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.
Zbuduj agenta, aby zrozumieć, jak działają te systemy. Większość ludzi mówi o nich, nie znając rzeczywistości. Nie powinieneś być jak większość.
Źródło: https://dev.to/mkautsar/i-built-my-own-ai-agent-heres-what-nobody-tells-you-3g31
Opcjonalna społeczność edukacyjna: https://t.me/GyaanSetuAi