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  1. Product Rebels
  2. Making AI Work for Product Teams
Making AI Work for Product Teams

Making AI Work for Product Teams

Product Rebels · Oct 30, 2025

Master AI in product by focusing on user problems, not tech. Adopt a dual strategy for efficiency and growth, and get hands-on to lead.

AI Functions as an Accelerant for Incumbents, Not a Disruptor for Startups

Unlike mobile or internet shifts that created openings for startups, AI is an "accelerating technology." Large companies can integrate it quickly, closing the competitive window for new entrants much faster than in previous platform shifts. The moat is no longer product execution but customer insight.

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Making AI Work for Product Teams

Product Rebels·4 months ago

Designate Rotating "Pilots" and "Passengers" to Manage Team AI Adoption

To avoid chaos in AI exploration, assign roles. Designate one person as the "pilot" to actively drive new tools for a set period. Others act as "passengers"—they are engaged and informed but follow the pilot's lead. This focuses team energy and prevents conflicting efforts.

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Making AI Work for Product Teams

Product Rebels·4 months ago

Strategic AI Adoption Requires a Dual Roadmap for Productivity and Growth

Treat AI initiatives as two separate strategic pillars. Create one roadmap focused on internal efficiency gains and cost reduction (productivity). Maintain a separate roadmap for developing new, revenue-generating customer experiences (growth). This prevents conflating internal tools with external products.

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Making AI Work for Product Teams

Product Rebels·4 months ago

Frame Your Product's Unique Data and Functionality as Superpowers for AI Agents

Instead of simply adding AI features, treat your AI as the product's most important user. Your unique data, content, and existing functionalities are "superpowers" that differentiate your AI from generic models, creating a durable competitive advantage. This leverages proprietary assets.

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Making AI Work for Product Teams

Product Rebels·4 months ago

Hands-on Coding with AI Reveals Its Enthusiastic But Repetitive Incompetence

Product leaders must personally engage with AI development. Direct experience reveals unique, non-human failure modes. Unlike a human developer who learns from mistakes, an AI can cheerfully and repeatedly make the same error—a critical insight for managing AI projects and team workflow.

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Making AI Work for Product Teams

Product Rebels·4 months ago

Reframe AI-Impacted Jobs by Shifting Employee Roles From Creation to Curation

When AI automates a core task like content writing, don't eliminate the role. Instead, reframe it to leverage human judgment. A "content writer" can be transformed into a "content curator" who guides, edits, and validates AI-generated output. This shifts the focus from replacement to augmentation.

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Making AI Work for Product Teams

Product Rebels·4 months ago

High-Performing AI Teams Function Like Jazz Bands, Not Assembly Lines

The traditional "assembly line" model of product development (PM -> Design -> Eng) fails with AI. Instead, teams must operate like a "jazz band," where roles are fluid, members "riff" off each other's work, and territorialism is a failure mode. PMs might code and designers might write specs.

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Making AI Work for Product Teams

Product Rebels·4 months ago