Leadcode: Multi-Client Isolation for AI Coding Assistants
Freelance developers juggling multiple clients face a recurring headache: account contamination. You commit code in Client A's project using Client B's GitHub token — it happens more often than anyone admits. Leadcode solves this.
Each client gets an isolated workspace with its own GitHub, Claude Code, and API credentials. Switch projects and the right accounts load automatically. The isolation is built on environment variables (CLAUDE_CONFIG_DIR, GH_CONFIG_DIR), keeping personal and client work physically separate.
macOS only for now. Pro subscription includes a 14-day free trial. If you're doing AI-assisted development for two or three clients simultaneously, this is worth a look.
Who it's for
Freelance developers serving multiple clients, small team leads, anyone who needs to handle different organizations' code on the same machine.
IQ Routing: Cheapest Model That Holds Quality
Most LLM calls in production don't need the strongest model. A customer service bot answering "What's your refund policy?" with GPT-4o is pure waste. IQ Routing automatically routes each request to the cheapest model that meets the quality bar for that specific task.
It's an API gateway that sits in front of your OpenAI or Anthropic SDK — swap the base URL and you're in. The routing logic assesses prompt complexity and task type to decide which model to use. The company reports 40–80% cost savings on their own traffic.
Works for chatbots, RAG pipelines, and agent call chains. Kimi and GLM support is on the roadmap. Free tier requires a card but doesn't charge — good for running a demo.
Who it's for
Teams with bloated LLM API bills who don't want to maintain routing rules manually, developers building multi-model pipelines, cost-conscious AI startups.
AI Engineer Notebooks: Hands-On AI Engineering Without Frameworks
Most AI tutorials rely on LangChain or LlamaIndex. You learn the framework, not the fundamentals — change the scenario and you're lost. AI Engineer Notebooks takes the opposite approach: pure code, no frameworks, direct API calls.
125 GitHub Stars and growing. Covers the full AI engineer skill set: model APIs, structured output, tool calling, RAG, evals, agent loops from scratch, MCP protocol, LoRA fine-tuning, prompt injection defense. All Jupyter Notebooks running on Google Colab with the free Groq API — zero cost to start.
Each notebook is a standalone project, not a "Hello World" demo. Built for developers who want to understand LLM engineering principles, not just call framework APIs.
Who it's for
Developers moving from AI application layer to engineering layer, tech leads training new team members, pragmatic engineers who distrust framework black boxes.
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