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What's New in AI (2026 Edition)

For Returning Users

If you learned AI in 2023-2024, welcome back! The landscape has transformed dramatically. This page gets you up to speed quickly.

The Biggest Shifts​

1. Chat → Agents 🤖​

Then (2024):

  • You: "Write a marketing plan"
  • AI: [Writes text]
  • You: [Copies, pastes, uses manually]

Now (2026):

  • You: "Create and execute a marketing campaign"
  • Agent: [Researches competitors, generates content, creates calendar, schedules posts, monitors performance]
  • You: [Reviews automated work]

The shift: AI now completes entire workflows autonomously.

Tools to try:

2. Tiny Context → Massive Context 📏​

Then:

  • GPT-4: 8K tokens (≈6 pages)
  • Claude: 100K was revolutionary
  • Workarounds needed for long documents

Now:

  • Standard: 200K tokens (≈500 pages)
  • Gemini: 2M tokens (≈5,000 pages)
  • You can give AI entire codebases or document libraries

What this means:

  • No more splitting documents
  • AI understands full project context
  • Better, more coherent long-form work

3. Skills & Customization Ecosystem 🧩​

Then:

  • Base model only
  • Some custom GPTs
  • Limited customization

Now:

  • Skills.sh - Marketplace of AI capabilities
  • Custom skills for any use case
  • MCP servers for tool integration
  • Skills work across platforms

Example: Instead of prompting "analyze data like an expert", install a "Data Analysis" skill that knows your preferred methods, tools, and output format.

4. MCP Becomes Standard 🔧​

Model Context Protocol (MCP) is now the universal way to connect AI to tools.

One MCP server → Works with Claude, ChatGPT, Gemini

Popular servers:

  • GitHub (repos, issues, PRs)
  • Slack (messages, search)
  • Postgres (database queries)
  • Filesystem (read/write files)
  • Google Drive (docs, sheets)

Impact: Build integrations once, use everywhere.

Learn more: MCP Introduction

5. Multi-Modal Is Default 🎨​

Then:

  • Text models separate from image models
  • Had to switch modes
  • Limited integration

Now:

  • Text, images, audio, video in one interface
  • No mode switching
  • Seamless multi-modal reasoning

Example: "Analyze this chart [image], compare to this data [file], and create a video explanation [generation]" - all in one conversation.

Major Model Updates​

Claude Sonnet 4.5 (Late 2025)​

What's new:

  • Computer use (controls browsers, apps)
  • Extended thinking mode
  • 200K standard context
  • Better coding and reasoning

Best for: Autonomous agents, complex coding, research

Try it: claude.ai

GPT-4.5 (2025)​

What's new:

  • Improved reasoning
  • Better tool use
  • GPT Store matured
  • More reliable outputs

Best for: General use, custom GPTs, familiar interface

Gemini 2.0 Flash (Late 2025)​

What's new:

  • 2M token context (largest available)
  • Flash thinking for speed
  • Deep Google integration
  • Native multi-modal

Best for: Research, massive documents, Google Workspace users

New Tool Categories​

AI-First Code Editors​

Winners:

  1. Cursor - Most popular, VS Code fork with AI
  2. Windsurf - New contender with strong agent mode
  3. VS Code + Copilot - Still relevant but losing ground

What changed: AI isn't a plugin anymore, it's the core interface.

Natural Language to App​

Game changers:

  • v0.dev - Describe UI → Get React components
  • Bolt.new - Full-stack apps from descriptions
  • Replit Agent - Entire deployed apps in minutes

Impact: Non-developers building functional software.

No-Code Agent Builders​

Platform tier:

  • Relevance AI - Build "AI employees"
  • Lindy - Personal AI assistant
  • Respell - Workflow automation
  • Zapier Central - Natural language automation

Impact: Anyone can build custom agents without coding.

Browser Agents​

  • Claude in Chrome - Research and automation
  • MultiOn - General web agent
  • Browserbase - Headless browser for agents

Use case: "Research these 10 companies and create comparison spreadsheet" - agent handles everything.

