Monday, January 12, 2026

What is generative AI and agentic AI , explain with example ?

What is Generative AI?

Definition

Generative AI is a type of Artificial Intelligence that can create new content based on what it has learned from existing data.

It doesn’t just analyze or classify data — it generates:

Text
Images
Code
Audio
Video

In simple words:

Generative AI creates something new rather than just responding with predefined answers.

How Generative AI Works (Simplified)

Generative AI models:

Learn patterns from large datasets
Understand relationships between words, images, or sounds
Generate new output that follows those learned patterns

Most generative AI systems are based on:

Large Language Models (LLMs) for text
Diffusion / GAN models for images

Examples of Generative AI

1️⃣ Text Generation

✅ ChatGPT, Copilot, Gemini

Example:

Writing emails
Creating documentation
Generating SQL queries
Summarizing reports

You ask:
“Write an email to request database downtime”
Generative AI creates a new email, not copied from anywhere.

2️⃣ Code Generation

✅ GitHub Copilot

Example:

Auto‑generates Python, SQL, Java code
Suggests optimized queries

📌 Useful for DBAs:

Generate scripts
Write monitoring queries
Create automation logic

3️⃣ Image Generation

✅ DALL·E, Midjourney

Example:

Create system architecture diagrams
Generate design mockups

You describe → AI generates a new image.

4️⃣ Database & IT Example

Generative AI can:

Generate SQL tuning suggestions
Create incident RCA summaries
Write SOP or runbooks

✅ Example:

Automatically generating a root cause analysis after a database outage

Key Characteristics of Generative AI

Aspect	Description
Output	New content
Creativity	High
Autonomy	Limited
Decision Ownership	Human

What is Agentic AI?

Definition

Agentic AI refers to AI systems that can act autonomously to achieve a goal by:

Planning steps
Making decisions
Taking actions
Adjusting based on results

In simple words:

Agentic AI doesn’t just generate content — it decides what to do next and does it.

How Agentic AI Works

An Agentic AI system typically has:

Goal – What needs to be done
Planning capability – Breaks goal into tasks
Tools access – APIs, databases, scripts
Feedback loop – Learns from results
Decision logic – Chooses next action

It often uses Generative AI as one component, but adds autonomy.

Real‑World Examples of Agentic AI

1️⃣ AI Operations Agent (IT / DBA Example) ✅

🔹 Goal: “Keep database running optimally”

Agentic AI actions:

Monitor CPU, memory, waits
Detect abnormal behavior
Analyze historical patterns
Decide: scale resources / kill session / raise incident
Execute automatically or seek approval

📌 Unlike Generative AI:

It does not wait for a prompt
It acts on its own

2️⃣ Self‑Healing Systems

✅ Common in modern DevOps

Example:

App crashes
Agentic AI detects failure
Restarts service
Verifies recovery
Notifies team

No human prompt required.

3️⃣ Autonomous Customer Support Agent

🔹 Goal: “Resolve customer issues”

Steps:

Understand issue
Query CRM
Reset password
Update ticket
Close issue

📌 A chatbot that only replies is Generative AI
📌 A bot that resolves the issue end‑to‑end is Agentic AI

4️⃣ AI Shopping Agent

You say:

“Buy the cheapest laptop with 16GB RAM”

Agentic AI:

Searches websites
Compares prices
Applies filters
Makes decision
Places order (with rules)

Key Characteristics of Agentic AI

Aspect	Description
Output	Actions + decisions
Autonomy	High
Goal‑oriented	Yes
Tool usage	Yes
Self‑correction	Yes

Generative AI vs Agentic AI (Clear Comparison)

Feature	Generative AI	Agentic AI
Core Purpose	Create content	Achieve goals
Autonomy	Low	High
Requires Prompt	Yes	Often No
Takes Actions	❌ No	✅ Yes
Uses Tools	Limited	Extensive
Example	ChatGPT writing email	AI auto‑healing a DB

Simple Real‑Life Analogy

✅ Generative AI

Like a skilled writer who creates content when asked.

✅ Agentic AI

Like a project manager who decides what to do, assigns tasks, and ensures results.

