GPT, or Generative Pre-trained Transformer, is an autoregressive language model that uses deep learning to produce human-like texts. GPT-3 is the third generation of the GPT series launched by OpenAI, ...
The problem: I kept making "mega-commits" with unrelated changes because I get in a flow state and then end up with a huge number of changes I forgot to commit.The solution: I built a tool that analyzes your staged git changes, clusters them by semantic similarity using embeddings + hierarchical clustering, and creates separate commits for each cluster.How it works:- Parses diffs into semantic chunks using tree-sitter- Generates embeddings (OpenAI text-embedding-3-small)- Clusters with
Uses an LLM to identify where tables actually start/end in Excel/CSV files, then extracts clean, typed data.<p>Handles all the messy formatting (currency, percentages, different number formats) and streams efficiently for large files.<p>Works with OpenAI, DeepSeek, or any compatible API.
Raising capital pre-revenue is pretty difficult for most people. I realize that everyone's not having the same difficulties.<p>I'm opening up a feedback loop to get a better insight on the experiences founders are having.
I’ve been dogfooding a small writing helper I built called Rephrazo, and I thought it might be useful to share some implementation details and mistakes so far.The idea is simple: - highlight text where you’re writing - press a hotkey - get an AI paraphrase in a small popup - insert it back with one click The goal is to remove the “copy - open AI tool - paste - rewrite - paste back” loop for small edits.This post is about how I wired it up, what worked technically, and what didn’t.Constra
LLMs generate a lot of Markdown—Claude exports, ChatGPT conversation dumps, research notes, wiki-style docs.I found myself constantly opening these in VS Code or converting them just to read comfortably.So I built mdfocus: a zero-config local reader that you point at any folder and start reading instantly (npx mdfocus ~/notes).It's not a static site generator or a publishing tool—just a clean, focused way to consume Markdown locally.Includes live-reload, auto-generated table of content
I put together a small side project that lets me use AI to work with my own Telegram account — searching chats, summarizing long threads, and sending messages without opening the app.It’s not a product or a framework. I mostly built it because I’m in a lot of noisy Telegram groups and wanted a better way to answer questions like “what did we decide last week?” or “did anyone mention X recently?”The setup uses a Model Context Protocol (MCP) server that connects Telegram to AI clients like Claude
Just a month after introducing GPT 5.1, OpenAI introduced GPT-5.2, the next-generation model that will power its popular chatbot. GPT-5.2 is OpenAI's "most capable model series yet for professional knowledge work". GPT-5.2 is designed to help people get more done quicker. It's better at creating spreadsheets, building presentations, writing code, perceiving images, understanding long context, using tools, and completing multi-step projects.
GPT-5.2 is now live for all ChatGPT users with improved coding, writing and image interpretation, with Kurt Knutsson offering ...
Despite OpenAI's bold claims of widespread improvements, GPT-5.2 feels largely the same as the model it replaces. Google, ...
On Wednesday, Anthropic released Claude Haiku 4.5, the newest version of its smallest model, billed as offering similar performance to Sonnet 4 “at one-third the cost and more than twice the speed,” ...
Anthropic's Skills are reusable bundles of instructions, scripts and resources that allow AI to perform specialized tasks ...
I have ADHD tendencies. I leave things half-done, go home with my work keys still in my pocket, and as soon as I start something else I completely forget the task I was doing before. Reminders don’t work — I just don’t look at them. Checklists don’t work either — I forget to check them in the first place. So I built PocketCheck. It periodically asks, “Anything to put in your pocket?” It’s a pocket that stands in for my working memory. I forget what I put in my actual pockets all the time, but th
Google Bard expands its capabilities with YouTube video understanding. I put this new feature to the test – does it live up to expectations? Google introduces an enhancement to Bard's AI, enabling it ...
Hey,A few weeks ago I randomly decided to build a seamless pattern engine for Swift/SwiftUI projects. I called it Tessera (GitHub link). It’s an open-source framework that lets you generate endlessly repeatable, seam-free patterns from pretty much anything you can build in code: shapes, SF Symbols, emojis, text, custom icons, etc.While working on it, I also built a demo app so developers could see how to use the framework. However, that demo turned out to be so much fun to play with that I
Simple proxy service that uses your oauth credentials from Claude Code which you can pop into Cursor and use.<p>Falls back to your API key if you have one set.<p>I spent $XXXX on Cursor on Anthropic API Credits, but was told that the Claude Code $200 pmo plan was much more affordable. It's a great arbitrage, so I made this hack so I could save money on this.<p>Note: Cursor OpenAI baseurl overriding is <i>extremely</i> buggy right now so I don't recommend trying this for now.
Single-model inference is a single point of failure. I got sick of Chatgpt hallucinating fake citations and having to manually check them in a different tab with Claude.So I built CouncilThe Difference: Shared Context Most "multi-bot" UIs are just parallel silos. Council uses a sequential backend stream where every response is injected into the context of the next model.If GPT cites a fake study, Claude sees it and calls it out.If Gemini misses a logic gap, Grok roasts it.Adversarial L
I built an extension that gives developers cheaper access to AI models in a Kilo Code fork.Free tier: 200 requests/day to open source models (DeepSeek, Qwen, Minimax) Paid tier ($20/month): $45 in credits for Claude/GPT-5/Gemini-3 + 1000 daily open source requestsWorks in VS Code, Cursor, and Windsurf. Your data isn't used for training.Just launched today, still rough but functional. Would appreciate feedback.agentica.genlabs.dev Download extension from: https:/
My background is primarily software (Python, AI/ML, large-scale data). This is my first serious hardware-heavy product.I’m working on a company concept that depends on embedded IMUs, and I’m trying to front-load learning so I don’t lock myself into poor architectural, software or component decisions early on, especially those pitfalls that someone with more knowledge/expertise would know how to avoid.I understand “learning by doing” is essential, but I suspect there are canonical pitfa
Universal SDK for working with multiple LLM providers (OpenAI, Anthropic, Gemini, etc.). Built-in caching can reduce API costs by 90%+. 15K+ PyPI downloads.<p>pip install llmswap
