upvote

points

by lukaszkorecki23 hours ago |
comments
upvoteby bredren20 hours ago|
next
[-]
> 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:

   1. Resume unfinished work → "where did we leave off on that?"
   2. Recover the intent/scope → "what was the actual goal of this whole effort?"
   3. Verify it got done → "did we ever finish that, and which session proves it?"
   4. Recall a fix → "how did we fix this the last time it broke?"
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

reply
upvoteby f8ght14 hours ago|
parent|
[-]
the problem w/ this is that if people actually need their logs saved...99% is to finetune custom models on their codebase later...this is a whole pipe, u neeed to refine and prune the data into proper format for reinforcement learning i think...they will never us a mac app for this, they will use same agent and have custom scripts for this. for programming ur context is the codebase..not the logs, the bot searching through all chat log is wasted tokens when they can read context from codebase directly, and if not then they can search diff....there are edge case maybe like oops i accidentally deleted this code its only in chat logs.....you simply tell to go find log and extract data....so you cant make a product on this sorry.
reply
upvoteby vehemenz23 hours ago|
prev|
[-]
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.
reply
upvoteby lukaszkorecki22 hours ago|
parent|
[-]
I understand the point, but shouldn't the code be documented and well structured so that the intent is clear without looking at the discussion around changes?

I'm working on a legacy system right now - I'd commit several felonies just to have well documented code, I don't really care about all the conversations that the original team had to decide what they eventually did.

Maybe I'm just too old and don't get it.

reply
upvoteby anthonypasq22 hours ago|
parent|
[-]
surely you could imagine that being able to sit in on a meeting that was had when they were designing the system would be useful for you?

theres a lot of context and decision making that is useful but not documented in the code. The code tells you how the system works, not how its supposed to work.

reply
upvoteby godwinson__4-821 hours ago|
parent|
[-]
This is just the classic rehash of are comments in code an anti-pattern.

I tend to agree that at a certain point if you need to constantly think "gee, I wish I was in the meeting when they came up with this" the code you are looking at might just suck.

In such contexts it is also often the case that being in the meeting may not have helped. As they say, garbage in, garbage out.

reply
upvoteby anthonypasq1 hours ago|
parent|
next
[-]
no its not. there is nothing in the code that can tell you how the system was intended the work. The existence of a bug is by definition related to information that is not contained in the code. it is a mismatch between intent and what the code does.
reply
upvoteby bredren20 hours ago|
parent|
prev|
[-]
Sometimes it is useful to simply know something was brought up, but then someone had a sneezing fit and everyone lost track of the thread and the important edge case under discussion just fizzled.

A similar thing happens in agentic conversations, where a model may point out something but it is not recognized as important by the operator.

A few directives later and the model is being pushed another direction.

It can be very useful to have perfect recall of moments like these.

reply