Deprecated / Less Relevant​

What's fading:

  • ChatGPT Plugins → Replaced by GPT Actions and MCP
  • Jasper/Copy.ai → Base models got so good, specialized tools less needed
  • Basic code completion only tools → Agents do more than autocomplete now
  • Tabnine → Still exists but Cursor/Copilot dominated

Pricing Changes​

Standard pricing (2026):

  • Claude Pro: $20/month
  • ChatGPT Plus: $20/month
  • Gemini Advanced: $20/month
  • Cursor Pro: $20/month
  • Copilot: $10/month (still cheapest for code)

Enterprise:

  • Most platforms: $30-40/user/month
  • More usage limits, admin controls, SSO

Free tiers:

  • Still available but limited
  • Claude Free: Basic access
  • ChatGPT Free: GPT-4o mini
  • Gemini Free: Gemini 1.5 Flash

Skills You Should Learn (2026)​

For Everyone​

  1. Agent delegation - How to give tasks vs ask questions
  2. Skill creation - Extending AI with custom capabilities
  3. Basic MCP - Understanding tool connections

For Technical Users​

  1. LangGraph or CrewAI - Agent orchestration frameworks
  2. MCP server creation - Build custom integrations
  3. Prompt caching - Optimize costs and speed
  4. Agent safety - Sandboxing and guardrails

For Business Users​

  1. Workflow design - Thinking in agent processes
  2. No-code platforms - Relevance AI, Lindy, Respell
  3. ROI measurement - Proving agent value
  4. Team training - Getting team to think agentically

Common Mistakes (From 2024 Thinking)​

❌ Mistake 1: Still Treating AI Like Chat​

Old: "AI, write me an email" → Copy/paste → Send New: "Handle email responses for X type of inquiry" → Agent does it

❌ Mistake 2: Not Using Skills​

Old: Long, detailed prompts every time New: Create a skill once, reuse forever

❌ Mistake 3: Ignoring MCP​

Old: Copying data in and out manually New: Connect AI directly to your tools via MCP

❌ Mistake 4: Single Agent for Everything​

Old: One ChatGPT for all tasks New: Specialized agents for different domains (research agent, coding agent, writing agent)

❌ Mistake 5: Not Thinking in Workflows​

Old: One-off requests New: "What repeating workflow can an agent handle?"

Quick Start Guide (2026)​

Week 1: Foundation​

  • Try Claude Sonnet 4.5 or GPT-4.5
  • Give it a complete task (not just a question)
  • Watch it use tools autonomously
  • Browse skills.sh for ideas

Week 2: Skills & Customization​

  • Create your first custom skill
  • Install an MCP server
  • Build a simple agent workflow

Week 3: Development (if technical)​

  • Install Cursor or try v0.dev
  • Use Claude Code for a feature
  • Experiment with Bolt.new

Week 4: Deployment​

  • Pick one recurring task
  • Build an agent to handle it
  • Measure time saved

Resources for Catch-Up​

Essential Reading​

  1. AI Agents Overview - Core concepts
  2. 50+ Agent Use Cases - Practical examples
  3. Tools & Platforms 2026 - What to use
  4. Skills & Instructions - Customization

Communities​

Keep Learning​

  • AI changes fast - follow key platforms on social media
  • Join relevant Discord/Slack communities
  • Build something small each month
  • Share what you learn (teaching solidifies knowledge)

What's Coming Next (2026-2027)​

Predictions based on current trajectory:

  1. Agent-to-Agent Communication - Your agents talk to others' agents
  2. Persistent Agents - Agents that work 24/7 in background
  3. Specialized Hardware - Agent-optimized compute
  4. Agent Marketplaces - Buy/sell trained agents
  5. Regulation - Laws specifically for autonomous agents

The Bottom Line​

2024: AI was a powerful assistant 2026: AI is an autonomous teammate

The question changed from "What should I ask AI?" to "What should I delegate to my agents?"

Start here: AI Agents Overview

Welcome to 2026. Time to build some agents.