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
DevOS GitHubNo features have been listed yet.
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This is why eval and observability ship as a unit, not as separate purchases. agent-eval scores and gates the output โ the tiers above, drift, hallucination. AgentLens captures the trace of how the agent got there: every model step and tool call, the resolved inputs, the raw outputs, the trajectory. Two things fall out of that:. - Source: dev.to / 7 days ago
The real fragility is in trying to constrain arguments. The docs are explicit that a pattern like Bash(curl http://github.com/ *) fails to do what it looks like it does. It won't match curl -X GET http://github.com/... (option before the URL), curl https://github.com/... (different protocol), curl -L http://bit.ly/xyz (redirects to GitHub), URL=http://github.com && curl $URL (variable), or curl http://github.com... - Source: dev.to / 8 days ago
Fallback chains โ og:title โ twitter:title โ- SSRF protection โ if you fetch user-supplied URLs, you MUST block
localhost, RFC-1918 ranges, and internal hostnames, or your preview endpoint is a proxy into your own infrastructure- Caching โ you do not want to re-fetch a URL on every render
- Rate limiting โ a public...
- Source: dev.to / 10 days ago
$ git pull Remote: Repository not found. Fatal: repository 'https://github.com//.git/' not found. - Source: dev.to / 12 days ago
// ==UserScript== // @name GitHub -> Obsidian Task // @namespace obsidian // @version 1.0 // @match https://github.com/*/*/issues/* // @match https://github.com/*/*/pull/* // @grant GM_setClipboard // ==/UserScript== (function () { 'use strict'; function getTitle() { return document.querySelector("bdi")?.textContent.trim(); } function copyTask() { ... - Source: dev.to / 14 days ago
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