The Agile Industrial Complex Is Dead—AI Killed It

Let me be clear: the Agile Industrial Complex—that bloated mess of process consultants that couldn't code, certifications, and tool vendors that turned a simple idea into a bureaucratic nightmare—is on its last legs. And AI is the one pulling the trigger. For years, we’ve been drowning in pointless meetings, endless backlog grooming, and rigid processes that slow us down more than they help us ship software. But now, AI is tearing through all of that, and I say it’s about damn time.

Back in 2019, when I started HipSpec, my thesis was that teams were wasting their time sitting around in meetings, writing backlog stories when they should be building. That thesis rings truer than ever today. Tools like Claude, ChatGPT, Grok, and Gemini when paired with new IDE's like Curor and Windsurf and MCP's into your other tools can run circles around the clunky processes we’ve been stuck with.

Soon, Agents will generate code, prioritize tasks, and even manage backlogs—without the need for hours of "sprint planning" or "story pointing." If you’re still clinging to two-week sprints, you’re already behind. Lets be clear - soon, agents will be making Pull Requests into code bases for bugs reported to customer service before a developer lays eyes on the problem.

I’m betting on multiple production deployments a week, feature flags, and teams that move fast because they aren’t bogged down by ceremony.

AI Is Eating the Agile Playbook

The Agile Manifesto was never meant to be a cash cow. It was about simplicity—individuals and interactions over processes and tools. But somewhere along the way, it got hijacked. Now, we’ve got "enterprise Agile" frameworks that are anything but agile. They’re slow, they’re expensive, and they’re killing innovation.

AI is the antidote. It’s not just automating the grunt work; it’s fundamentally changing how I think we should build software. Tools like Windsurf and Cursor, AI-powered IDEs, are making developers more productive than ever. I would argue these tools understand your codebase better than most humans do. I can ask them to refactor, write tests, or even explain complex logic in plain English. Compare that to the old way: endless meetings to debate whether a task is a "3" or a "5" in story points. It’s laughable.

Then there’s the Model Context Protocol (MCP), which is like APIs for AI agents. It lets AI tools talk directly to your project management software—Linear, Asana, whatever you use. Need to create a bug ticket? I just say, "Hey AI, make a ticket for that login issue," and it’s done (Linear MCP Server). No more manual entry, no more backlog grooming sessions. It’s automation at the speed of thought.

High Agency Teams Will Dominate

Here’s the hard truth: not every team is going to survive this shift. If your engineers are sitting around waiting for a Scrum Master to spoon-feed them requirements, they’re toast. Low agency teams—those that need to be led by the hand—are going to fall behind. Fast.

But high agency teams? They’re going to thrive. These are the teams I see embracing AI, automating the boring stuff, and focusing on solving real problems. They’ll be demand-constrained, not because there isn’t work to do, but because they’ll burn through tasks so quickly they’ll need to go find new problems to solve. That’s the kind of team I’d want to lead.

Product managers, listen up: your job is changing too. If you think you can keep writing requirements in Word docs or Notion pages and tossing them over the wall to engineering, think again. I believe you need to get technical. Learn markdown, contribute to the repo, and make sure your PRDs are embedded in the code where they belong. If you’re not helping align the documentation with the actual functionality—like ensuring SAML SSO for enterprise users is properly captured—you’re dead weight.

And QA testers? Manual testing is dead. If you’re still running siloed Selenium tests in some separate repo, you’re living in the past. I advocate for upskilling QA testers to prompt automated test suites in the repository, moving away from those siloed Selenium tests. AI can generate test cases, identify bugs, and even write automated tests for you. Your job now is to prompt those AI tools and ensure the tests are integrated directly into the codebase. Anything less, and you’re just slowing things down. Once your QA has backfilled in Repo tests, they should hopefully be upskilled enough to begin contributing to functionality or prompting better documentation for your product.

The Automated Pre-Backlog: Let AI Listen to Your Customers

Here’s something I’m excited about: my concept of an automated pre-backlog, curated by AI, pulling from real customer interactions. Imagine AI analyzing sales calls, support tickets, and user feedback to identify patterns—like recurring login issues or feature requests—and automatically creating tasks in your project management tool. No more guesswork, no more "let’s ask the PM what to build next." The AI does the heavy lifting, surfacing what matters most to your users.

This isn’t just a nice-to-have; it’s a game-changer. It ensures that your development team is always working on the highest-impact tasks, directly aligned with customer needs. And with MCP, those tasks can flow seamlessly into your backlog, ready for the team to tackle. It’s the ultimate feedback loop, and I think it’s going to make product-market fit a lot less elusive.

The Two-Week Sprint Is Dead—And Good Riddance

Let’s kill the two-week sprint while we’re at it. In a world where AI can help you deploy weekly—or even daily—there’s no reason to stick to arbitrary cycles. Feature flags let you ship continuously and turn on functionality when it’s ready, not when the sprint ends. Customers are going to demand this pace. If you’re still doing quarterly updates, you’re wearing a scarlet letter of staleness. Your competitors will eat you alive.

I’m all in on Kanban: simple, flexible, and focused on flow. With AI managing the backlog and automating the busywork, your team can focus on what matters—building great software.

The Future Is AI-Driven, Not Process-Driven

The Agile Industrial Complex had its day, but it’s over. AI is here, and it’s not just a tool—it’s a revolution. Teams that embrace it will move faster, build better products, and leave the laggards in the dust. If you’re a leader, I say your job is to upskill your team, integrate AI into your workflows, and get out of the way.

For greenfield projects, I’d optimize for AI from the start. Legacy projects? Start by automating your tests and backlog management. The SWE benchmark (SWE Bench) is a good directional indicator of where AI is heading—use it to gauge your progress.

In short: I believe the future of software development is AI-driven, not process-driven. The Agile Industrial Complex is dead. Long live AI.

Hat tip to @DHH, emulating his style a bit in this one. Find him here - https://x.com/dhh

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