Turning AI capabilities into usable products, developer infrastructure, and production workflows.
GitHub · Blog · Email · Shanghai, China
- Context and retrieval systems for agentic coding
- Execution orchestration and observability for long-running AI workflows
- Evaluation platforms for comparing and optimizing agent performance
- Developer infrastructure that makes AI automation more reliable
- Shipping infrastructure for long-running coding agents
- Exploring control planes, memory systems, and workflow reliability
- Building reusable foundations for AI-native engineering tools
| Project | What it does |
|---|---|
| ContextAtlas | Context infrastructure for AI coding agents with hybrid retrieval, project memory, and retrieval observability. |
| meta-harness | Experimental platform for observing, evaluating, optimizing, and comparing agent or harness workflows. |
| ai-orchestration | Execution orchestrator for making AI automation progressively more observable and less human-dependent. |
| auto_freelancer | Automated bidding bot for freelancer workflows. |
- Context Engineering in Practice: ContextAtlas as Harness Engineering Infrastructure for AI Coding Agents - Notes on harness engineering, context engineering, and the design ideas behind ContextAtlas.
- The Upgrade Path of VibeCoding - A practical reflection on learning VibeCoding, improving context quality, and evolving toward more systematic AI development workflows.
Context Infrastructure -> retrieval, memory, project context, observability
Agent Orchestration -> execution control, workflow coordination, reliability
Evaluation Systems -> comparison loops, optimization, experiment platforms
Developer Tooling -> CLI workflows, automation systems, AI-native tooling
- Languages: Python, TypeScript, Java, SQL, with working familiarity in Go and Rust
- Frontend: React, Vue, Tailwind CSS
- Infra and Data: PostgreSQL, pgvector, MySQL, Redis, RabbitMQ, Docker, Nginx
- Observability and Ops: Prometheus, Grafana, Linux server and network basics
- AI Engineering: RAG, MCP, tool calling, multi-agent workflows, prompt engineering, context engineering
- GitHub: @codefromkarl
- Blog: codefromkarl.xyz
- Email: 1069123094@qq.com
- Location: Shanghai, China