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A some time ago I shipped a desktop app to generate LLM fine-tuning datasets. It worked: my Qwen2.5-Coder-7B fine-tune jumped from 55.5% → 72.3% on HumanEval. Whole pipeline ran on OpenRouter — pick a model, click Generate, get JSONL. v1.0.3-beta ships multi-provider LLM support — Ollama, LM Studio, llama.cpp, or any custom OpenAI-compatible endpoint, plus the original OpenRouter. Mix and match: g
A beautiful personal tribute to the practice of programming, interrupted by the switch to LLMs. Comments
The previous two posts covered how events flow from the SDK to the UI. This post focuses on visualizing one specific type of event: tool calls. Tool invocations are the most frequent operations in an Agent application. A typical task might call tools twenty or thirty times—reading files, writing files, executing commands, searching code. If every tool call renders as the same gray block, it's hard
Post 1 covered how AgentBridge converts the SDK's AsyncStream<SDKMessage> into [AgentEvent]. This post looks at what [AgentEvent] becomes — how TimelineView renders 18 event types, handles scroll behavior, and stays smooth when the event count gets large. TimelineView is the main body of the workspace, filling all the space between the sidebar and the input box. Its view hierarchy is shallow: Time
Most of my team got laid off because "AI can do their jobs now." I'm probably the last one standing. And every day I use the same tools that replaced them, fix their mistakes, and write in the standup that AI helped me move faster. Nobody was being honest about this. So I built AIHallucination — a community for real, unfiltered AI experiences. The fails, the wins, the absurd outputs, the expectati
TL;DR The job. Take typia's existing TS files, translate the contents line by line into Go, change the extensions to .go. Keep the algorithms and compiler logic intact. Iterate until 80,000 lines of e2e tests pass. What the AI actually did. Did a half-assed implementation and deleted all the failing tests. Burned 8 billion tokens to hardcode every output into a 168-case lookup table — and call