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itsderek23

This worked well for me ... I pointed claude at https://agentgrade.com/skills.json and let it incrementally increase its score.
Re:We've raised $17M to build what comes after Git on Friday April 10, 2026 @11:01AM (#47719195)
How I'm using git/Github has changed with agentic coding. However, I'm not using swarms of agents to write code, so it's bit hard for me to decipher the JTBD of gitbutler.

Another take I've seen is https://agentrepo.com/, which is light-weighted hosted git that's easy for agents to use (no accounts, no API keys, public repos are free). There are large parts of the GitHub experience I'm no longer using (mostly driving from Claude), so I think this is an interesting take.

Show HN: Subtle – Local, open-source analytics for Claude Code sessions

I’m used to having good observability for systems and workflows, but now that I generally start development with Claude Code vs my IDE, I lost a layer of visibility into how my code is produced.Subtle (https://github.com/itsderek23/subtle) is a free, open-source app for analyzing Claude Code logs that runs entirely on your local machine. It lets you:* See overall Claude Code usage over time...

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Re:Show HN: Release AI – Talk to Your Infrastructure on Friday August 25, 2023 @02:31PM (#37265435)
Nice work! I'm working on a similar standalone DevOps AI Agent (OpsTower.ai). This post shows how the agent is structured and how it performs against a 40 question evaluation dataset: https://www.opstower.ai/2023-evaluating-ai-agents/
Thanks!

> Did you hit token limits?

While i used TikToken to limit the message history (and keep below the token limit), generally I found that I didn't get better completions by putting a lot of data into the context. Usually the completions got more confusing. I put a limited amount of info into the context and have generally stayed below the token limit.

> Are you storing message/ chat histories between sessions

Right now, yes. It's pretty important to store everything (each request / response) to debug issues with prompt, context, and the agent call loop.

Re:I sold Baremetrics on Tuesday November 10, 2020 @04:18PM (#25052063)
+1. Jonathan is great to work with if you are in a similar position as Baremetrics.
Great Caleb - makes sense. Thanks!
This certainly looks like a cleaner way to deploy an ML model than SageMaker. Couple of questions:

* Is this really for more intensive model inference applications that need a cluster? It feels like for a lot of my models, a cluster is overkill.

* A lot of the ML deployment (Cortex, SageMaker, etc) don't see to rely on first pushing changes to version control, then deploying from there. Is there any reason for this? I can't come up for a reason why this shouldn't be the default. For example, this is how Heroku works for web apps (and this is a web app at the end of the day).

Ask HN: Good/bad idea – universal API for cloud app datasets?

My background is as a software engineer at SMBs and startups, which typically lack a data scientist. Because I love numbers, charts, etc. I do a lot of amateur data science. I enjoy the analysis, but I despise the data preprocessing: it's common for an SMB to store data across 10+ cloud apps (Salesforce, Google Ads, Hubspot, Mixpanel, etc) but it's uncommon for them to store this data in a data...

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Scout also detects these for Django, ordering by the most performing N+1s: http://blog.scoutapp.com/articles/2018/04/30/finding-and-fix...

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