Most AI agents aren't really agents.
They're API wrappers with a system prompt.
The hard part is building the loop around the model: context, tools, memory, retries and verification.
AI: โI can write your entire application.โ
Me: โCan you fix this one bug?โ
AI: โSure.โ
deletes production database
Me: โI should've just learned CSS.โ
Me: โIโll just make one small change.โ
6 hours later:
fixed 3 bugs
created 2 new bugs
learned about a service I didnโt know existed
questioned my career choices
shipped it anyway
Software development is basically side quests with a salary. ๐ญ
Everyone is building AI apps.
Fewer people are thinking about what happens when the AI is slow, expensive, wrong, or unavailable.
That's the part of AI engineering I find interesting.
Looking for my next opportunity ๐
Full Stack & AI Engineer | ~1 YOE
React โข Next.js โข Node.js โข Python โข FastAPI โข RAG โข LLMs โข Redis โข AWS
If youโre hiring, Iโd really appreciate a DM or share.
GitHub: https://t.co/Z9WufjN768
Good developers write code that works.Great developers write code that other developers can understand six months later.Readability scales better than cleverness.#Coding#SoftwareEngineering
Built a modular RAG pipeline focused on making AI responses more context-aware and reliable using semantic retrieval and dynamic context injection.
One thing Iโve learned: retrieval quality impacts output far more than prompt engineering.
#RAG#AI#LLM#SemanticSearch#Nextjs