Combined Example (Very Important)

Most modern systems use both together:

📌 Agentic AI + Generative AI

Agent plans and decides
Generative AI produces text, code, explanations

✅ Example: AI SRE Agent:

Detects incident (Agentic)
Diagnoses cause (Agentic)
Generates RCA document (Generative AI)
Executes fix (Agentic)
Sends summary email (Generative AI)

Interview‑Ready Summary (2–3 lines)

“Generative AI focuses on creating new content like text, code, or images based on learned patterns. Agentic AI goes a step further by autonomously planning, deciding, and taking actions to achieve a goal, often using Generative AI as part of its decision process.”

what is AI and Type of AI ?

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is a branch of computer science that focuses on creating systems or machines that can simulate human intelligence to perform tasks such as:

Learning from data
Reasoning and decision‑making
Problem‑solving
Understanding language
Recognizing images or patterns

In simple words:

AI enables machines to think, learn, and act like humans—within a defined scope.

Key Capabilities of AI

AI systems can:

✅ Learn from experience (Machine Learning)
✅ Adapt to new inputs
✅ Make predictions or decisions
✅ Automate complex tasks
✅ Improve performance over time

Types of AI

AI is commonly classified in two major ways:

Based on Capability
Based on Functionality

1️⃣ Types of AI Based on Capability

1. Narrow AI (Weak AI)

This is the most common form of AI today.

Definition:

AI systems designed to perform one specific task very efficiently.

They cannot think, reason, or act beyond their assigned task.

Examples:

✅ Google Search
✅ Chatbots (customer support bots)
✅ Voice assistants (Siri, Alexa)
✅ Recommendation systems (Netflix, YouTube, Amazon)
✅ Fraud detection systems in banks

How it Works:

Operates using trained models
Uses historical data
Executes predefined tasks without self‑awareness

📌 Example:

A chatbot can answer questions about orders but cannot understand emotions or unrelated topics like a human.

Summary:

Feature	Narrow AI
Scope	Single task
Learning	Yes
Self‑awareness	No
Exists Today	✅ Yes

2. General AI (Strong AI)

This type of AI can perform any intellectual task that a human can do.

Definition:

A system with human‑level intelligence, capable of understanding, learning, reasoning, and applying knowledge across multiple domains.

Capabilities:

Think logically
Reason abstractly
Learn any topic
Transfer knowledge across tasks
Understand emotions and context

Current Status:

❌ Does not exist today

General AI is still theoretical and under research.

Example (Hypothetical):

An AI that can:

Learn medicine
Write novels
Drive a car
Teach students
Make business decisions

…all without being retrained for each task.

Summary:

Feature	General AI
Scope	Multiple tasks
Learning	Independent
Self‑awareness	Possible
Exists Today	❌ No

3. Super AI

This represents AI that surpasses human intelligence in all aspects.

Definition:

AI that exceeds human intelligence in:

Creativity
Decision‑making
Emotional intelligence
Social skills

Capabilities:

Self‑improving
Superior problem solving
Independent goal setting
Potentially uncontrollable

Current Status:

❌ Does not exist Only discussed in science fiction and future research.

Example (Fiction):

AI in movies like Her, Matrix, or Ex Machina

Summary:

Feature	Super AI
Intelligence	Beyond humans
Control	Self‑directed
Exists Today	❌ No

2️⃣ Types of AI Based on Functionality

1. Reactive Machines

The simplest form of AI.

Characteristics:

No memory
Reacts only to current input
Cannot learn from past experience

Example:

IBM Deep Blue (chess computer)

📌 Deep Blue could defeat chess champions but didn’t learn improvement strategies over time.

2. Limited Memory AI

Most modern AI systems fall into this category.

Characteristics:

Uses past data
Learns from historical patterns
Improved decision making

Example:

Self‑driving cars
Fraud detection systems
Recommendation engines

📌 A self‑driving car remembers recent traffic patterns but does not have long‑term memory like humans.

3. Theory of Mind AI

This type of AI understands:

Human emotions
Intentions
Beliefs

📌 Still under research.

Example:

Emotion‑aware robots (experimental)

4. Self‑Aware AI

The most advanced stage.

Characteristics:

Consciousness
Self‑awareness
Independent decision making

📌 Does not exist today.

Real‑World AI Examples (Detailed)

1️⃣ AI in Healthcare

Disease prediction
Medical imaging analysis
Drug discovery

✅ Example: AI analyzes MRI scans to detect cancer faster than traditional methods.

2️⃣ AI in Banking

Fraud detection
Credit scoring
Chatbots for support

✅ Example: AI flags suspicious transactions in real‑time based on behavioral patterns.

