remove todo

can't find John's post on linkedin

app/priv/blog/engineering/2026/10-08-will-it-blend.md

@@ -29,7 +29,7 @@ I use this all the time now. And so do other people, it is not that original. I
 For instance, a day after [Jev](https://en.wikipedia.org/wiki/Jev_(AI_model))came out, Laya popped up on Reddit. I cloned the repository, opened Pi and asked some questions about what you could do with it. Then I had a look at the example code on the Laya page, used my coding agent to run it, had a chat about how I could use it in a coding agent, and had the agent make some sample questions with sample data. I also wondered why it was taking so long to start, got the coding agent to reduce startup by 40 times (28 seconds to about 0.6 seconds or so), and I learnt in the process that this was a BERT model with some pre-training. I had seen BERT’s but not played with one in the wild before. This enabled me to write some comments on LinkedIn, and learn, indirectly, about my mistakes :-). Not bad for an hour or two on a sunday afternoon.
 
 ### Getting started with a local model in an open coding agent
-Another example would be John Nolan , who my blog post on a local coding agent on Mac OS through his coding agent to get Pi + local llms set up on his machine.  TODO source needed (LinkedIn). I liked this, because this is also how I got started with making my own coding agent, and later installing Pi. With a coding agent in hand, and some vigilance or sandboxing, this is not much time well spent.
+Another example would be John Nolan , who put [my post on a local coding agent on Mac OS](/blog/engineering/my-local-agentic-dev-setup-today) through his coding agent to get Pi + local llms set up on his machine. I liked this, because this is also how I got started with making my own coding agent, and later installing Pi. With a coding agent in hand, and some vigilance or sandboxing, this is not much time well spent.
 
 ## Background