Next-Gen Artificial Intelligence

Learn Agentic
AI Systems

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Systems that reason, plan, act, and evolve — operating in continuous loops of perception, reasoning, and action.

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0 Core Agent Types
0 Ecosystem Tools
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01 — Foundation

What Is
Agentic AI?

Agentic AI refers to systems designed to act as autonomous agents — understanding goals, making decisions, using tools and APIs, and learning over time. Unlike single-turn models, these systems operate continuously.

  • Responds to single prompts only
  • Limited or no memory between turns
  • Cannot independently take actions
  • Requires constant human input
  • Works in isolation
  • Works across multiple steps autonomously
  • Maintains short-term and long-term memory
  • Uses tools, APIs, and external systems
  • Collaborates with humans or other agents
  • Continuously learns and adapts
▶ Live Agent Loop Simulation
[INIT] Agent runtime booting...
02 — Architecture

Agent Workflow

Every agentic system follows a continuous four-phase loop that mirrors human cognitive processes.

👁
Perception
Understanding input, environment context, and incoming data streams from the world.
🧠
Reasoning
Analyzing options with Chain-of-Thought, Tree-of-Thought, and LLM planning systems.
⚡
Action
Executing tasks via tools, APIs, databases, and coordinating with other agents.
🔄
Learning
Improving future behavior through feedback loops and memory consolidation.
03 — Agent Types

Types of AI Agents

Type-01
Reactive Agents
Respond immediately to environmental inputs without memory. Pure stimulus-response systems that are fast, predictable, and excellent for real-time tasks.
⚡
Type-02
Proactive Agents
Take initiative based on goals, anticipating future needs and acting before prompted. They model the world and reason about what should happen next.
🎯
Type-03
Goal-Driven Agents
Plan and execute complex multi-step tasks to achieve defined objectives. They decompose problems, allocate tools, and track progress toward outcomes.
🧩
04 — Ecosystem

Tools & Ecosystem

Agent Frameworks
LangChain AutoGen CrewAI Haystack
Vector Databases
Pinecone Weaviate FAISS Milvus
Orchestration
n8n Make Apache Airflow
Large Language Models
GPT-4.5 Claude LLaMA DeepSeek

▸ Agent Memory Layers

Short-Term
92%
Long-Term
67%
Contextual
78%
Episodic
45%
05 — Plans

Smart Choices,
Smarter Prices

Basic
Inquiry Analysis
$ 34 / mo
  • AI Integration layer
  • Basic agent workflows
Popular
Premium
Inquiry Analysis
$ 75 / mo
  • AI Integration layer
  • Multi-agent coordination
  • Long-term memory access
Standard
Inquiry Analysis
$ 45 / mo
  • AI Integration layer
  • Standard agent workflows
06 — FAQ

Frequently Asked
Questions

Agentic AI operates in continuous loops — perceiving, reasoning, acting, and learning — rather than responding once per prompt. It can use tools, call APIs, coordinate with other agents, and maintain memory across sessions. ChatGPT is a reactive model; agentic systems are autonomous actors.
LangChain is the most widely adopted and has the largest ecosystem. For multi-agent coordination, AutoGen from Microsoft and CrewAI are excellent. Start with LangChain to understand the fundamentals, then explore specialized frameworks.
Log in to your dashboard, navigate to Billing & Plans, and select the plan you'd like to switch to. Changes take effect at the start of your next billing cycle. PayPal and card payments are both supported.
It depends on your use case. GPT-4.5 and Claude excel at complex reasoning tasks. LLaMA and DeepSeek are cost-efficient open-source options for high-volume workloads. Many production systems use a mix, routing tasks to the most appropriate model.

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of Intelligence

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