Readme Updates (#186)

Author: kraftp

README.md

@@ -1,14 +1,14 @@
 
 <div align="center">
 
-# DBOS Transact: Ultra-Lightweight Durable Execution
+# DBOS Transact: A Lightweight Durable Execution Library Built on Postgres
 
 #### [Documentation](https://docs.dbos.dev/) &nbsp;&nbsp;•&nbsp;&nbsp;  [Examples](https://docs.dbos.dev/examples) &nbsp;&nbsp;•&nbsp;&nbsp; [Github](https://github.com/dbos-inc) &nbsp;&nbsp;•&nbsp;&nbsp; [Discord](https://discord.com/invite/jsmC6pXGgX)
 </div>
 
 ---
 
-DBOS Transact is a Python library providing **ultra-lightweight durable execution**.
+DBOS Transact is a Python library for **ultra-lightweight durable execution**.
 For example:
 
 ```python
@@ -28,18 +28,23 @@ def workflow()
 
 Durable execution means your program is **resilient to any failure**.
 If it is ever interrupted or crashes, all your workflows will automatically resume from the last completed step.
-If you want to see durable execution in action, check out [this demo app](https://demo-widget-store.cloud.dbos.dev/) (source code [here](https://github.com/dbos-inc/dbos-demo-apps/tree/main/python/widget-store)).
-No matter how many times you try to crash it, it always resumes from exactly where it left off!
+Durable execution helps solve many common problems:
 
-Under the hood, DBOS Transact works by storing your program's execution state (which workflows are currently executing and which steps they've completed) in a Postgres database.
-So all you need to use it is a Postgres database to connect to&mdash;there's no need for a "workflow server."
-This approach is also incredibly fast, for example [25x faster than AWS Step Functions](https://www.dbos.dev/blog/dbos-vs-aws-step-functions-benchmark).
+- Orchestrating long-running or business-critical workflows so they seamlessly recover from any failure.
+- Running reliable background jobs with no timeouts.
+- Processing incoming events (e.g. from Kafka) exactly once.
+- Running a fault-tolerant distributed task queue.
+- Running a reliable cron scheduler.
+- Operating an AI agent, or anything that connects to an unreliable or non-deterministic API.
 
-Some more cool features include:
+What’s unique about DBOS's implementation of durable execution is that it’s implemented in a **lightweight library** that’s **totally backed by Postgres**.
+To use DBOS, just `pip install` it and annotate your program with DBOS decorators.
+Under the hood, those decorators store your program's execution state (which workflows are currently executing and which steps they've completed) in a Postgres database.
+If your program crashes or is interrupted, they automatically recover its workflows from their stored state.
+So all you need to use DBOS is Postgres&mdash;there are no other dependencies you have to manage, no separate workflow server.
 
-- Scheduled jobs&mdash;run your workflows exactly-once per time interval.
-- Exactly-once event processing&mdash;use workflows to process incoming events (for example, from a Kafka topic) exactly-once.
-- Observability&mdash;all workflows automatically emit [OpenTelemetry](https://opentelemetry.io/) traces.
+One big advantage of this approach is that you can add DBOS to **any** Python application&mdash;**it’s just a library**.
+You can use DBOS to add reliable background jobs or cron scheduling or queues to your app with no external dependencies except Postgres.
 
 ## Getting Started
 
@@ -50,7 +55,7 @@ pip install dbos
 dbos init --config
 ```
 
-Then, try it out with this simple program (requires Postgres):
+Then, try it out with this simple program:
 
 ```python
 from fastapi import FastAPI
@@ -80,14 +85,14 @@ def fastapi_endpoint():
     dbos_workflow()
 ```
 
-Save the program into `main.py`, edit `dbos-config.yaml` to configure your Postgres connection settings, and start it with `fastapi run`.
+Save the program into `main.py` and start it with `fastapi run`.
 Visit `localhost:8000` in your browser to start the workflow.
 When prompted, press `Control + \` to force quit your application.
 It should crash midway through the workflow, having completed step one but not step two.
 Then, restart your app with `fastapi run`.
 It should resume the workflow from where it left off, completing step two without re-executing step one.
 
-To learn how to build more complex workflows, see our [programming guide](https://docs.dbos.dev/python/programming-guide) or [examples](https://docs.dbos.dev/examples).
+To learn how to build more complex workflows, see the [programming guide](https://docs.dbos.dev/python/programming-guide) or [examples](https://docs.dbos.dev/examples).
 
 ## Documentation
 
@@ -98,7 +103,7 @@ To learn how to build more complex workflows, see our [programming guide](https:
 
 - [**AI-Powered Slackbot**](https://docs.dbos.dev/python/examples/rag-slackbot) &mdash; A Slackbot that answers questions about previous Slack conversations, using DBOS to durably orchestrate its RAG pipeline.
 - [**Widget Store**](https://docs.dbos.dev/python/examples/widget-store) &mdash; An online storefront that uses DBOS durable workflows to be resilient to any failure.
-- [**Earthquake Tracker**](https://docs.dbos.dev/python/examples/earthquake-tracker) &mdash; A real-time earthquake dashboard that uses DBOS to stream data from the USGS into Postgres, then visualizes it with Streamlit.
+- [**Scheduled Reminders**](https://docs.dbos.dev/python/examples/scheduled-reminders) &mdash; In just three lines of code, schedule an email to send days, weeks, or months in the future.
 
 More examples [here](https://docs.dbos.dev/examples)!