I’m always on the lookout for tools that let me and my team stay in the terminal and cut down on context-switching. That’s why the ForgeCode CLI coding agent (often just called “Forge”) has become a game-changer for my team. It’s an AI-powered assistant that lives in the shell and helps automate everything from CI/CD scripting to debugging and deployment.
Forge integrates seamlessly with my CLI tools and even lets me mix and match models or use self-hosted AI (so enterprise teams get “complete control” over their data). In this post I’ll walk through 10 specific DevOps workflows I’ve sped up by asking Forge to do the grunt work. Let’s dive in and see what this AI shell can do!
1. Automating CI/CD Pipelines and Configs
Rather than manually writing complex CI/CD YAML or pipeline scripts, I simply describe what I need and let Forge draft it. For example, I once fed Forge a legacy GitHub Actions workflow and asked it to explain each step. In seconds it “parsed the config and output a human-readable summary of each job”. That meant I quickly understood a tricky build pipeline without poring through docs. Similarly, you can prompt Forge to generate or modify your pipeline config: e.g. “create a Jenkinsfile that runs tests and deploys to staging.” It will scaffold the boilerplate so you can tweak the details. This keeps our delivery pipeline airtight and saves hours of YAML debugging.
2. Accelerating Infrastructure-as-Code
Setting up servers, networking, or cloud resources via IaC is tedious – but Forge can help. I often describe the desired infrastructure in plain English (e.g. “Spin up an AWS EC2 instance with Docker installed and expose port 80”), and Forge will draft the Terraform/CloudFormation script or shell commands for it. This means spinning up or updating our cloud environment becomes much faster and consistent. While this is a general DevOps pattern (Terraform is built for it), having Forge handle the initial IaC template saves me from manual typos and lets me focus on reviewing the logic.
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3. Containerization & Deployment Manifests
When I need a Dockerfile or Kubernetes manifest, I just describe it to Forge. For instance, I asked Forge to fix a failing Docker build with a permission error, and it immediately spotted that files were being created as root and suggested adding a chown or switching to a non-root user – exactly the real fix we needed. Beyond fixes, Forge can draft new container files from a prompt (“generate a Dockerfile for a Node.js app”), including the right base image and commands. The same goes for K8s: ask it for a deployment YAML for your service, and it will write a working template. This turbocharges our container workflows by automating boilerplate and catching common mistakes.
4. Automated Testing & QA
Writing unit tests and end-to-end tests by hand eats up time. Instead, I let Forge be my test engineer. After coding a function, I open it in the terminal and say: “Forge, generate a set of Jest unit tests for this function, covering edge cases.” Forge then “returns a comprehensive test suite” with normal cases and failure scenarios, even commenting the assertions. I just copy the snippet into a *.test.js file and run it. For example, it generated full Jest tests for a calculateShippingCost(order) function in a few seconds. This automation instantly ramps up our coverage without manual effort. It’s amazing to see Forge crank out dozens of assertions that would otherwise take me ages to write.
5. Documentation & Knowledge Transfer
Forge isn’t just for code – it’s a built-in technical writer. Need docstrings or READMEs? I point Forge at a tricky algorithm and ask it to “document this function in detail.” It produces clear doc comments or Markdown docs on the spot. In one case, I showed Forge a CI pipeline YAML and asked “explain this pipeline step by step.” It “parsed the config and output a human-readable summary of each job”. This is invaluable for onboarding and reviews: new team members can get up to speed by asking Forge to explain any file or config. No more guessing what that cryptic script does – Forge will paraphrase it in plain English for you.
6. System Architecture & Planning
On a higher level, Forge doubles as an architecture assistant. I simply describe a system or requirements in natural language, and Forge proposes a design. For example, I prompted: “Propose a scalable microservices architecture for an e-commerce order processing system.” Forge then reviewed our project structure and suggested splitting order intake, payment, and shipping into separate containers with a message queue between, plus the right database model. It even sketched out a sample DB schema. This kind of AI-driven brainstorming helped avoid weeks of indecision – I could iterate on architecture ideas with the agent in seconds. It’s like having an experienced solutions architect in the terminal.
