Just canceled my @cursor_ai subscription after a year of usage.
It’s clear that if you don’t fully own your software and AI stack you will be subject to companies disturbing your workflow
Erdal
2,030 posts
Erdal
@ErdalToprak
AI Engineer | 🇺🇸🇫🇷🇹🇷
- Replying to @abacajOwning the hardware is great! If anyone is interested in an homelab guide for your next AI project, I wrote a post a few months ago (featuring proxmox, gpu passthrough and initial software setup)
- Replying to @steipeteI’ve been doing it since the beginning all I need for any repo are - a file tree - a comprehensive text + diagrams readme - a contributing file - a changelog file And finally the issue / feature to build Each commit is a changelog block
- Replying to @ErdalToprakIf you’re wondering how to get started with a local AI setup, I wrote an article a few years ago! Basically proxmox + lxc / vm Inference with vllm
- Replying to @sdrznIn my current org Cline is one of the few approved extensions thanks for the amazing work Saoud!
- vLLM is the only way for personal projects and large scale production environments, the number of features and community involvement is incredibleggerganov has it rough. imagine writing the backend for your llm inference in C++... then some rando group wraps it with a non-compatible API, calls it "ollama", which gets a majority of the outside attention and support
- Replying to @forgebitzThis is where good system design, docs, file trees, function signatures, tests make the difference between vibe coded slop and production at scale
- Replying to @an21m> Checks the Snap docs for API to post content > Nothing
- In my AI team we released today our first batch of agents using @AgnoAgi! (cc @ashpreetbedi) The framework is super well thought out and integrates very well with our @vllm_project cluster
- Replying to @tekniumOpenAI has les restrictions on medical examination usages so that’s something
- Replying to @ErdalToprakAlso wrote a script to automate AI environment setup on a new machineI created a script that automates the setup of a fresh Ubuntu 24.04 server for AI/ML development work. It handles the complete installation and configuration of Docker, ZSH, Python (via pyenv), Node (via n), NVIDIA drivers and the NVIDIA Container Toolkit, basically everything
00:00 - Replying to @vltansky and @cursor_aiRunning models on my own GPU, looking to buy more and on the software side leaning more into vscode / zed + custom ai cli with tools that I made a while back (like Claude code) Building / Fixing according to architecture designs, requirements and issues
