Building an AI agent in 2025?

Here's the stack you need to know:

1. Memory:
* Stores and retrieves past conversations, context, and long-term knowledge.
* Popular services include zepai, mem0, cognee.

2. No-code/Low-code Tools:
* Lets you build agents without writing code.
* Popular platforms include Build That Idea, Flowise, n8n, Gumloop, Voiceflow, Make.

3. Tool Libraries:
* Give agents the ability to search, browse, code, or perform actions on the internet.
* Popular libraries include Exa, Composio, Browserbase.

4. Observability:
* Tracks, monitors, and debugs agent behavior in real time.
* Popular platforms include Langsmith, AgentOps, Langfuse, Braintrust.

5. Agent Orchestration:
* Manages workflows, multi-agent coordination, and complex task execution.
* Popular frameworks include Langchain, AG, Crew AI, LlamaIndex, OAI.

6. Foundational Models:
* LLMs that power reasoning, generation, and understanding.
* Popular models include OpenAI, DeepSeek, Gemini, Qwen, Anthropic, Mistral.

7. Agent Frameworks:
* Provide the logic and building blocks for creating autonomous agents.
* Popular frameworks include PhiData, Letta, LangGraph, LlamaIndex, CrewAI, AutoGen, AutoGPT.

8. Storage:
* Handles vector embeddings, structured data, or file management.
* Popular databases include Chroma, Weaviate, Supabase, Neon, Pinecone.

9. Infra/Base:
* Supports deployment, scaling, and containerization of agent systems.
* Popular infrastructure includes Docker, Kubernetes, Auto Scale VMs.

10. GPU/CPU Providers:
* Offer compute power for training and running models.
* Leading providers include Azure, AWS, Groq, Lambda, Runpod, Nvidia.

What did we miss?