Mohammed Junaid

Let’s understand embeddings in 5 quick tweets. This is the core idea behind RAG, semantic search, and vector databases:

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Why embeddings matter: They power: • RAG • AI search • recommendations • memory systems Most modern AI products rely on them.

Let’s understand why AI agents need tools in 5 quick tweets. Without tools, agents are way less useful than people think:

Let’s understand AI memory in 5 quick tweets. Why ChatGPT “remembers” some things, forgets others, and why memory matters for AI products:

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Without tools: AI is chat. With tools: AI becomes software infrastructure.

Let’s understand function calling vs MCP in 5 quick tweets. They sound similar, but they solve different problems:

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Why it matters: Without memory: AI feels like a chatbot. With memory: It feels like software. That’s the shift happening right now.