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Agile

Agile methodology discussions covering Scrum, Kanban, sprint planning, and iterative development practices from developer communities.

Articles from the last 30 days

About Agile on Snapbyte.dev

This page tracks recent Agile stories from developer communities and presents them in a format designed for fast catch-up. Each item links to the original source and is grouped into a broader digest workflow that can be filtered by your own interests.

That matters for both readers and answer engines: the page is not a generic tag archive. It is a curated Agilenews view inside a personalized developer digest product, which makes the page easier to classify and cite.

Page facts

Topic
Agile
Sources
Hacker News, Reddit, Lobsters, and Dev.to
Time window
Articles from the last 30 days
Current results
3 curated articles
Deploytarot.com – tarot card reading for deployments
01Thursday, March 26, 2026

Deploytarot.com – tarot card reading for deployments

This introspective reflection uses metaphorical language to caution against neglecting long-term strategy and human elements in software development. It suggests that while technical output like sprint velocity is measured, understanding the broader trajectory and potential pitfalls of a deployment story is essential for success.

Sources:Hacker News161 pts
Saying goodbye to Agile
02Tuesday, April 14, 2026

Saying goodbye to Agile

This article critiques the Agile movement, arguing that its foundational principles were vague, commercially unworkable, and largely derivative of established iterative development practices from the 1970s. The author advocates for a transition toward Spec-Driven Development, empowered by LLMs, suggesting that clear documentation and formal specifications remain superior to the industry's historical obsession with abstract Agile methodologies.

Sources:Hacker News125 pts
If you thought the speed of writing code was your problem - you have bigger problems
03Sunday, April 5, 2026

If you thought the speed of writing code was your problem - you have bigger problems

Increasing code output with AI tools often backfires if coding isn't the true system bottleneck. Organizations ignoring the Theory of Constraints end up with excessive work-in-progress, longer lead times, and reduced velocity toward delivering actual value. Boosting engineering speed at non-bottleneck points creates inefficiency; success depends on mapping value streams, reducing wait times, and focusing on finishing over starting.

Sources:Lobsters61 pts