slavakurilyak
Joined 9 years ago
Karma
19
Submissions
9
Member since
Apr 30
Recent submissions
Comment · 1 year ago
This looks well-built, but have you considered using Jujutsu (jj) instead? It elegantly solves the snapshot/checkpoint problem without needing MCP servers or a separate app.
With jj, every file change is automatically captured (no manual commits needed), and you can create lightweight "sandbox" revisions for each Claude Code task. When things go wrong, `jj undo` instantly reverts to any previous state. The operation log tracks everything, making it virtually impossible to lose work.
The workflow becomes: let Claude Code generate messy experimental code → use `jj squash`/`jj split` to shape clean commits afterward. You get automatic checkpointing plus powerful history manipulation in one tool.
I've been using jj with Claude Code for months and it's transformed how I work with coding agents - no fear of breaking things because everything is instantly reversible. The MCP integration seems like added complexity when jj's native capabilities already handle the core problem.
For anyone interested in the jj + agent workflow, read my post: https://slavakurilyak.com/posts/use-jujutsu-not-git
That said, respect for shipping something that solves a real pain point! The UI looks clean and the diff viewer is nice.
Comment · 1 year ago
Gemini CLI pricing:
1. Gemini Code Assist (GCA) for Individuals: FREE for 1,000 model requests/day
2. GCA Standard: $22.80/month for 1,500 model requests/day (1.5x more than FREE)
3. GCA Enterprise: $54.00/month for 2,000 model requests/day (2X more than FREE)
Source: https://codeassist.google
Comment · 9 years ago
TL;DR
It's possible to generate new colors using Multi-layer Recurrent Neural Network (RNN, LSTM, and GRU) based on Sherwin-Williams paint colors along with their RGB values (RGB = red, green, and blue color values)
Comment · 9 years ago
> In fact, according to a new report by the London venture capital firm Atomico, European startups are now taking the lead in artificial intelligence, building new tech hubs, and drawing investment from traditional industrial stalwarts.
That is incorrect. According to Atomico's 2016 report, Europe is behind US in number of artificial intelligence (machine learning and deep learning) startups (1252 vs 950 startups formed from 2014-2016), and percentage of startups funded (53% vs 43% startups funded from 2011-2016).
Comment · 9 years ago
> Emulation of human thinking in other media will be constrained by cost.
Technology assets generally decline in price as more efficient means of production and distribution become available (i.e. cloud) and the cost of technology components becomes more commoditized.
> I will extend that further to claim that the only way to get a very human-like thought process is to run the computation on very human-like wet tissue.
I think wetware (or human-like wet tissue) needs to be created first, before any judgement can be made about it’s costs.
Comment · 9 years ago
TL;DR
It's possible to predict the location and quantity of 911 calls based on call data (accident time, description of emergency calls and geolocation data) using Regression analysis
[ my public key: https://keybase.io/slavakurilyak; my proof: https://keybase.io/slavakurilyak/sigs/1QlUs6TGGhvyOmm5AmKtn-mOAe8LoIOQocGgVfA6Wog ]