Bahá'u'lláh's teachings focus, at their core, on the concept of the essential unity of humanity: that we are biologically one "species", we should expand our notions of belonging and compassion to the entirety of humanity, and that doing so is the road to peace. [1]

Another of His teachings is the concept of moderation [2]. One manifestation of that moderation is in the balancing act between "units" of humanity: individual, family, community, institutions, government. Each unit has its prerogatives [3], its spheres of action, overlapping one another, seeking to avoid infringement on the others whilst simultaneously protecting the harmony of all.

Today we are celebrating the second of the Twin Holy days in the Bahá'í calendar: the birth of Bahá'u'lláh, founder of the Bahá'í Faith, in 1817. Yesterday we celebrated the birth of the Báb, born in 1819, who as an independent messenger from God both declared a new religion as a break from Islam, and prophesied that another, greater revelation would come soon after His own. Both were born in Persia, which is today known as Iran. In the lunar calendar used by the Muslim world, their births fell on consecutive days. Consequently, Bahá'ís around the world celebrate them as the "Twin Holy Days".

Entrance to the Bahjí Pilgrim House, near the Shrine of Bahá'u'lláh (source)

Continue...

GitHub Copilot Coding Agent is an impressive and powerful tool for "autonomously" completing development tasks running in GitHub's environment. Like any tool, there is a learning curve ahead before any of us become truly high functioning, beginning with the statement of a well crafted prompt.

⚠️ But I have a concern: lack of commit signing. Should that stop us from adopting Coding Agent? TL;DR conclusion: time to relax the commit signing requirement.

GitHub CoPilot recently promoted Agent mode as a full feature in VS Code. Many writers and commenters in the blogosphere think competitors are still better; perhaps they're right. But this is the one I have, and Microsoft is innovating rapidly - seeing that first hand at Microsoft Build even as I type this. So in recent days I've performed three initial experiments that I want to share. Not because I'm doing anything brilliant: just trying to find tasks that might be a good fit, learn how to interact with the tool, and share a bit to help others in my proximity.

Lesson: be patient, and be in a learning mode. Not just waiting for it to finish (might take several minutes), but also in getting the right results. I remarked on a failure (below) to my colleague Jason Hoekstra; he suggested that I simply undo and try again. It was the right advice. Experiment and build an intuition.

Below I describe three experiments and outcomes.

Containerization of an application benefits operations of the application by solving the problem of "it works on my machine" (at least, for the application itself). The container holds the operating system and all needed components. Once you have Docker on a host - whether localhost, on-prem data center, or in the Cloud - you can run the application with greater confidence, knowing that the application will execute the same in all environments.

But the benefits of containerization can also shift left in the development lifecycle. For example: have you ever needed to revisit an older application, and realized that you don't have the SDK on your machine? Instead of installing the SDK locally, you may be able to run the SDK in a Docker container.

Data engineering gurus Joe Reis and Matthew Housley once again led a closing town hall at Data Day Texas. Rather than opining from the front, they turned the session over to the wisdom of the crowd. Housley seeded the conversation with a single question – “what is the elephant in the room?” – and the room was ready with an answer: AI. In particular: what is AI going to do to my job?

Given a room full of strangers, some participants were remarkably open about their fears. Perhaps knowing that the audience is composed of fellow data geeks helped to establish a sense of vulnerability. These fears were being expressed by the people who, in theory, should be the ones developing expertise in using AI tooling. But that’s how disruptive the technologies may be: even the data experts are uncertain and afraid.

Notes from three talks on data cataloging at the recent Data Day Texas 2025

• The Meta Grid
• Investing in Semantics and Knowledge
• We Are All Librarians

Following up on Grudgingly Accepting AI Coding Assistants, I have a small win from my first experiment with GitHub Copilot: a Python script for converting portions of an Open API specification file to a CSV. There is nothing revolutionary in this small win; countless programmers have doubtlessly done much more. But a reluctant engineer has to start somewhere.

As a software engineering director building open source products, I have prohibited my teams from using AI coding assistants due to concerns about intellectual property and questions about the risks and real world effectiveness of AI coding assistants. It is now time to allow and even encourage AI coding assistants, with guardrails.

Manager-dom was not a sought-after status (though I admit to prior curiosity), but as with many other engineers-turned-managers, it found me anyway (Q3 2023). Being a team lead and then an architect came naturally and brought success for many years. Some of the skills translate well from those roles while other necessary capabilities tend to be underdeveloped. Nothing can truly substitute for the value of gaining experience and reflecting on it; here are a few resources that I have found useful in my journey so far, giving me new ideas to play with and questions to aid my reflection.