3️⃣ AI in IT & Databases (Your Domain)

Performance tuning
Predictive failure analysis
Automated backups
Intelligent monitoring

✅ Example: AI predicts database outages by analyzing CPU, IO, and query trends.

4️⃣ AI in Everyday Life

Google Maps traffic predictions
YouTube recommendations
Spam email filters
Voice assistants

Short Interview‑Ready Summary

AI is the ability of machines to simulate human intelligence. Based on capability, AI is classified into Narrow AI, General AI, and Super AI. Today’s systems mostly fall under Narrow AI, performing specific tasks like recommendations or chatbots. Based on functionality, AI ranges from reactive systems to limited‑memory systems, with self‑aware AI still theoretical.

Interview Question 23 : What troubleshooting steps you will follow when user complaints about connectivity issue ?

When a user reports a database connectivity issue, I follow a structured, layered troubleshooting approach so I can isolate the problem quickly without jumping to conclusions. The goal is to identify whether the issue is user‑side, network‑side, listener‑side, or database‑side.

Below is my real‑world DBA troubleshooting checklist, explained step by step.

Database Connectivity Troubleshooting Steps

1️⃣ Gather Basic Information (Do First)

Before touching the system, I ask targeted questions:

Which application or user is affected?
Error message (ORA‑error, TNS‑error, timeout, etc.)
From where is user connecting? (App server, laptop, batch job)
Is it one user, multiple users, or all users?
When did it start? Sudden or intermittent?
Has anything changed recently? (patch, password change, server reboot)

📌 This helps narrow down whether it's a local or global issue.

2️⃣ Check if Database Is Up

First, I verify database status on the server:

ps -ef | grep pmon

sqlplus / as sysdba

Then:

SELECT status FROM v$instance;

✅ Expected: OPEN

Possible findings:

DB down → startup required
DB mounted or restricted → user connections blocked

3️⃣ Validate Listener & Network Services

Most connectivity issues are listener or network related.

Check listener status

lsnrctl status

Ensure:

Listener is running
Correct SERVICE_NAME is registered
No errors like:
- TNS-12541: no listener
- TNS-12514: listener does not know of service

Restart listener (if safe)

lsnrctl stop

lsnrctl start

4️⃣ Test Local Connectivity

To rule out OS/network issues:

sqlplus user/pass@localhost:1521/service

or:

tnsping service_name

✅ If local connection works but remote fails → likely network firewall or routing issue

5️⃣ Check Database Service Registration

Inside database:

SHOW PARAMETER service_names;

SELECT name FROM v$services;

If service not registered:

ALTER SYSTEM REGISTER;

Also check:

SHOW PARAMETER local_listener;

6️⃣ Review Listener Logs

Listener log path:

$ORACLE_HOME/network/log/listener.log

Look for:

Connection refusals
Service handler issues
High connection rate
Service UNKNOWN status

7️⃣ Verify User Account Status

If only specific users are affected:

SELECT username, account_status

FROM dba_users

WHERE username = 'USER1';

Check for:

LOCKED
EXPIRED
Password changed recently

Unlock if needed:

ALTER USER user1 ACCOUNT UNLOCK;

8️⃣ Check Resource & Session Limits

Connectivity can fail if limits are hit:

SELECT resource_name, current_utilization, limit_value

FROM v$resource_limit

WHERE resource_name IN ('processes','sessions');

If limits reached:

Increase parameters
Kill runaway sessions
Restart application tier if required

9️⃣ Validate Network & Firewall

If DB and listener look fine:

Confirm DB port (1521) open
Check firewall or load balancer changes
Coordinate with network team

Typical errors:

ORA-12170: TNS connect timeout
Random disconnections

🔟 Check Application & Connection Pool

For application issues:

Connection pool exhaustion
Stale connections
Incorrect TNS string
Hardcoded passwords

Fix:

Restart app
Correct JDBC/tns configuration
Clear pool

1️⃣1️⃣ Review Alert Log

Always check database alert log:

$ORACLE_BASE/diag/rdbms/*/*/trace/alert*.log

Look for:

ORA‑errors
PMON cleanup issues
Instance restarts
Network errors

Summary Flow (Quick Mental Model)

User → App → Network → Listener → DB → Service → User Account

Common Scenarios & Root Causes

Symptom	Likely Cause
All users down	DB or listener down
One user down	Account locked / password
App down, SQL works	Pool / config issue
Intermittent	Network / firewall
ORA‑12514	Service not registered
ORA‑12170	Timeout / network

Interview‑Ready Answer (Concise)

“When a user reports connectivity issues, I first gather error details and scope, then verify database status, listener health, service registration, and user account state. I test local connectivity, review listener and alert logs, check resource limits, and finally coordinate with network or application teams if needed.”

