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Sichere ProgrammierungDurable AI Agents: Workflow Strategies for Resilient Systems(29.09.2026 um 07:29 Uhr)
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Sichere ProgrammierungWhat If Your AI Agent Never Had to Leave the Browser?(29.09.2026 um 07:30 Uhr)
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Sichere Programmierung"Why My Agent Needed Hindsight Beyond Chat History ?"(29.09.2026 um 07:35 Uhr)
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Day 17 of 60: I Deployed My First Production AI API and It's Live 24/7 (This Changes Everything)

Today everything became real. Every system I've built over the past 16 days lived only on my local machine. The moment I closed my laptop it went offline. n8n Cloud couldn't reach it without ngrok running. No client could access it. I…

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Today everything became real.



Every system I've built over the past 16 days lived only on my local machine. The moment I closed my laptop it went offline. n8n Cloud couldn't reach it without ngrok running. No client could access it. I couldn't share it with anyone without being physically present.



Today I fixed that. My AI Agent API is live. 24/7. No laptop required.






## The Gap This Closes



There is a clear line between a developer project and a professional product.



A portfolio of systems that only run locally is a collection of demos. A deployed API that runs 24/7 from a cloud server is a product; something you can hand to a client, link to from your LinkedIn, or build a business on.



Today I crossed that line.






## What Got Deployed



A production-ready FastAPI server combining the capabilities from the last three projects into one unified AI agent API:





  • Document Q&A endpoint: ask questions against any document


  • Research endpoint: multi-agent research and report generation


  • Data analysis endpoint: CSV analysis with AI-generated insights



Deployed to Render's free cloud hosting. Permanently accessible at a real URL. n8n Cloud workflows can now call it directly. Clients can access it. It's in my portfolio.






## What I Learned



requirements.txt: the dependency file that tells cloud platforms what to install. Standard for every Python deployment.



Environment variables in production: storing API keys securely on Render so they are never in code or GitHub. This is non-negotiable in production.



Production start command: the uvicorn command Render uses to start the server. Different from how you run it locally.



Health check endpoint: the GET / endpoint that tells Render your service is alive.



Auto-deploy from GitHub: every time I push new code Render redeploys automatically. Continuous deployment from day one.






*🌐 Live API → https://ai-agent-api-w7uh.onrender.com

🔗 GitHub → https://github.com/mbuguacessy-glitch

*


43 more to go!.






python #fastapi #deployment #render #claudeapi #automation #learninpublic #buildinpublic #100DaysOfCode

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