I don't quite get it - it reminds me of using Slack as the decision making places, sure it works for hashing out the details, but it's not great for being the decision record store. I'm not sure what is the value of preserving hundreds of lines of conversations about how code came to be if the code keeps changing? What happens in 5 years? Do I have to read the whole transcript just to understand what's going on? AI will summarize it for me?
This feels like engaging with a prog lang community for the first time, and answer to a basic question is "this has been covered before, read the IRC chat history"
It's not like Pull Requests are perfect, and with discipline they do the job well - but this looks like a step in the wrong direction.
If one builds something with an agent, the process itself is largely opaque. Preserving the transcript shows the reasoning of the agent and the decision process of the builder. This way everyone's on the same page instead of re-prompting same CLAUDE.md but with different results, and/or going through similar work over and over again.
> Do I have to read the whole transcript just to understand what's going on?
No but you will want all of the transcripts anyway.
> AI will summarize it for me?
Not exactly. You will have some question later that you would never have entertained during your thousands of conversations about code.
You’ll ask your AI something fairly abstract but it will be deep in the context of some other idea.
And the AI will find among all your conversations those turns that are relevant to solving your problem or explaining why.
I know this is the case because I’ve built this and use it every day.
Here are some examples:
I shared these and more in my post in the August “what are you working on?” thread. [0]You would be amazed how good the agent can be at assembling queries against a corpus of transcripts and assembling the results.
My product is called Contextify: https://contextify.sh
[0] https://news.ycombinator.com/item?id=49236853