How I Earned $700 in AWS Credits as an AWS Community Builder

A. S. Md. Ferdousul Haque — Mon, 02 Nov 2026 15:55:22 +0000

I got $700 worth of AWS credits to play and learn across the AWS ecosystem, and you can follow the same path. Here's how.

TL;DR: Where the $700 comes from

Source	Credits
AWS Community Builders Program	$500
New AWS account bonus	$100
"Explore AWS" tasks (5 × $20)	up to $100
Total	up to $700

Step 1: Join the AWS Community Builders Program

The program opens for applications once a year, usually around November/December. To get in:

Join the waitlist and submit your interest.
Share your engaging posts and community contributions, since these are what get you noticed.

Benefits include:

✨ $500 in AWS credits for your projects
✨ Exclusive sessions with AWS product teams
✨ 50% discount on AWS re:Invent tickets
✨ One year of free CloudAcademy access
✨ A free AWS certification of your choice
✨ A global network of 3,000+ AWS experts

Apply here:

📌 Join the waitlist
📌 Program details

Step 2: Get into the Builders portal and Slack

Once you're selected, you get access to the AWS Builders portal and the Community Builders Slack workspace. The Slack is active and worth joining for its own sake. Members post new things constantly, and you hear about upcoming AWS products before they launch.

Step 3: Claim your $500 credits

Watch the #cb-announcements Slack channel. When the time comes, the team posts a link to claim your $500 in AWS credits.

⚠️ Heads up: every member gets a unique credit link. Don't share it, and don't redeem it on a company account.

Step 4: Create your AWS account (+$100)

Use your personal credit link to create an account in the AWS Console.

You'll need an international credit card. AWS usually makes a $1 charge to verify the card, then refunds it.
As a first-year user, AWS gives you $100 in credits to experiment with.

Running total: $600

Step 5: Complete the "Explore AWS" tasks (+$100)

After sign-up, the console shows a new Explore AWS section covering popular services such as EC2, Serverless, RDS, Bedrock and Cost Alerts. Each task you complete earns $20, and with five tasks you can earn up to $100.

I've completed 4 of 5, which is $80 so far.

Step 6: Check your Billing page

Open the Billing page to see a full breakdown of every credit and where it came from.

Wrap-up

That's how you can reach $700 in credits in your first year as an AWS Community Builder. That's plenty of room to build, break and learn on AWS without worrying about the bill.

If you apply, I'd love to hear how it goes. Drop a comment below, and follow me for more AWS content. 🚀

Program terms and credit amounts can change, so check the official AWS Community Builders pages for the latest details.

Opencode for Agentic Development with Local LLMs

A. S. Md. Ferdousul Haque — Sun, 23 Nov 2025 12:48:22 +0000

Agentic development is rapidly transforming the way developers design, build, and ship software. Tools like Opencode let developers pair powerful local LLMs with intelligent agents to automate coding tasks, refactor large codebases, and accelerate development—all while keeping data private and within your own machine.

If you want to get started with Opencode using local LLMs (like Llama, Mistral, Qwen, DeepSeek, Gemma), here’s a simple, practical guide. before that, let's know

Why OpenCode?

Agentic workflows – AI agents that can modify your codebase intelligently.
Local-first development – Integrate your own LLM running on GPU or CPU.
Extensibility – Bring your own models, tools, and workflows.
Security & Privacy – No proprietary code leaves your machine.

Pre-requisites:

Ollama
GhostTTY
Opencode

Install and Run a Local LLM

Go to Ollama and follow the steps to install on your OS
Add the desired LLM that supports agentic flow e.g. qwen3:8B, llama3.1:8b and so on. Check on ollama site.
Run the following to install Qwen LLM to your local environment

ollama pull qwen3:8b
ollama list
ollama run qwen3:8b

Now add the following tweaking to increase context window for agents to work properly.

ollama run <model_name>
>>> /set parameter num_ctx 32768
>>> /save <model_name>

Install Ghostty

There are several TTY supported with opencode, I prefer ghostty which is very simple at the same time good UIUX. Follow instructions on Ghostty to install.

Install OpenCode

Follow instructions on OpenCode to install.

Configuration

Once the pre-requisite steps are done. Now comes the execution part. First we need to add the LLM to the OpenCode config opencode.json file located at .config/opencode/opencode.json to work on.

For more providers of opencode check here

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "ollama": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Ollama (local)",
      "options": {
        "baseURL": "http://localhost:11434/v1"
      },
      "models": {
        "qwen3:8b": {
          "name": "qwen3:8b"
        }
      }
    }
  }
}

Once this is done, opencode is ready for action.

Execution

Now let's build something. Follow the steps:

Open the ghostty terminal
Create a directory for the application
Run opencode inside the directory

Select the model from /models

By using TAB of keyboard select the BUILD AGENT mode
Give prompt for generating the code for new features or fix a bug in the application

Final Product

I just build a tic-tac-toe game using the local LLM, although my CPUs are burning now 🔥 Play here

Benefits of Using Local LLMs

Zero data leakage across the internet
Better cost efficiency—no API billing
Unlimited customization of models
Offline development
Faster iteration with GPU acceleration

Setting up Opencode with a local LLM unlocks a powerful, private, and fully autonomous coding partner. Whether you're building services, refactoring monoliths, or improving developer productivity, agentic development gives you a major edge.

If you're working with large codebases or exploring AI-powered software engineering, this setup is one of the best ways to get started.

DEV Community: A. S. Md. Ferdousul Haque