AuthorAgus L. Setiawan

AI agent operator building autonomous workflows and rapid product experiments. Based in Stockholm, building global ventures while engaging with the Nordic startup community and the ecosystem around KTH Innovation. Focused on turning ideas into working software using AI, automation, and fast iteration.

How to Build a Local Multi-Agent Workforce with Eigent

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Badge I ran into this project while evaluating desktop-first agent platforms that coordinate many workers in parallel. Eigent is a Cowork style desktop app that lets you build and run a local multi-agent workforce, with MCP integration and tools for orchestration, privacy, and enterprise features. Unlike Hermes Agent which focuses on a single persistent terminal assistant, Eigent manages teams of...

Contains Studio Agents, Ready-Made AI Templates

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Badge I ran into this repo while collecting agent templates and practical examples for rapid development. Contains Studio Agents is a curated collection of specialized AI subagent templates you can drop into your agent stack, they cover many common developer and product workflows, and they are ready to invoke when expertise is needed. contains-studio-agents-repo.jpg Repository snapshot and...

Chrome DevTools MCP, Live Browser Inspection for Agents

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I ran into this while tracking agent tooling that gives coding assistants real runtime visibility. Chrome DevTools MCP is an MCP server that exposes Chrome DevTools to AI agents, letting them inspect a live browser, test generated code, debug network problems, and analyze performance traces in real time. It brings reliable, empirical verification to the agent loop, so fixes can be validated...

Awesome LLM Apps, Curated Open-Source LLM Projects

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I ran into this curated collection while following agentic experiments. The repo pulls together practical LLM apps across RAG, AI Agents, Multi-agent Teams, MCP, Voice Agents, and more. What caught my attention is a recent claim that a China model beat Claude Sonnet 4.5 and GPT-5.2 on the OpenHands agentic coding benchmark, and many linked projects point to open-weights models. That makes the...

How to Build RAG Apps with BRAG LangChain Notebooks

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BRAG LangChain provides five notebooks that walk from basic RAG setups to advanced multi-query, routing, indexing, and reranking techniques. This compact, hands-on guide helps developers learn and build real RAG apps without hunting through scattered examples. For a broader view of how retrieval systems fit into agentic workflows, see how to use Chroma Context-1 for local agentic search. Notebook...

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