Is nirvacana.com Still Updated? Topics and Posting Cadence

Updated

nirvacana.com is still updated, but slowly. The blog "Recent Thoughts – Thinking in Systems" shows posts spanning from 2013 to 2026, with long-form essays on AI, data science, and systems thinking rather than frequent news-style updates. If you want a steady stream of commentary, this is not that kind of site; if you want occasional deep pieces worth returning for, it fits.

What the site covers

The homepage lists three visible posts, and together they sketch the blog's range:

Post Date shown Topic
The AI Agentic Systems Ladder January 6, 2026 AI agents, framed through the game Snakes & Ladders / Moksha Patam
Demystifying Artificial Intelligence December 27, 2017 Explaining AI from different dimensions
Becoming a Data Scientist – Curriculum via Metromap July 8, 2013 A learning path for data science

The through-line is systems thinking applied to technical subjects — AI, data science careers, and how to reason about complex systems. The AI agent post is the clearest example: it takes an ancient Indian board game (ladders as virtues, snakes as vices) and uses it as a metaphor for progress and setbacks in agentic AI systems.

How often it updates

The dates above are the main signal: 2013, 2017, and 2026. That is a very low cadence — years between posts, not weeks. The site reads as a personal essay archive rather than a publication with a schedule.

Two caveats on reading too much into this:

  • The homepage shows only "Recent Thoughts," so older posts may exist beyond what is listed.
  • A 2026 date on the newest post means the blog has not been abandoned, even if gaps are long.

Who should follow it

Worth subscribing or bookmarking if:

  • You like long-form, metaphor-driven explanations of AI and systems concepts.
  • You are building a data science learning path and want a curriculum-style guide (the 2013 post is explicitly framed as one, and the author notes it drew strong reader feedback over the years).
  • You prefer a small number of substantial posts over a high-volume feed.

Probably not worth a regular visit if:

  • You need current AI news, releases, or frequent analysis.
  • You want a predictable publishing schedule you can plan around.

Practical takeaway

Treat nirvacana.com as an occasional-read archive. Check back every few months rather than weekly, or subscribe if the site offers a feed, so new long-form posts reach you without repeated manual visits. The value is in the individual essays — particularly the AI agentic systems piece and the data science curriculum — not in update frequency.