The so-what of AI
I translate what's happening in AI intowhat your business should actually do about it.
I'm Vinil. I've spent 10+ years in data and now lead data and AI teams. Most AI posts stop at what launched. I write about the part they skip: so what do we do now?
- Leads data & AI teams
- Analytics lecturer
Fresh takeaways
All takeaways →Your AI evaluation might be biased against the model you're replacing
Property Finder found 96.8% of its eval labels came from its old model. After rebuilding ground truth, a different model won at 86% lower cost.
AI access is a different governance problem from web access
Cloudflare now separates Search, Training and Agent crawlers. The question shifts from 'can AI access this?' to 'why is it accessing it?'
Which parts of your role are moving from human-led to AI-led?
Anthropic says Claude leads 26% of its AI R&D work. The better question about AI and jobs isn't replacement, it's which tasks shift.
As code gets cheaper, verification gets more valuable
OpenAI's report on researchers using coding agents: even successful long tasks needed human steering. Knowing what good looks like is the skill.
Explore by topic
About
Why the so-what?
I've spent over a decade in data, from writing SQL as an analyst to leading data and AI teams, and I teach analytics on the side. Most AI news tells you what launched. Very little tells you what it means for the people doing the work.
So that's what I write about: one new thing at a time, and the practical takeaway for data teams and the businesses they support.
One useful takeaway, straight to your inbox
Join the newsletter for new takeaways and the tools worth your time. No hype.
Contact
Let's talk
Questions about a takeaway, an idea for a collaboration, or just want to say hi? Send me a message and I'll get back to you.
Or connect with me on LinkedIn