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โI feel there is one element of leadership that has been ignored for too long. A very important element: great leaders lead by not doing much.
Great leaders are masterful because they don't get in the way. They don't interfere. When you step away from your ego and you release your competitive streak, you become nicer, better, and more effective. When you don't force your ideas on everyone else, when you don't force a direction, magical things happen.
Your team comes together. They come up with amazing ideas. They set the direction and they are inspired to follow it. They try harder. They do more. And this can only happen when there is no interference and disruption from an egotistical leader who loves hearing his own voice. It seems like a counterintuitive concept for leadership, l know. But I can tell you it works. It's worked for me for more than ten years nowโฆโ
AI is collapsing the distance between ideas and working products, and that changes what leadership looks like.
To delve into this I used ChatGPT & Replit to spin-up a functioning physiotherapy tracker app in under an hour.
But the leadership insights matter more than the code.
- True innovation balances vision with velocity: test the pain points quickly, but never lose sight of the big idea.
- AI increasingly makes scope creep cheaper, so good leadership is needed to maintain focus.
- The future of tech leadership is turning AI from a tool into a teammate, and reshaping how we build together.
I shared my full walkthrough and leadership takeaways here: https://medium.com/@jbyrnephd/building-faster-leading-smarter-a-tech-leaders-experiment-with-ai-driven-app-development-518c47b765c2
A hands-on build with ChatGPT and Replit, and what it reveals about leading tech teams today.
What do you think, are we ready to treat AI as a teammate?
I tested ChatGPTโs new Agentic AI to find out: can GPT-5 access and optimise my calendar for me?
When OpenAI announced last month that ChatGPT could now act as an Agentic AI, I wanted to see what that actually feels like in practice. Wit
My key insight:
โข For individuals, Agentic AI will soon be the personal assistant we never had; becoming a commodity in everyday tools that supercharges productivity.
โข For enterprises, the real edge will come from tailoring such agents with proprietary data and workflows across pillars like Supply Chain, R&D, Marketing, and Central Functions. Those who combine high-quality data, cross-system workflows, and AI-skilled people, with appropriate governance, will unlock the ground-breaking opportunities.
I tested ChatGPTโs new Agentic AI to find out: can GPT-5 access and optimise my calendar for me?
When OpenAI announced last month that ChatGPT could now act as an Agentic AI, I wanted to see what that actually feels like in practice. Wit
My key insight:
โข For individuals, Agentic AI will soon be the personal assistant we never had; becoming a commodity in everyday tools that supercharges productivity.
โข For enterprises, the real edge will come from tailoring such agents with proprietary data and workflows across pillars like Supply Chain, R&D, Marketing, and Central Functions. Those who combine high-quality data, cross-system workflows, and AI-skilled people, with appropriate governance, will unlock the ground-breaking opportunities.
Shipping GenAI isn't just models, it's ๐ซ๐๐ฉ๐๐๐ญ๐๐๐ฅ๐ ๐ฉ๐ข๐ฉ๐๐ฅ๐ข๐ง๐๐ฌ with ๐ ๐จ๐ฏ๐๐ซ๐ง๐๐๐ฅ๐ ๐๐๐ญ๐ ๐ฉ๐๐ญ๐ก๐ฌ.
So ๐ง๐ณ๐ฐ๐ฎ ๐ต๐ถ๐ต๐ฐ๐ณ๐ช๐ข๐ญ ๐ต๐ฐ ๐ต๐ฆ๐ข๐ฎ ๐ฑ๐ญ๐ข๐บ๐ฃ๐ฐ๐ฐ๐ฌ: I've distilled Databricks' unstructured data pipeline for RAG into a ๐๐๐๐๐๐๐, ๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐๐๐๐๐๐ your teams can drop into a UC-governed project and start measuring.
Highlights:
- widgets and a _bootstrap setup (that software developers might hate but data scientists will appreciate).
- gotchas: path configs and UC table naming.
- levers to tune: chunk size/overlap, model swaps.
Leader's angle: ๐ฌ๐ญ๐๐ง๐๐๐ซ๐๐ข๐ฌ๐ ๐๐ฑ๐ฉ๐๐ซ๐ข๐ฆ๐๐ง๐ญ๐ฌ, reduce setup drag, and enable fast iteration and comparison of results across projects and teams.
This is a walkthrough of the Databricks tutorials for setting up an unstructured data pipeline for RAG (retrieval augmented generation)โฆ
