We have officially entered the era of #VibeCoding. It's no longer about syntax; itโs about being a "System Architect" while the AI agents handle the heavy lifting.
โข Context is King: AI now indexes million-line codebases instantly.
โข Self-Correction: Agents are now fixing their own build errors without human prompts.
โข Speed: 1 year of corporate bureaucracy vs. 1 hour of raw AI reasoning.
Are we witnessing the end of "writing" code and the start of "curating" it?
#AICoding #ClaudeCode #SoftwareEngineering #VibeCoding #Programming2026 #Grok #BuildInPublic
Youโre right @elonmusk. Focus on this topic. Aging has a relatively simple explanation and is apparently reversible. Clinical trials begin shortly๐ค
Example app is @cleverai_app
Clever AI Hub used all the items mentioned above to empower +100k users.
I built this 3 years ago so users donโt have to pay for multiple AI subscriptions and to be able to personalize their AI experience.
The modern AI stack is moving fast. Here is a breakdown of the 7 concepts you need to know to stay ahead:
LLM, RAG, Tools, MCP, Workflow, Agents, and Multi-agents. ๐
๐ง 1. LLM (Large Language Model)
The core engine. Think of an LLM as a library that has read nearly everything. Itโs a prediction machine that generates human-like text based on its training.
โข The limitation: It has a knowledge cutoff. It doesnโt know what happened this morning.
๐2. RAG (Retrieval-Augmented Generation)
This is how you give an LLM an "open-book" exam. Instead of relying on memory, RAG allows the model to look up your specific documents or databases before answering.
โข Why it matters: It stops hallucinations and provides real-time accuracy.
๐ ๏ธ 3. Tools & Functions
By itself, an LLM is just a brain. Tools give it hands.
You can give an AI access to a calculator, a web search, or a database connection. This transforms it from a "talker" into a "doer."
๐ 4. MCP (Model Context Protocol)
The "Universal USB-C" for AI.
Introduced by Anthropic, MCP is a standard that allows models to easily connect to data sources (like Google Drive or Local Files) without building custom integrations every time. Itโs the bridge between models and your data.
โ๏ธ 5. Workflow
The "blueprint." A Workflow is a predefined sequence of steps.
While an LLM can be random, a workflow ensures reliability. Itโs the "If This, Then That" logic that tells the AI: "First search the data, then summarize it, then format it as an email."
๐ค 6. Agents & Multi-Agents
An Agent is an LLM with a goal and autonomy. It plans, uses tools, and corrects itself.
A Multi-agent system is a team of these specialized AIs working together.
โข One researches.
โข One writes code.
โข One reviews.
The result? Higher quality with less human oversight.
๐ The Bottom Line
Intelligence (LLM) is becoming a commodity. The real value is in Context (RAG/MCP) and Structure (Workflows/Agents).
The winners in this era won't just be the ones with the best prompts, but the ones with the best systems.
@jonathanbrnd The 30s are the new 20s, just look at how people in their 30s looked 50 years ago. It's never too late. Keep up the good work and good luck!
explain ChatGPT in 2007
akinator was basically the chatgpt of its time.
if this blew your mind back thenโฆ congrats, your knees probably crack now
#ChatGPT