stillsut

10 ms·

1.
by stillsut 11mo ago
Exactly what I was looking for, thanks. I've been doing something similiar: aider+gpt-5, claude-code+sonnet, gemini-cli+2.5-pro. I want to coder-cli next. A main problem with this approach is summarizing the different approaches before
2.
by stillsut 11mo ago
I've actually written my own a homebrew framework like this which is a.) cli-coder agnostic and b.) leans heavily on git worktrees [0]. The secret weapon to this approach is asking for 2-4 solutions to your prompt running in parallel.
3.
by stillsut 1y ago
I think the easiest explanation is to look at the table here: https://github.com/sutt/innocuous?tab=readme-ov-file#how-it-... Watch how the "Cumulative encoding" row grows each iteration (that's where th
4.
by stillsut 1y ago
I've been building something like this, a markdown that tracks your prompts, and the code generated. https://github.com/sutt/innocuous/blob/master/docs/dev-summa... Check it out, I'd be cu
5.
by stillsut 1y ago
Encoding / decoding hidden messages in LLM output. https://github.com/sutt/innocuous The traditional use-case is steganography ("hidden writing"). But I see more potential applications than just for sp
6.
by stillsut 1y ago
I'm also working on a library to steer the sampling step of LLM's but more for steganographic / arbitrary data encoding purposes. Should work with any llama.cpp compatible model: https://github.com/sutt/i
7.
by stillsut 1y ago
You can also earn zaps for pull requests working on Nostr clients. We've been hosting some bounties like this one here: https://app.lightningbounties.com/issue/615dc5f7-ed91-4ecd-8...
8.
by stillsut 1y ago
I've got some receipts for what I think is good vibe coding... I save every prompt and associated ai-generated diff in a markdown file for a steganography package I'm working on. Check out this document: https://github.
9.
by stillsut 1y ago
I'm actually working on something similar to this where you can encode information into the outputs of LLM's via steganography: https://github.com/sutt/innocuous Since I'm really looking to sample the on
10.
by stillsut 1y ago
I think the "magic" that we've found a common toolset of methods - embeddings and layers of neural networks - that seem to reveal useful patterns and relationships from a vast array of corpus of unstructured analog sensors (p
11.
by stillsut 1y ago
"Unstructured data learners and generators" is probably the most salient distinction for how current system compare to previous "AI systems" examples (NLP, if-statements) that OP mentioned.
12.
by stillsut 1y ago
Makes sense: M-chips, Falcon-9, GPT's are product subsets or the incumbent's traditional product capabilities.
13.
by stillsut 1y ago
At a meta-level, I wonder if there's this un-talked about advantage of poaching ambitious talent out of an established incumbent to work a new product line in a new organization, in this case Apple Silicon disrupting Intel/AMD. An
14.
by stillsut 1y ago
Got your shovelware right here...with receipts. Background: I'm building a python package side project which allows you to encode/decode messages into LLM output. Receipts: the tool I'm using creates a markdown that displays
15.
by stillsut 1y ago
Not an expert but my chats with ChatGPT led me to believe async + FastAPI can give you 40x throughput for request handling over non-async code. The essential idea was I could be processing ~100 requests per vCPU in the async event loop whil
16.
by stillsut 1y ago
Hey I made an open source version of this last week (albeit for different purposes). Check it out at: https://github.com/sutt/innocuous There's lot of room for contributions here, and I think "fingerprinting
17.
by stillsut 1y ago
> we should always consider asking the LLM the same question more than once, perhaps with some variation in the wording. Then we can compare answers, Yup, this matches my recommended workflow exactly. Why waste time trying to turn an ini
18.
by stillsut 1y ago
Not OP but I know it can be difficult to really difficult to measure or communicate this to people who aren't familiar with the codebase or the problem being solved. Other than just dumping 10M tokens of chats into a gist and say read
19.
by stillsut 1y ago
I'm rolling my own like this [0]: .agdocs/ ├── specs/ # Task specification files ├── conf/ # Configuration files ├── guides/ # Development guides for agents └── swap/ # Temp
20.
by stillsut 1y ago
Yeah, I've been able to stack ~200 AI-generated commits on top of each other. Over 95% of the code is now AI generated. You can see each prompt and each commit that was generated here: https://github.com/sutt/agro&
21.
by stillsut 1y ago
Just added a fork of aider that does do agentic commands: https://github.com/sutt/agent-aider In testing I've found it to be underwhelming at being an agent compared to claude code, wrote up some case-studies on
22.
Gpt5 400: Your organization must be verified to stream this model(old.reddit.com)
2 points by stillsut 1y ago|1 comments
23.
by stillsut 1y ago
I've been finding adding context for your external packages is really important when the package is relatively new and or has breaking changes since the model training cut-off date. Two that stick out this week are google's gena
24.
by stillsut 1y ago
Yeah I suspect some of these providers will become Microsoft in the '90s type bully holdouts on implementing the emerging conventions. But ultimately with CLI interface you have workarounds to all the major providers read in your syste
25.
by stillsut 1y ago
Last year, I was actually working on a bounty platform for Github PR's. The low quality human-authored PR's that came in (due to the incentive we offered) combined with the fact that a draft PR could be made for pennies with AI ma
26.
by stillsut 1y ago
I think the Github-PR model for agent code suggestions is the path of least resistance for getting adoption from today's developers working in an existing codebase. It makes sense: these developers are already used to the idea and the
27.
AI for Coding Is Inevitable(ashtom.github.io)
5 points by stillsut 1y ago|1 comments
28.
by stillsut 1y ago
This has repo has a great prebuilt llm docs sections. This seems like a killer feature for clients who want to roll their own customizations. https://github.com/crbnos/carbon/blob/main/CLAUDE.md https:&
29.
by stillsut 1y ago
Currently working on a python package: agro. It helps devs build parallel agents from the cli. (think claude code, gemini, aider) And simplifies the git workflow for testing and accepting the best solution. Check it out: https://
30.
by stillsut 1y ago
Working on a script to let people launch claude code, gemini cli, and aider agents on the same task and compare results. Handles all the git worktree stuff for you so they can run in parallel. Kind of like OpenRouter but for CLI agents. Wha

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