASIC on the Apple IIe, transitioning through various languages such as Pascal, Perl, and JavaScript. Despite initially dismissing Python due to its indentation rules, he eventually dedicated time to mastering it through consistent practice and application. His philosophy encourages using Python for tasks he could accomplish easily with JavaScript, aiming to solidify his understanding and muscle memory. Camden's extensive background in front-end, back-end, and development relations brings a unique perspective to learning Python, showcasing a blend of experience in various programming paradigms.
Building a Resume Review System Using Generative AI
One of Camden's recent projects involves creating a resume review and revision tool using Generative AI and Flask. The project demonstrates how Python's simplicity allows for quick implementation of complex functionalities, such as file uploads and AI-driven feedback. He highlights how leveraging Generative AI can transform processes like resume enhancement by providing personalized suggestions based on the content. The ease with which he integrated the AI functionalities into his Flask application exemplifies the power of Python in developing practical and innovative solutions.
Exploring Automated Sentiment Analysis with DiffBot
Camden discusses another project focused on automated sentiment analysis utilizing DiffBot's Knowledge Graph and PipeDream's workflow tools. This tool enables users to handle vast amounts of online data efficiently, identifying articles related to specific keywords and analyzing sentiments surrounding products or individuals. By integrating APIs into a low-code environment, he streamlines the process of retrieving and processing sentiment data. The project's workflow showcases how Python can facilitate connections between different technologies to create powerful monitoring systems for businesses.
The Importance of Developer Relations
Throughout his career, Camden has pursued a path in developer relations, which he attributes to his passion for sharing knowledge through blogging and presentations. He recognizes the significance of effective documentation and user experience in attracting developers to new technologies, highlighting his ability to bridge the gap between users and product teams. His experience gives him insight into what developers need, emphasizing that a smooth and intuitive onboarding process is crucial for adoption. Camden's role in this space exemplifies the need for collaborative communication in tech environments.
The Future of Python and Generative AI
Camden expresses excitement about the evolving landscape of Python and its intersection with generative AI tools. He notes the potential of new tools like UV to streamline Python development and improve user experiences. By exploring generative AI applications, he hopes to harness its capabilities not just for automation but as a means of enhancing creativity and problem-solving skills. His enthusiasm reflects a broader trend of integrating AI technologies into regular workflows, ultimately aiming to make programming more accessible and efficient.
Are you looking for some projects where you can practice your Python skills? Would you like to experiment with building a generative AI app or an automated knowledge graph sentiment analysis tool? This week on the show, we speak with Raymond Camden about his journey into Python, his work in developer relations, and the Python projects featured on his blog.
Raymond is a developer evangelist and advocate who works with APIs, AI, and the web. He’s been expanding his developer knowledge by learning Python and documenting his journey through his blog and with the live-streaming show Code Break.
We discuss a couple of his recent Python projects. The first is building a resume review and revision system with generative AI and Flask. The other project uses Diffbot’s knowledge graph and Pipedream’s workflow tools to create an automated sentiment analysis tool.
In this video course, you’ll find a set of guidelines that will help you start applying your Python skills to solve real-world problems. By the end, you’ll be able to answer the question, “What can you do with Python?”
Topics:
00:00:00 – Introduction
00:03:15 – Programming background and learning Python
00:07:59 – What’s been hard about learning a new language?
00:09:26 – Learning pip, managing packages, and suggesting uv
00:12:26 – Developer relations and sharing knowledge
00:14:40 – Sponsor: AMD - AIatAMD
00:15:17 – Moving things from Code Break to the blog
00:17:27 – Building a resume review and revise system with Gen AI
00:31:58 – Video Course Spotlight
00:33:16 – Adding the revision step
00:35:59 – Exploring code assistance
00:38:52 – Changing into the developer relations role
00:41:40 – Using Diffbot and Pipedream for sentiment analysis project
00:48:06 – Pipedream workflow with Python scripts
00:53:28 – What are you excited about in the world of Python?
00:55:45 – What do you want to learn next?
00:57:45 – How can people follow your work online?
