When I left Silicon Valley in 2014, I made a conscious choice to step away from social media and let my blog fade into digital silence. It was time to live life away from the constant hum of online presence. Fast forward to today, and I find myself drawn back to public discourse—not out of necessity, but from a genuine desire to share in this transformative era of AI and technology.
Recently, I encountered a peculiar issue with my Gatsby-based blog: the RSS feed was timestamping posts with the build time instead of the actual publication date. While this might seem like a minor inconvenience, it was creating friction in my content distribution workflow, requiring manual intervention where automation should prevail.
The solution journey was significantly enhanced by my development setup. Using VSCode with the Cline plugin provided a seamless environment for AI pair programming. What makes Cline particularly powerful is its ability to switch between different AI models and maintain context. I could easily:
The solution came through an interesting collaboration with AI assistants. I pulled my Gatsby.js configuration into O1, using it to explore my GraphQL database and verify the existence of date fields. This exploration, combined with brainstorming sessions through Claude/Sonnet via Cline’s planning mode, led to a comprehensive solution.
The root cause? A subtle but important syntax change in Gatsby v3+. Here’s what we discovered:
# Old syntax (causing the issue) allArticle(sort: { date: DESC }) { nodes { date # ... } } # Correct syntax for Gatsby v3+ allArticle(sort: { fields: [date], order: DESC }) { nodes { date # ... } }
The solution involved three key components:
nodes
and edges
query structuresThis fix, while technical in nature, represents something larger than just correcting a timestamp. It’s about streamlining the pipeline between thought and distribution. With the RSS feed now correctly dated, my content flows automatically to various networks—including my old Facebook page, reaching those who haven’t heard from me there in years.
This experience exemplifies why I believe in “Learning in the Open.” At Austin LangChain AIMUG (aimug.org), we emphasize the importance of sharing our learning journey, including the challenges and solutions we discover along the way. AI tools have become invaluable partners in this process, not just solving problems but helping us articulate and share our solutions more effectively.
The past few years have seen me gradually re-emerge into public discourse, but with a different purpose. Whether it’s speaking at events, guiding our “Learning in the Open” initiatives at Austin LangChain AIMUG, or sharing technical insights like this RSS feed fix, each interaction is an opportunity to contribute to our collective understanding of this AI-enhanced future.
As we continue to navigate this technological renaissance, the value of sharing our experiences—both successes and challenges—becomes increasingly apparent. The tools we use, like AI assistants, aren’t just helping us solve problems; they’re helping us become better teachers and learners in this interconnected world.
After a year back on professional networks, I’ve found these platforms transformed from mere social networks into vibrant technical communities. You can follow my journey and join the discussion:
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