Vibe coding is a good starting point, but it is not where serious AI-assisted development ends. The next step is agentic engineering: using AI coding agents inside a controlled engineering workflow, with context, tests, review and clear boundaries. Vibe coding often focuses on the generated output: Ask for feature -> get code -> run it -> ask for fixes Agentic engineering focuses on the system ar
AgentFlow — The Python Framework for Production AI Agents Stop rebuilding the same agent infrastructure. AgentFlow gives you auth, streaming, persistence, and a React frontend — out of the box. AgentFlow (10xscale-agentflow on PyPI) is an open-source Python framework for building and deploying multi-agent AI systems. Write your agent graph once. Run it locally. Ship it to production without rew
This post was created with AI assistance and reviewed for accuracy before publishing. Cursor can use project rules and documentation to steer behavior. Exact file names and mechanisms evolve; check Cursor documentation for the current layout (for example rules in .cursor or legacy .cursorrules patterns). Short, enforceable bullets beat long essays: stack versions, test commands, “no new dependenci
Vibe coding is one of those terms that sounds unserious until you notice how many people are actually doing it. The basic idea is simple: describe what you want, let an AI coding tool generate the implementation, run it, adjust the prompt, and keep going. It can feel magical. It can also go wrong very quickly. Vibe coding works best when the problem is visible and forgiving: small prototypes inter
Postmortem: How a LangGraph 0.1 Multi-Agent Bug Broke Our 2026 Customer Support Bot Executive Summary On October 12, 2026, our production customer support bot experienced a 4-hour partial outage caused by an unpatched edge case in LangGraph 0.1’s multi-agent orchestration layer. The bug triggered infinite agent handoff loops for 18% of inbound customer queries, leading to SLA breaches