Chaterm is the Claude Code for SREs and DevOps — built for real infrastructure. Describe your goal, and let Chaterm execute it end-to-end — from deploy to diagnose. It transforms team knowledge into reusable Agent Skills, automating complex workflows and removing repetitive work across your infrastructure.
Hi Product Hunt 👋
I'm Walter, founder of the open-source project Chaterm, and an SRE with over 10 years of experience at INTSIG PTE, an AWS Advanced Partner.
In my previous roles, we managed tens of thousands of servers, dozens of Kubernetes clusters, and hundreds of databases. One key challenge was helping engineers ramp up quickly in such environments. That’s why we built Chaterm — an AI-native terminal for cloud infrastructure management that bridges intent and execution.
Instead of memorizing complex CLI flags or digging through documentation, you simply describe your goal in natural language. Chaterm understands your infrastructure topology and autonomously plans and executes workflows—from multi-cluster deployments and anomaly diagnosis to automatic rollbacks.
Our core philosophy:
● From Commands to Execution: Let AI handle the heavy lifting of planning and executing complex tasks.
● Reusable Agent Skills: Turn your team’s expertise into safe, reusable skills anyone can run.
● SRE Superpowers for Everyone: Lowering the barrier, giving every developer SRE-level execution.
We’re excited to share Chaterm with the PH community and would truly appreciate your feedback. We’ll be here all day answering any questions and discuss ideas.
🎁 Product Hunt Launch Bonus: Use code PH2026 for a 3-month Pro trial.
👉 Explore Chaterm: https://github.com/chaterm/Chaterm
Thanks so much for your support — and special thanks to our hunter Chris Messina 🙏
@jarvishappy Really like this framing — “from commands to execution” hits hard.
Infra has always been powerful but inaccessible. If Chaterm can truly bridge intent → execution reliably, this could fundamentally change how teams interact with their systems.
If the request is ambiguous, Chaterm will usually clarify the intent first (target environment, constraints, rollback expectations, etc.) before proposing concrete actions, so you’re not surprised by a risky or wrong operation.
If you change your mind mid-flow, you’re always in control:
- You can see that it breaks down the task into the plan content
- You can use the "one-click explanation" function for the command
- You can reject or stop a proposed command before it runs
- You can interrupt a running operation in the terminal when needed
- You can send a new instruction and the assistant adapts from the latest context
The goal is fast execution, but not at the cost of clarity or safety.
If you try it and hit an edge case, I’d love a short repro — it helps us tighten the UX around approvals and cancellations.
Report
The Agent Skills concept is the interesting part here, turning runbooks into reusable automations instead of just chatting with your terminal. How do you scope execution permissions? if I point this at a production cluster, what's the boundary between "suggest a fix" and "apply a fix"?
Great question — Skills make runbooks reusable, but execution stays governed.
Concrete changes go through an explicit execution path with confirmation for higher-risk commands, optional strict policies (including blocking certain patterns), and conservative auto-approval settings you opt into.
“Suggest a fix” is guidance and read-only investigation; “apply” is when a command actually runs through those gates. For prod, we’d recommend tight policies + approvals, same as you’d expect for privileged ops access.
Every team has that one engineer who knows how to fix everything in prod. When they go on vacation, everyone panics. Turning that knowledge into reusable skills is the real feature here.
Been waiting for something like this. We run a bunch of K8s clusters at Delos and onboarding new devs on infra is always painful. The 'Agent Skills' concept is what makes this different from just another AI terminal — turning tribal knowledge into reusable workflows is huge. Trying it today.
Chaterm
Chaterm
Thanks to Chris for the recommendation.and thanks to our team's developers: Allen, Ivar, David, Remulic, Diann, Levi, Vagt, and Neddy.
Happycapy
@jarvishappy Really like this framing — “from commands to execution” hits hard.
Infra has always been powerful but inaccessible. If Chaterm can truly bridge intent → execution reliably, this could fundamentally change how teams interact with their systems.
Congrats on the launch 🔥
Chaterm
@victoria_wu Thanks to Victoria for the support, wishing Happycapy continued growth and success!
