Parents always stay in control: they give approval and set their own limits. Not the right moment yet? Then you can simply choose not to enable BUUT Pay.
On to the financially strongest generation ever!
New: BUUT Pay!
My team and I had worked so hard on this ground breaking feature.
Starting today, you can pay with your phone at @buut, directly from a jar. Even if you’re under 16. In a world where nearly every young person has a smartphone, contactless payment is the logical next step.
With BUUT Pay, young people can pay safely and easily via their own BUUT wallet, within a fully regulated banking environment. 🧵
Do you know you can have shared custom AI agent across all your github repos? Even for individual subscriptions?
Create a private .github-private repo, drop your Copilot custom agents in agents/, and they're available across all your personal repositories. One place to maintain them, zero duplication.
Full write-up on how to set it up (and why to keep it private 🔒): 👉 https://shinglyu.com/blog/2026/05/28/github-private-repo-personal-copilot-agents.html
In my latest post, I break down the configuration and the specific pitfalls I encountered—from firewall allowlists to the nuances of the runs-on label and permission requirements.
Check it out here: https://shinglyu.com/blog/2026/04/20/copilot-cloud-agent-custom-runner-aws-codebuild.html
Want to run GitHub Copilot Cloud Agents entirely within your own AWS VPC?
I’ve been experimenting with using AWS CodeBuild as a self-hosted runner for Copilot, allowing for a fully remote "vibe coding" setup. It's a great way to handle issue implementation in the background, but the setup has a few "sharp corners" you need to watch out for.
If you aren't looking into GitHub Agentic Workflows yet, you’re already behind the curve on the next evolution of CI/CD.
Read the full breakdown here: https://shinglyu.com/blog/2026/04/15/automating-weekly-research-with-github-agentic-workflows.html
#GitHub #GitHubAgenticWorkflows #AI #Automation #SoftwareArchitecture #DevOps
Instead of jumping between different AI tools and UIs, I’ve moved my entire weekly tech deep-dive into code and GitHub Actions. It’s automated, it’s headless, and it lives exactly where my work does.
In my latest post, I break down:
- Why I’m ditching UI-based AI tools for a code-first approach.
- How to orchestrate deep research directly within your repo.
- My exact setup for tracking AWS, AI trends, and Software Architecture updates on autopilot.
Most people are still trying to automate their lives through clunky web dashboards and "no-code" interfaces. But as developers, we know that if it isn’t in code and version-controlled, it’s a nightmare to maintain.
I’ve spent the last few weeks diving into GitHub Agentic Workflows, and it’s a total game-changer for how we handle agentic automation.
You get automation without blindly trusting a model with your numbers. Write the import rules once, and everything stays deterministic and auditable after that.
If you want more control over their financial data without paying for yet another SaaS tool, this might be the workflow you've been looking for.
Full post: https://shinglyu.com/blog/2026/03/18/hledger-and-ai.html