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7. Code Understanding & Onboarding
When diving into unfamiliar repos, I treat Forge as my personal mentor. Just last week I asked it to “explain how the authentication system works in this codebase,” and Forge parsed multiple files (middleware, models, controllers) to describe the end-to-end login-to-JWT flow and key modules. It even pointed out where tokens were verified. This saved me from tracing code manually. We use this tactic often: any time someone on the team wonders “What does this function/endpoint do?”, we fire up Forge. It scans the context and delivers a quick summary, which is a huge time-saver during reviews or when handing off features to other engineers.
8. Feature Scaffolding & Implementation
Building new features becomes dramatically faster with Forge. I just describe the feature in natural language and let it scaffold the code. For instance, to add a theme toggle in our React app I typed: “Implement a dark mode toggle in our React application.” Forge came back with a step-by-step plan – update global stylesheet, add a toggle component, configure CSS variables – and even provided example JSX for the button. I then asked it to “write the React component,” and it churned out clean code with comments. It even knew to store the preference in localStorage. It’s like having a seasoned teammate draft boilerplate, so I can focus on fine-tuning the logic.
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9. Troubleshooting & Debugging
Forge shines as a first-pass troubleshooter for environment and deployment issues. Whenever our CI/CD jobs break or a server misbehaves, I paste the error or describe the situation. For example, when a Docker build failed with a generic “permission denied” error, I asked Forge for help. It analyzed the problem and realized we were creating files as root without chown, then suggested the exact fix (use chown or run as non-root). Similarly, it caught a missing .env copy in our Dockerfile that was causing production errors. In general, I treat Forge as my AI debugger: it has “helped troubleshoot environment and deployment problems” by surfacing root causes whenever we prompt it. This saves us from long blind hunts in logs and configs.
10. GitOps & Release Automation
Even version control and release tasks get faster with Forge. It can guide merges, write commit messages, and draft release notes. I’ve had it resolve branch conflicts by running, for example, “Merge branch 'feature/login' into 'main' and resolve conflicts.” Forge scanned the diff and interactively suggested how to reconcile differences, even auto-editing conflict markers. It noted schema changes and recommended keeping the latest version – very handy. We also use custom Forge commands (like /commit) to auto-generate conventional commit messages (“feat(login): add remember-me checkbox”), and we ask it to summarize our Git history into a changelog draft. In short, any time I’m juggling branches or writing a release note, Forge smooths out the process and cuts down manual writing.
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Conclusion
In all these cases, ForgeCode’s CLI agent has literally become my most-used dev tool. It keeps me in the terminal (no GUI context switches) and acts like an AI pair programmer that boosts our productivity. For busy enterprise teams, that means routine DevOps tasks are faster, smarter, and less error-prone.
If you’re an enterprise developer ready to supercharge your workflow, give ForgeCode CLI a try. Install it in a few commands (e.g. npm i -g @antinomyhq/forge), connect your AI model key, and start asking it to handle your next DevOps chore – from “fix this bug” to “generate tests” to “draft this script.” You’ll be amazed how much grunt work it can automate. Go ahead and try it now – your next deployment (and your team) will thank you!.
Top comments (8)
Thanks for this! It's still on my list - I've just been insanely busy! So, I have a question for you since you've been working with it for awhile now: do you think Forge could work as part of a GitHub Actions workflow? What would that look like?
Thanks for reading Ashley, forgecode supports git operations...for instance if you ask this > I need to merge branch 'feature/user-profile' into main but there are conflicts then it will assist you in that
Think bigger 😉 Because Coding Agent can execute an entire story in the GHA VM but there's no good solution for CLI (at least, not yet), which makes automation difficult. So, I host an internal version of Forge, make it accessible via whatever proxy magic that team does (not at all my strong suit!): if I assign it a story, could it execute, test, document, commit, push, and open a PR from that workflow without manual intervention?
Absolutely, that's the vision! ForgeCode already handles story execution, testing, docs, commits, and PRs from the CLI. Your setup sounds spot on, once it’s wired to your proxy, it should run full workflows with minimal touch. Full automation from terminal FTW....
That’s exactly what I like to hear 🥰 I did a little digging on the GitHub side too, and it looks like they’ve mostly pivoted away from the CLI in favor of using Models to generate workflows instead. If you end up exploring that route, definitely keep me in the loop! I’ll do the same once I get a breather and can finally give Forge a spin 🛠️✨
Sure Ashley...!!!
Looks great!! Sharing this with my team.
Thanks Tom, appreciate it!!