Ideas, guides, and
production lessons.
What we learn building AI agents, RAG systems, and Claude integrations for real clients.
95K impressions: what happened when I showed a voice-controlled Mac agent on LinkedIn
A LinkedIn post showing Gemini Mac Pilot went viral. Why controlling your Mac by voice resonated with 95K people — and what it means for desktop AI.
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Scaling RAG to production: the 3-layer architecture that actually works
Why naive RAG breaks at scale and the 3-layer approach we use with clients: smart chunking, hybrid retrieval with re-ranking, and context assembly with citations.
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Ollama Laravel: from open-source package to 87K downloads
How building an open-source Laravel package for local AI created trust, community, and a consulting pipeline. Lessons from two years.
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How we design autonomous AI agents for business processes
Architecture, design patterns, and lessons learned building agents that operate 24/7 without human intervention.
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How we built a multi-agent system that manages itself
6 AI agents. 1 team. Each with a role, a budget, and a chain of command. Architecture and lessons learned building an autonomous AI team.
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Integrating the Claude API into enterprise applications
Tool use, structured outputs, streaming, and cost management: everything you need to take Claude to production.
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10 questions every team should answer before building AI systems. Avoid the most common mistakes we see in production projects.
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