DBA Best Practice

✅ Always fix root cause, not just restart
✅ Document incident for future prevention
✅ Add monitoring for:

Listener
Connection count
Process/session usage

Interview Question 22 : Explain about oracle database each stage in open till open include nomount , mount , open ?

Oracle Database Startup Stages

(From SHUTDOWN to OPEN State)

Oracle database startup happens in three logical stages:

NOMOUNT  →  MOUNT  →  OPEN

Each stage gives Oracle access to different components of the database.

1. NOMOUNT Stage

What happens in NOMOUNT?

At this stage:

✅ Instance is started
✅ Memory structures and background processes are created
❌ Database files are NOT accessed

Components Started

During NOMOUNT:

SGA is allocated
Background processes start:
- SMON
- PMON
- DBWn
- LGWR
- CKPT
Initialization parameter file is read:
- spfile or pfile

What is NOT Available?

Control files ❌
Data files ❌
Redo log files ❌

📌 At NOMOUNT, Oracle knows how to start, but not which database to open.

Command

STARTUP NOMOUNT;

When is NOMOUNT Used?

Creating a new database
Re‑creating control files
Troubleshooting severe corruption
Checking initialization parameters

✅ Example:

CREATE DATABASE testdb;

(Database must be in NOMOUNT state before this command)

Diagram

NOMOUNT
|
|-- SGA allocated
|-- Background processes started
|-- Init. parameters read

2. MOUNT Stage

What happens in MOUNT?

At this stage:

✅ Control files are opened
✅ Oracle knows the database structure
❌ Data files and redo logs are still NOT opened

Oracle now knows:

Database name
Data file locations
Redo log file locations
SCN and checkpoint information

Command

STARTUP MOUNT;

ALTER DATABASE MOUNT;

What is Accessible?

✅ Control files
❌ Data files
❌ Redo logs
❌ User sessions

Only DBA users can connect:

sqlplus / as sysdba

When is MOUNT Used?

Database recovery
Renaming a database
Enabling ARCHIVELOG mode
Restoring datafiles
Handling missing or corrupt files

✅ Example:

ALTER DATABASE ARCHIVELOG;

✅ Example:

RECOVER DATABASE;

Diagram

MOUNT
|
|-- Control files opened
|-- Database structure known
|-- No user access

3. OPEN Stage

What happens in OPEN?

At this stage:

✅ Data files are opened
✅ Redo log files are opened
✅ Database is fully operational

Oracle verifies:

Data files match control file SCN
Crash recovery (if needed) is completed
Redo is applied automatically

Command

ALTER DATABASE OPEN;

or simply:

STARTUP;

(Default STARTUP = NOMOUNT → MOUNT → OPEN)

Database in OPEN State

✅ Users can connect
✅ DML and DDL allowed
✅ Transactions possible
✅ Applications start working

OPEN Modes

Oracle can open the database in different modes:

a) READ WRITE (Default)

ALTER DATABASE OPEN;

b) READ ONLY

ALTER DATABASE OPEN READ ONLY;

Used for:

Reporting
Data verification
Standby databases

c) RESTRICTED

ALTER SYSTEM ENABLE RESTRICTED SESSION;

ALTER DATABASE OPEN;

Only users with RESTRICTED SESSION privilege can connect.

Diagram

OPEN
|
|-- Data files opened
|-- Redo log files opened
|-- Users allowed
|-- Database operational

Summary Table

Stage	Instance	Control Files	Data Files	Redo Logs	User Access
NOMOUNT	✅ Yes	❌ No	❌ No	❌ No	❌ No
MOUNT	✅ Yes	✅ Yes	❌ No	❌ No	❌ No
OPEN	✅ Yes	✅ Yes	✅ Yes	✅ Yes	✅ Yes

Real‑World DBA Example

Scenario: Control file corruption
Steps:

SHUTDOWN IMMEDIATE;

STARTUP NOMOUNT;

CREATE CONTROLFILE ...

ALTER DATABASE MOUNT;

ALTER DATABASE OPEN;

Interview‑Ready One‑Line Explanation

Oracle database startup occurs in three stages: NOMOUNT starts the instance, MOUNT opens control files, and OPEN makes the database available to users by opening data files and redo logs.