Most people say "build an AI agent."
Very few know what that actually means.
Here’s the real blueprint to go from idea → working agent 👇
1. Define the job
What problem are you solving?
Who’s the user? What does success look like?
2. Design the brain
Clear system prompt, role, instructions, guardrails
(This is where most agents fail)
3. Pick the right model
Speed vs cost vs intelligence
Don’t overpay for simple tasks
4. Add tools
APIs, databases, MCP servers, custom functions
Agents become powerful when they can act, not just answer
5. Give it memory
Short-term + long-term context
So it learns, adapts, and improves over time
6. Orchestrate everything
Workflows, triggers, retries, agent-to-agent communication
7. Build the interface
Chat, app, API, Slack bot
Make it usable, not just functional
8. Test + improve
Evals, latency checks, real-world feedback
Iteration is the real moat
💡 Truth:
An “AI agent” isn’t one prompt.
It’s a system.
And the people who understand systems…
are the ones building unfair advantages right now.
📌 Save this (you’ll need it when you build)
🔁 Repost for builders
➕ Follow @elora_khatun for practical AI breakdowns (no fluff) 🚀
Stop wasting hours trying to learn AI. 📘📚
I have already done it for you.
With one list. Zero confusion. And no fluff
📹 Videos:
1. LLM Introduction: https://t.co/YkuDFVmW9e
2. LLMs from Scratch: https://t.co/u3kSz5SGuJ
3. Agentic AI Overview (Stanford): https://t.co/W6rzVHGSgC
4. Building and Evaluating Agents: https://t.co/sEl8vVax3F
5. Building Effective Agents: https://t.co/c7fD4aWFYO
6. Building Agents with MCP: https://t.co/GlMdR6htgA
7. Building an Agent from Scratch: https://t.co/kUQ9jPuI0R
8. Philo Agents: https://t.co/8JHvqw0DKn
🗂️ Repos
1. GenAI Agents: https://t.co/cyHPvOAjlK
2. Microsoft's AI Agents for Beginners: https://t.co/zFJAN74JQe
3. Prompt Engineering Guide: https://t.co/liUshX2XsP
4. Hands-On Large Language Models: https://t.co/TXFhbiboZY
5. AI Agents for Beginners: https://t.co/zFJAN74JQe
6. GenAI Agentshttps://lnkd.in/dEt72MEy
7. Made with ML: https://t.co/lkXP6itwK0
8. Hands-On AI Engineering:https://t.co/zB8EEctE4Y
9. Awesome Generative AI Guide: https://t.co/lF7CuIQHRw
10. Designing Machine Learning Systems: https://t.co/XlYUZYOoVi
11. Machine Learning for Beginners from Microsoft: https://t.co/hF5UzZoMJB
12. LLM Course: https://t.co/4tLAwy8fOQ
🗺️ Guides
1. Google's Agent Whitepaper: https://t.co/0OEKVLgF34
2. Google's Agent Companion: https://t.co/r0Dxe4VvDO
3. Building Effective Agents by Anthropic: https://t.co/I0ZyuwiOS3.
4. Claude Code Best Agentic Coding practices: https://t.co/HIBC2TwwAP
5. OpenAI's Practical Guide to Building Agents: https://t.co/1I8n0wnjHQ
📚Books:
1. Understanding Deep Learning: https://t.co/XEzhyAcWbq
2. Building an LLM from Scratch: https://t.co/4sZmBnHPEg
3. The LLM Engineering Handbook: https://t.co/IkAYNFkVNI
4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://t.co/KsFnET47hx
5. Building Applications with AI Agents - Michael Albada: https://t.co/lJhMLtsLql
6. AI Agents with MCP - Kyle Stratis: https://t.co/C2lhD8uTDL
7. AI Engineering: https://t.co/34EyUiIVMv
📜 Papers
1. ReAct: https://t.co/kfQ8tWysne
2. Generative Agents: https://t.co/wbfqXq8KZK.
3. Toolformer: https://t.co/OQ7m49YWls
4. Chain-of-Thought Prompting: https://t.co/XeNgLQdTIL.
🧑🏫 Courses:
1. HuggingFace's Agent Course: https://t.co/tUZyPEGhni
2. MCP with Anthropic: https://t.co/wx1DAIWis0
3. Building Vector Databases with Pinecone: https://t.co/8XsQzDstTB
4. Vector Databases from Embeddings to Apps: https://t.co/9n6DvZGTMN
5. Agent Memory: https://t.co/OxFAaM0fp7
Repost for your network ♻️
HyperFrames, now natively in Claude Design
Drop in the skill file, generate motion graphics, download project
ask Claude Code or run command:
$ npx hyperframes render
Design to animation to MP4, all in one flow
details in thread
.@Esri launched @CityEngine 2024, introducing Visual CGA Editor, a node-based programming interface that simplifies building designs for users without programming backgrounds.
More new features: https://t.co/g02JS3xM42
#cityengine#archviz#procedural
The following is a general summary of my personal philosophy regarding painting. It is a verbalization of my own research and standards for areas that I did not understand well before, and then I actually tried it out.
Sem nenhum aviso prévio o X (esta plataforma aqui) colocou nas configurações uma opção autorizando que todas as postagens, interações e dados serão usados para treinar sua inteligência artificial, o Grok, e colocou como resposta padrão "sim" para todos os usuários.