𝗜 𝗕𝘂𝗶𝗹𝘁 𝗠𝘆 𝗢𝘄𝗻 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁. 𝗛𝗲𝗿𝗲 𝗶𝘀 𝗪𝗵𝗮𝘁 𝗡𝗼𝗯𝗼𝗱𝘆 𝗧𝗲𝗹𝗹𝘀 𝗬𝗼𝘂.
Most people talk about AI agents like magic. I built one. It is not magic. It is plumbing.
Six months ago, I started building AkiraAI. It is a personal AI agent that runs 24/7 on my own server. It is not a chatbot. It is an agent that reads my emails, publishes articles, manages my calendar, and monitors my server.
Building it taught me things a tutorial cannot.
The Gap in Tech Everyone talks about agentic AI on LinkedIn and YouTube. Almost nobody builds one from scratch and runs it in production. I fell into that gap.
Tools Make the Agent When I first connected my agent to Claude, it was useless. It could answer questions, but it could not act.
An agent becomes real when you give it tools. I added web search, Gmail access, Google Drive, and shell execution. Tools are the difference between a parrot and an assistant.
The Memory Problem I thought memory would be simple. I was wrong. If you provide too much context, you hit token limits. If you provide too little, the agent forgets everything.
I built a three-layer system:
- Short-term: The last few messages in a session.
- Long-term: A file with facts about my projects and preferences.
- Lessons learned: A log of mistakes so the agent does not repeat them.
Production is Hard Running an agent on a laptop is easy. Running it on a server is difficult. I faced real problems:
- RAM spikes during web tasks.
- Timezone errors that broke reminders.
- Crashed processes and API rate limits.
Great agents are not built with perfect prompts. They are built with reliable software engineering. They need versioning, monitoring, and fallbacks.
Define Boundaries I wanted total autonomy at first. Then the agent almost restarted a critical service. I learned that building an autonomous agent means deciding when it should NOT act. Defining boundaries is good engineering.
The Result One morning, I woke up to a Telegram message from my agent. It had already flagged my emails, published my articles, and checked my server RAM. It worked while I slept.
My advice for you:
- Start small. Pick one task and do it well.
- Add tools one at a time.
- Do not skip the boring parts like error logging and monitoring.
- Run it in production as early as possible.
Costruisci un agente per capire come funzionano questi sistemi. La maggior parte delle persone ne parla senza conoscerne la realtà. Tu non dovresti essere come la maggior parte delle persone.
Fonte: https://dev.to/mkautsar/i-built-my-own-ai-agent-heres-what-nobody-tells-you-3g31
Community di apprendimento opzionale: https://t.me/GyaanSetuAi