Previous State of Things

Over the past decade of building software teams, one recurring frustration stands out: requirement leakage between Business, Design, and Development.

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The traditional product requirements funnel looked like this:

1. Stakeholders Interviews — Business Analyst or Product Manager
2. Business Analysis — Business Analyst or Product Manager
3. Design Specifications — UX Designer
4. Technical Validation — Tech Lead or Software Architect
5. Formal Requirements Breakdown — Project or Product Manager
6. Execution — Tech Team

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This structure had one major advantage: predictability. As long as every party clearly understood and translated the inputs from the step before, the machine moved smoothly.

But that’s a fragile assumption.

Misinterpretations — even minor ones — tend to cascade. And by the time an idea reaches the execution layer, it often bears only a faint resemblance to the original intent.

‍The result? Engineering calories are spent building things that don’t solve the actual business problem. The closer technical teams are to the business, the more accurate — and impactful — the output becomes.

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How AI is changing the paradigm?

By Q1 2025, it’s clear we’ve passed an inflection point.

What used to be speculative (“AI might replace developers”) now feels less far-fetched. Tools like Cursor, Windsurf, and others show just how effectively AI can navigate and generate codebases with high context awareness and precision.

To put it simply, there a way more things which can be generated by AI from with minimum instructions based on the context environment (ChatGPT memory, CodeBase scanning, meta-instructions).

This changes two fundamental dynamics in software development:

1. Fewer engineers are needed for repetitive tasks → Less delegation to mid-tier engineering
2. More time is available for business alignment → Less need for layers of translation and management

Now add to that tools like Claude Sonnet 3.7 or V0 by Vercel, which can scaffold functional UX interfaces without the need for initial design input and you get rid of another layer of the initial requirements funnel.

So at the end if we combine those things together you basically move Tech experts up into the funnel as they need less time and less dependency on other parties to generate immediate feedback loop on business. Entropy goes down, productivity goes up.

The big question is “But will development hours decrease?”Not in the near future. What will change is what those hours are spent on.

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The future of AI-driven Product Teams

While many fear AI will eliminate jobs, something different will happen.

Senior Developers will become more fulfilled, because they’re no longer stuck delivering outputs disconnected from business reality. They will transition into business context and will be more connected to the business.

Instead of fixing misaligned specs or chasing handoffs, engineers are finally working on problems that matter. They’re solving, not translating. We will see the trend of engineers working more on things what matter and less on in-depth troubleshooting.

When AI handles 90% of the coordination scaffolding, teams no longer need fragmented roles to move an idea forward. That reduction in cognitive and process overhead makes room for creativity, agility, and purpose.

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What This Means for Product Teams

• Teams will be leaner, yet more effective
• Developers will be closer to the business, not hidden behind layers
• Iteration will speed up, and with it, innovation
• Entropy — in both communication and process — will be systematically reduced

We’ll spend less time clarifying requirements and more time delivering impact.

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