I’m Yuval, and for the past several years I’ve been building dev tools (some of you might know Amplication). Over that time, we’ve all seen the rise of AI copilots and agents. They are useful for individuals in the IDE, but limited when it comes to how teams actually ship software. I believe the next step is moving beyond copilots into *autonomous, continuous AI* that runs inside the SDLC itself.
That’s what we’re building with https://overcut.ai/. It connects directly to GitHub, Jira, and other tools, and runs workflows that handle things like:
- Reviewing PRs
- Writing tests
- Generating specs and docs
- Triaging and resolving issues
- Opening and updating PRs automatically
The difference is that instead of manually operated assistants or black box agents, you define the workflows (like CI/CD pipelines, but for AI agents). This makes it transparent and under your control.
We provide several ready-made playbooks, and you can also build your own for anything you can imagine on top of Git and tickets. There are built-in integrations to GitHub, GitLab, Bitbucket, Azure DevOps, and Jira.
Would love to hear your thoughts: what workflows would you want AI to take over, and what would hold you back from trusting something like this?
Prisma’s type-safe database access, powerful query API and migrations were a game-changer for Amplication building our platform and also the code we generate.
Agree with you on that! To my opinion the plugins are the most excising in this version. We are still working on the doc on how to create your own plugins
Hello, Yuval here, founder of Amplication. I’m very excited to share with you what the Amplication team is working on.
Amplication saves engineers from undifferentiated heavy lifting in application development, while helping organizations speed up delivery, and enforcing best practices and standardization across multiple teams and developers.
Amplication accelerates the development of backend applications and microservices with high-quality code generation, streamlining and automating development while solving issues that delay production readiness.
We built Amplication so developers like us could focus on coding the parts that matter rather than get distracted by repetitive tasks and boilerplate code.
Amplication is an open-source platform that lets you easily configure your backend services, by generating a human-readable and editable TypeScript Node.js codebase. The generated code includes everything you need to start writing your business logic.
Amplication continuously generates the code based on changes in the schema and configuration, then pushes the code to a GitHub repository to allow developers to continue off and edit it further based on their needs.
Today's launch of our v1.0 also incorporates a plugin architecture that enables developers to develop their own plugins to implement best practices, code conventions, custom integrations, and virtually anything in the generated code. Developers can use plugins created by Amplication’s core team, by our community, or create their own.
We already have several plugins on our Github plugins repo -https://github.com/amplication/plugins, including support for Kafka, MySQL PostgreSQL, Passport JWT, Passport Basic authentication, and the list is growing.
We can’t wait for you to experience Amplication, please share your thoughts.
I’m Yuval, and for the past several years I’ve been building dev tools (some of you might know Amplication). Over that time, we’ve all seen the rise of AI copilots and agents. They are useful for individuals in the IDE, but limited when it comes to how teams actually ship software. I believe the next step is moving beyond copilots into *autonomous, continuous AI* that runs inside the SDLC itself.
That’s what we’re building with https://overcut.ai/. It connects directly to GitHub, Jira, and other tools, and runs workflows that handle things like:
- Reviewing PRs - Writing tests - Generating specs and docs - Triaging and resolving issues - Opening and updating PRs automatically
The difference is that instead of manually operated assistants or black box agents, you define the workflows (like CI/CD pipelines, but for AI agents). This makes it transparent and under your control.
We provide several ready-made playbooks, and you can also build your own for anything you can imagine on top of Git and tickets. There are built-in integrations to GitHub, GitLab, Bitbucket, Azure DevOps, and Jira.
Would love to hear your thoughts: what workflows would you want AI to take over, and what would hold you back from trusting something like this?
Thanks for reading