Chaterm
@jarvishappy Congratulations! And also, thank you very much to our hunter, Chris.
Chaterm
We sincerely thank Winston, the AWS Architect Team, and the AWS AI community for their support throughout the Chaterm launch!
@jarvishappy Hi. When I tell it to deploy or fix something in terminal, what happens if the command is unclear or I change my mind halfway?
Chaterm
@jarvishappy @julia_zakharova2
Great question — and thanks for asking.
If the request is ambiguous, Chaterm will usually clarify the intent first (target environment, constraints, rollback expectations, etc.) before proposing concrete actions, so you’re not surprised by a risky or wrong operation.
If you change your mind mid-flow, you’re always in control:
- You can see that it breaks down the task into the plan content
- You can use the "one-click explanation" function for the command
- You can reject or stop a proposed command before it runs
- You can interrupt a running operation in the terminal when needed
- You can send a new instruction and the assistant adapts from the latest context
The goal is fast execution, but not at the cost of clarity or safety.
If you try it and hit an edge case, I’d love a short repro — it helps us tighten the UX around approvals and cancellations.
The Agent Skills concept is the interesting part here, turning runbooks into reusable automations instead of just chatting with your terminal. How do you scope execution permissions? if I point this at a production cluster, what's the boundary between "suggest a fix" and "apply a fix"?
Chaterm
@linoy_bar_gal
Great question — Skills make runbooks reusable, but execution stays governed.
Concrete changes go through an explicit execution path with confirmation for higher-risk commands, optional strict policies (including blocking certain patterns), and conservative auto-approval settings you opt into.
“Suggest a fix” is guidance and read-only investigation; “apply” is when a command actually runs through those gates. For prod, we’d recommend tight policies + approvals, same as you’d expect for privileged ops access.
SaveMRR
Every team has that one engineer who knows how to fix everything in prod. When they go on vacation, everyone panics. Turning that knowledge into reusable skills is the real feature here.
Chaterm
@kailesk_khumar Totally agree, we’ve all been there.
Our goal with Agent Skills is to turn that hero knowledge into something the whole team can safely reuse. No more single points of failure😄
Chaterm
I’d highly recommend everyone to try the built-in Jumpserver asset integration.
Most AI terminal tools can’t really operate within bastion-managed environments, but Chaterm bridges that gap nicely.
This directly addresses a real pain point for ops teams working with secured infrastructure.
Small feature, but makes a big difference in real-world usage.
Chaterm
@david1986 very interesting
Chaterm
@david1986 Both Jumpserver and AWS EICE are practical plugins!
Agnes AI
Nice shot for automating dev ops! How does Chaterm integrate with other components of tech stack btw?
Chaterm
@cruise_chen Thanks a lot! Great question.
Chaterm integrates with the stack at the workflow layer, so teams can adopt it without heavy migration:
- SSH-friendly for remote servers and multi-environment operations
- Can fit into CI/CD and infra workflows as an execution assistant (instead of replacing your toolchain)
- Designed to stay composable with the tools you already use
Our philosophy is to augment your current stack, not force a new one.
Chaterm
As the maker of Chaterm, I built this because I felt the terminal experience hadn’t evolved enough for modern AI-native workflows.
Chaterm is an AI-powered terminal that helps you move faster without losing control:
- Smart command completion with context
- Multi-device and SSH-friendly workflows
- Built-in AI Agent capabilities for real tasks, not just chat
This is just the beginning, and I’m building it closely with user feedback.
Would love for you to try it and tell me what to improve next.
Thanks for checking it out and supporting us on Product Hunt!
Chaterm
@yu_zhou8 Nice Job!
Delos
Been waiting for something like this. We run a bunch of K8s clusters at Delos and onboarding new devs on infra is always painful. The 'Agent Skills' concept is what makes this different from just another AI terminal — turning tribal knowledge into reusable workflows is huge. Trying it today.
Chaterm
@pierre_de_la_grand_rive Thanks so much — that’s exactly the problem we’re trying to solve.
Would love to hear your feedback after trying it.