[flagged]
As a founder, I can definitely feel this pain. So much company knowledge is just the thing on our laptops, and then we hope we can write accurate docs later. Actually we can't because our docs usually miss some…
[dead]
Cool. After reading your README, the "post-part" hook is the most interesting part for me. Chunk-level hooks make it easier to plug into things like rclone or other workflows. As you mentioned, the single…
The repo-native approach is pretty cool. Many agent systems still feel opaque because the operational context is buried within prompts and tools. Putting the company memory into Git makes the whole thing much more…
For me, the interesting part is the review loop after agents have written the code. For a native app that handles files and sanitized HTML, did you rely more on tests, manual use, or reading the generated Rust/JS…
It makes sense to do replay before prevention. For an agent, the challenge is often not recognizing that a bad action occurred, but reconstructing the complete decision context that led to it. I'm wondering how you…
For me, the interesting part here isn't GPT-2, it's the memory discipline. I feel like most inference runtimes slowly leak allocations everywhere as features pile up.
I think the git worktree per task idea makes more sense. The hard part with parallel agents seems to be reviewing and merging the mess
Make sense. A lot of these 10+ year old APIs end up surprisingly durable also because so many existing clients still depend on them. Thank you!
Do you think the DMG installation method will continue to be a long-term part of the macOS ecosystem, or is it more of a continuation of indie Mac culture?
So innovative! I've talked to your goose and I found this is really a great way to test whether I truly understand concept. I don't know how the goose thinks, maybe it would be even better if it allowed me to upload my…
I think your concept of this APP is meaningful for most people. I'm curious to know how you handle data calibration, especially when it comes to different regions, remote offers, and issues with uneven sample…
Awesome job! It really frees up my hands. As another reviewer mentioned, I’m so curious to know exactly what this robot can do when cleaning a room, how thoroughly it cleans, and who can monitor its status and how.
[flagged]
As a founder, I can definitely feel this pain. So much company knowledge is just the thing on our laptops, and then we hope we can write accurate docs later. Actually we can't because our docs usually miss some…
[dead]
[dead]
Cool. After reading your README, the "post-part" hook is the most interesting part for me. Chunk-level hooks make it easier to plug into things like rclone or other workflows. As you mentioned, the single…
[flagged]
[dead]
[dead]
The repo-native approach is pretty cool. Many agent systems still feel opaque because the operational context is buried within prompts and tools. Putting the company memory into Git makes the whole thing much more…
[flagged]
For me, the interesting part is the review loop after agents have written the code. For a native app that handles files and sanitized HTML, did you rely more on tests, manual use, or reading the generated Rust/JS…
It makes sense to do replay before prevention. For an agent, the challenge is often not recognizing that a bad action occurred, but reconstructing the complete decision context that led to it. I'm wondering how you…
[dead]
[dead]
[dead]
For me, the interesting part here isn't GPT-2, it's the memory discipline. I feel like most inference runtimes slowly leak allocations everywhere as features pile up.
I think the git worktree per task idea makes more sense. The hard part with parallel agents seems to be reviewing and merging the mess
[flagged]
Make sense. A lot of these 10+ year old APIs end up surprisingly durable also because so many existing clients still depend on them. Thank you!
[dead]
[dead]
Do you think the DMG installation method will continue to be a long-term part of the macOS ecosystem, or is it more of a continuation of indie Mac culture?
So innovative! I've talked to your goose and I found this is really a great way to test whether I truly understand concept. I don't know how the goose thinks, maybe it would be even better if it allowed me to upload my…
I think your concept of this APP is meaningful for most people. I'm curious to know how you handle data calibration, especially when it comes to different regions, remote offers, and issues with uneven sample…
Awesome job! It really frees up my hands. As another reviewer mentioned, I’m so curious to know exactly what this robot can do when cleaning a room, how thoroughly it cleans, and who can monitor its status and how.