Tools like Userdoc (https://userdoc.fyi) help in a few ways, you can easily create requirements (stories, personas, journeys, test cases), but also reverse engineer existing source code into detailed docs, then ask natural language questions etc. AI helps us plan our product in Userdoc, and our devs connect via MCP to bring those requirements directly in to Cursor (full disclaimer, I work at Userdoc - but we eat... - Source: Hacker News / about 1 year ago

Userdoc has versioning of stories and acceptance criteria, aimed to at helping this exact issue https://userdoc.fyi (transparency: I’m the founder). - Source: Hacker News / over 1 year ago

I'm interested to hear how other people are using tools to help them, we've been playing with userdoc.fyi and having good success, but there are just so many AI related tools I feel like I can't keep up! Source: about 3 years ago

Great read, I spent years thinking requirements should live somewhere like Jira, and I feel for many teams this is the case. But as the author mentions, Jira contains tasks related to bugs, text changes, colour changes etc.. These are not product requirements per se. Like the author, I came to the conclusion requirements are best kept in a requirements management system, that integrates with your project... - Source: Hacker News / about 3 years ago

I built Userdoc (https://userdoc.fyi) a requirements management system for software projects. After running a development consultancy for 8 years, I wanted a dedicated system for gathering and confirming requirements, and only syncing them with project management tools like Jira when they are ready (but keeping them in Userdoc as the living documentation and source of truth. Things are going well, we have some... - Source: Hacker News / about 3 years ago

Speed matters. Not speed in sprint or linear dashboards. Not speed in story points. - Source: dev.to / about 1 month ago

Model Context Protocol, for context, is the emerging standard for letting AI agents pull live data from external systems without custom integration code. Freshworks has implemented it as a native layer in Freddy AI, which means agents can now reach into Notion, ClickUp, Linear, Workday, Rippling, and the rest of the enterprise stack — not through brittle webhooks or bespoke connectors, but through a standardized... - Source: dev.to / about 2 months ago

Issue trackers: GitHub Issues, Linear, or Jira work well because technical debt records live in the same tool as feature work. This makes them easier to pull into sprint planning and keeps the debt backlog visible alongside the feature backlog. The main risk is that debt issues get buried under feature issues without careful labeling and triage discipline. - Source: dev.to / about 2 months ago

Linear and similar tools can track velocity metrics per area of the codebase over time, making the before/after comparison straightforward to document. - Source: dev.to / about 2 months ago

Most engineers fail salary negotiations because they use vague statements like "I work hard" or "I’m a good teammate" instead of quantified, verifiable impact. After 15 years of negotiating offers, I’ve found that engineers who tie their ask to concrete business outcomes land 30% higher offers than those who don’t. For example, instead of saying "I improved the API", say "I reduced API p99 latency by 400ms, which... - Source: dev.to / about 2 months ago