MCP vs RAG vs Skill

 

The world of AI is moving fast—so fast that "just chatting" with an LLM is quickly becoming old news. Today, we’re building AI Agents: systems that don't just talk, but actually do things.

But how do these agents get smarter? If you’ve been looking at modern AI architectures, you’ve likely bumped into three terms: MCP, RAG, and Skills. While they all aim to improve AI performance, they solve very different problems.

1. MCP (Model Context Protocol): The Universal Plug

Think of MCP as the "USB-C port" for AI.

2. RAG (Retrieval Augmented Generation): The Open-Book Test

RAG is the most common way to give an AI "long-term memory" or access to private data it wasn't trained on.

3. Agent Skills: The Toolbelt

If RAG is about knowing and MCP is about connecting, Skills are about doing. A "Skill" is a predefined set of actions or code that an agent can execute to solve a specific problem.

Feature	MCP	RAG	Skills
Primary Goal	Standardized Integration	Context & Accuracy	Action & Task Execution
Analogy	A Universal Adapter	An Open-Book Library	A Specialized Toolbelt
Data Source	Live Apps (Slack, Search)	Static Docs (PDFs, DBs)	Code/Functions (Python, Shell)
User Value	"Check my messages"	"What does our policy say?"	"Fix this code and deploy it"

GPT-5.5

OpenAI officially released GPT-5.5 (codenamed "Spud") on April 23, 2026. This model represents a shift from raw parameter scaling to agentic efficiency, focusing on the model's ability to operate autonomously across software tools and perform complex, multi-step professional work with minimal human oversight.

Technical Specs & Pricing

GPT-5.5 builds on the "Thinking" architecture introduced in GPT-5.4, but with a major focus on reliability and "computer use" with agentic coding, reduced hallucinauts and visual precision. GPT 5.x improvements are depicted in the diagram.

For developers, the API pricing reflects a competitive move against the growing open-source market (like GLM-5.1 and Llama 4):

• Input Cost: $5.00 per million tokens.

• Output Cost: $30.00 per million tokens.

• Efficiency: OpenAI claims GPT-5.5 maintains the same latency as GPT-5.4 while using fewer tokens per task, effectively lowering the "cost-per-result" for complex workflows.

As early bird, I'm already started making my hands dirty on GPT5.5 !

Cursor SpaceX acquisition

In a major move within the AI and aerospace sectors, SpaceX has officially entered a strategic partnership with Cursor (developed by Anysphere), including a massive option to acquire the AI coding startup for $60 billion.

The deal, announced in April 2026, signals Elon Musk’s intent to consolidate his tech empire—integrating software development, supercomputing, and space infrastructure ahead of a planned SpaceX IPO.

The Deal Structure

SpaceX has secured two distinct paths for the partnership to be finalized later in 2026:

• Acquisition Option: SpaceX has the right to buy Cursor outright for $60 billion. This would be the largest AI startup acquisition to date.
  

• Collaboration Option: If SpaceX chooses not to acquire the company, it will pay $10 billion as a strategic fee to continue working together on development.
  
  

Key Strategic Objectives

• Compute Power: Cursor will gain access to Colossus, the xAI-built supercomputer (now owned by SpaceX following a February 2026 merger). Colossus utilizes the power equivalent of roughly one million Nvidia H100 chips, which Cursor intends to use to scale its "Composer" models and break through previous compute bottlenecks.
  

• Vertical Integration: By bringing Cursor into the fold, Musk aims to create a unified ecosystem for "coding and knowledge work AI." This puts SpaceX in direct competition with OpenAI’s Codex and Anthropic’s Claude Code.
  

• IPO Momentum: The deal comes as SpaceX gears up for its own massive IPO (projected at a $1.75 trillion valuation). Integrating a high-growth AI company with $2 billion in annual recurring revenue (ARR) strengthens the "tech conglomerate" narrative for potential public investors.

GlassWing

Project Glasswing is a major cybersecurity initiative launched by Anthropic on Tuesday April 7, 2026. It is designed to use advanced AI to find and patch software vulnerabilities in the world's most critical digital infrastructure before they can be exploited by malicious actors.

At the heart of the project is Claude Mythos Preview, a frontier AI model so powerful at coding and vulnerability discovery that Anthropic has deemed it too dangerous for public release. 

Core Objectives

• Defensive Advantage: The project aims to give "defenders a head start" by identifying zero-day vulnerabilities (flaws unknown to developers) in a controlled environment.

• Securing Critical Infrastructure: It focuses on the software that runs power grids, banking systems, hospitals, and major tech platforms

• Open-Source Support: Anthropic has committed $100 million in model credits and $4 million in direct donations to open-source security organizations to help them secure the codebases that underpin the modern internet.

Why is it called "Glasswing"?

The project is named after the Glasswing butterfly, known for its transparent wings. This symbolizes the goal of creating "transparency" in software code—making vulnerabilities visible so they can be fixed—while also representing the fragile nature of the current digital ecosystem.