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DevOS
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DevOS is what happens when you stop thinking of AI as "a tool" and start thinking of it as "an employee." The premise: AI coding agents in 2026 are technically remarkable. Devin can ship features autonomously. Cursor + Claude Code accelerate every senior engineer. Copilot writes half the boilerplate. But every existing AI agent product treats AI as a tool you call โ invoked from an IDE, prompted in a chat, given a one-shot task. That's the wrong frame for how teams actually work. Real teams don't have "tools" โ they have employees. Employees: Have specialized roles (frontend, backend, QA, design, copy, sysadmin) Take tickets off a sprint board Attend standups and report blockers Hand off work to teammates with context Open PRs, get code reviews, respond to comments Have a track record visible across sprints DevOS treats AI agents the same way. Three layers in one product: 1. The marketplace. Browse specialized AI agents by role. Each comes with role-specific prompting, tool integrations, and a track record. Hire as many as your team's working style needs. Agents are configured for their role โ a "frontend dev" agent ships React/Vue with the team's design system patterns; a "copywriter" agent ships marketing pages in your brand voice; a "QA" agent writes Playwright tests and triages bugs. 2. The sprint board. Linear/Jira-style kanban with full agile machinery: sprints, epics, backlog grooming, sprint planning, retrospectives. Agents appear as assignable team members. Drag a ticket onto an agent the same way you'd assign it to a human dev. The agent picks it up, posts an estimate, asks clarifying questions if needed, and starts working. 3. The communication layer. Standups are automated โ every morning agents post what they shipped yesterday, what they're doing today, and what's blocking them. PRs are opened in your real repo. Code reviews happen in real GitHub / GitLab. Slack/Discord/Telegram integration so humans can talk to agents like teammates
Django DevOSNo features have been listed yet.
Based on our record, Django seems to be more popular. It has been mentiond 16 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Use of settings.py as a naming convention follows in Django's footsteps, but alternatively, you can save it to .env and integrate use of python-dotenv to more closely mirror Node. - Source: dev.to / 8 months ago
Let's dive into a quick implementation of this using AWS and Django. We will be using a couple of ideas from the AWS Official Blog. - Source: dev.to / almost 2 years ago
Django is a high-level Python web framework. It is an Model-View-Template(MVT)-based, open-source web application development framework. It was released in 2005. It comes with batteries included. Some popular websites using Django are Instagram, Mozilla, Disqus, Bitbucket, Nextdoor and Clubhouse. - Source: dev.to / almost 4 years ago
This seems like a job for Django. MDN offers a really good tutorial here. To be honest, it would be a massive undertaking so Iโd recommend going for a prebuilt solution like PowerSchool and the like. Source: almost 4 years ago
The first party docs are second to none. Start out with the official tutorial on https://djangoproject.com . Source: about 4 years ago
Ruby on Rails - Ruby on Rails is an open source full-stack web application framework for the Ruby programming...
SRE.ai - AI agents to simplify and automate Salesforce devops
Laravel - A PHP Framework For Web Artisans
Workflos.ai - AI assistant to Find & Manage SaaS with natural language
Flask - a microframework for Python based on Werkzeug, Jinja 2 and good intentions.
y0 - AI agents that code, browse, and build for you
