February 21, 2026
Sprint planning? Sprint to the comments!
The Software Development Lifecycle Is Dead
AI killed the old way to build software, say some — others call it fantasy
TLDR: A viral essay says AI coding agents squash the old step-by-step software process into one fast loop. The comments are split: some cheer ditching meetings, others call it hype, ask who sets goals, and point out that today’s code still needs reviews, version control, and human judgment.
The internet is fighting over a bold claim: that the old step-by-step way of making apps is dead, and AI “agents” now mash every stage into one messy-but-fast loop. In the piece, the author says newbies skip meetings, tickets, and reviews and just ship. Cue the fireworks. One camp loved it. A top comment cheered that real “agentic” work doesn’t speed up the old process — it “throws huge chunks of it in the trash.” Fans imagine pouring one out for Jira (the task-tracking tool) and sprint planning, while agents crank out versions on command.
Then the backlash hit. Long-timers argued the article built a strawman: “frozen specs” and perfect code have rarely been real life. A product manager type asked the killer question: if agents just build, who decides what to build — who talks to customers, reads rules, sets strategy? Another skeptic said none of this is true today: code still breaks, version control is real, and hype is getting “religious.” The spiciest jab? Someone said the article itself “reads like AI wrote it.” The verdict: half pep rally, half eye roll — with jokes about SDLC obituaries and a very lively comments section deciding what’s actually dead: old workflows or our grip on reality.
Key Points
- •The article claims AI coding agents collapse traditional SDLC stages into a single iterative process centered on intent and context.
- •It asserts that ‘AI-native’ engineers skip ceremonies like sprint planning, estimation, lengthy PR reviews, and focus on rapid build–iterate cycles.
- •Requirements are portrayed as evolving artifacts produced through iteration rather than fixed inputs defined before implementation.
- •Traditional project/ticketing systems (e.g., Jira) are described as ill-suited for agent workflows, functioning poorly as context stores for models.
- •System design is presented as discovered in real time with agent collaboration, narrowing the gap between architecture and working code.