docs: Add why section to the top

README.md

@@ -59,6 +59,19 @@ A powerful, self-contained Cron alternative with a clean Web UI and a [declarati
 - Email notification
 - Scheduling with Cron expressions
 
+
+## **Why we built Dagu**
+
+In many organizations, legacy systems still rely on hundreds of cron jobs running across multiple servers. These jobs are often written in various languages like Perl or Shell scripts, with implicit interdependencies. When one job fails, troubleshooting requires manually logging into servers via SSH and checking individual logs. To perform recovery, one must understand these implicit dependencies, which often rely on tribal knowledge. Dagu was developed to eliminate this complexity by providing a clear and understandable tool for workflow definition and dependency management.
+
+## **A Lightweight and Self-Contained Solution**
+
+While Cron is lightweight and suitable for simple scheduling, it doesn't scale well for complex workflows or provide features like retries, dependencies, or observability out of the box. On the other hand, tools like Airflow or other workflow engines can be overly complex for smaller projects or legacy environments, with steep learning curves and burdensome to maintain. Dagu is designed to be easy to use, self-contained, and require no coding, making it ideal for smaller projects.
+
+## **A Tool for Developers of Small Projects**
+
+Dagu's design philosophy stems from the real-world experience in managing complex jobs across diverse environments, from small startups to enterprise companies. By focusing on simplicity, transparency, and minimal setup overhead, Dagu aims to make life easier for developers who need a robust workflow engine without the heavy lift of a more complex tool.
+
 ## **Community**
 
 - Issues: [GitHub Issues](https://github.com/dagu-org/dagu/issues)
@@ -456,16 +469,6 @@ fi
 exit
 ```
 
-## **Motivation**
-
-Legacy systems often have complex and implicit dependencies between jobs. When there are hundreds of cron jobs on a server, it can be difficult to keep track of these dependencies and to determine which job to rerun if one fails. It can also be a hassle to SSH into a server to view logs and manually rerun shell scripts one by one. Dagu aims to solve these problems by allowing you to explicitly visualize and manage pipeline dependencies as a DAG, and by providing a web UI for checking dependencies, execution status, and logs and for rerunning or stopping jobs with a simple mouse click.
-
-Dagu addresses these pain points by providing a user-friendly solution for explicitly defining and visualizing workflows. With its intuitive web UI, Dagu simplifies the management of workflows, enabling users to easily check dependencies, monitor execution status, view logs, and control job execution with just a few clicks.
-
-## **Why Not Use an Existing DAG Scheduler Like Airflow?**
-
-There are many existing tools such as Airflow, but many of these require you to write code in a programming language like Python to define your DAG. For systems that have been in operation for a long time, there may already be complex jobs with hundreds of thousands of lines of code written in languages like Perl or Shell Script. Adding another layer of complexity on top of these codes can reduce maintainability. Dagu was designed to be easy to use, self-contained, and require no coding, making it ideal for small projects.
-
 ## **How It Works**
 
 Dagu is a single command line tool that uses the local file system to store data, so no database management system or cloud service is required. DAGs are defined in a declarative YAML format, and existing programs can be used without modification.