The Great AI Reorg: New Tools Demand New Roles—Not Just New Tasks

EPISODE 10 • PROCESS OF ELIMINATION

The AI revolution isn’t just changing how we work—it’s reshaping who does what. In this episode of Process of Elimination, Ryan Edwards and Justin unpack why simply adding AI tools to your existing workflow won’t cut it. From shifting job roles to breaking down silos, they explore how real transformation requires not just tools, but organizational redesign. Learn how "trickle-down" strategy must be matched with "tickle-up" feedback, why operating procedures matter more than ever, and how teams can audit their AI readiness in under 10 minutes. This isn’t a reorg—it’s a redefinition.

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Ready to scale this system with your team? This episode isn’t just theory—it’s a practical framework for real transformation.

Whether you're redefining roles, breaking down silos, or building AI into your SOPs, now is the time to design the structure that matches the speed and intelligence of your tools.

If your team is navigating AI adoption without a map, this is where you draw one.

Let’s reimagine how work gets done—with clarity, communication, and culture at the core.

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The Trickle + Tickle Framework™

  • Trickle down

    Leadership provides goals, guidelines, and cultural vision

  • Tickle up

    Teams provide input, feedback, and real-time adaptation

  • Meet in the Middle

    Alignment, ownership, and momentum

What You’ll Learn:

  • Why AI adoption fails when roles and systems stay the same

  • How project managers become agent coordinators and strategists become prompt architects

  • What "trickle down and tickle up" means—and how it unites leadership strategy with ground-level insight

  • Why AI needs structure—especially new SOPs—to thrive

  • How to run a simple but powerful audit (individual, team, and ROI) in under 10 minutes

  • Why the future of AI isn’t about ownership—it’s about facilitation

Best for:

  • Strategy leads, AI implementers, and cross-functional teams ready to scale smarter with systems that work across people, platforms, and priorities.

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Guides & Tools

Episode Glossary

  • A performance measure used to evaluate the efficiency or profitability of an investment. In the context of AI, it refers to the tangible benefits an organization gains from its AI implementation.

  • A diagram that visually represents the structure of an organization, showing the relationships among departments, roles, and individuals. The podcast argues that many org charts are outdated in the AI era.

  • Teams composed of individuals from different departments or functional areas, often formed to tackle complex problems that require diverse perspectives. AI integration benefits from breaking down traditional silos.

  • Detailed, step-by-step instructions compiled by an organization to help workers carry out routine operations. The podcast suggests that AI often exposes pre-existing flaws in SOPs.

Episode FAQ

  • The main challenge is that most organizations try to "bolt-on" AI as a new task without fundamentally rethinking their existing organizational structure, roles, and workflows. This leads to overload, confusion, inefficiency, and ultimately, failed AI rollouts because the "system" (the old org design and SOPs) was already broken, and AI merely exposes those cracks faster. It's like trying to run 2025 tools with 2015 roles.

  • Prompt Strategist: Shapes questions, frames requests, and protects brand voice when interacting with AI, translating complex business problems into usable prompt frameworks.

    Agent Ops Manager: Designs, monitors, and maintains workflows for semi-autonomous AI tools and agents, ensuring they run effectively and report back reliably. This role combines operations, product, and systems thinking.

    AI Auditor: A quality assurance role that reviews AI output, flags issues like "hallucinations," ensures ethical guardrails, and tracks whether AI use genuinely improves work, acting as part QA, policy, and advocate.

    Knowledge Librarian: Manages the internal knowledge base, including source material, SOPs, brand assets, and tone examples, making sure AI has access to accurate and relevant information to function effectively.

    Creative Synth: A hybrid role that takes AI-generated outputs and transforms them into shippable assets by refining the voice, structuring the narrative, and curating the message, elevating creative work rather than replacing it.

    What is the "trickle-tickle" approach to AI integration?

    The "trickle-tickle" approach emphasizes a two-way communication and integration strategy. It combines a "trickle down" from leadership, providing guidelines, goals, objectives, and shaping the AI-native culture. Simultaneously, it involves a "tickle up" from the bottom, where leaders actively engage with the people doing the work to understand how they are using AI, how it can be integrated into team and individual workflows, and to give them a voice and ownership in the process. This meeting in the middle fosters a unified company culture and reveals systemic issues, leading to significant improvements.

  • AI doesn't just change how we work; it changes who does what. Old titles no longer capture new realities. For example, project managers might become "Agent Coordinators," strategists evolve into "Prompt Architects," and ops teams need "Workflow Designers." Simply using AI tools without designing functions around them results in duplicated tasks, role confusion, and gaps in ownership. Teams that truly evolve build new functions and roles, recognizing the tension and synergy between human strengths (empathy, decision-making, brand intuition) and machine strengths (processing, summarizing, formatting).


    A "smart modular system," however, is an "intentional, flexible, branded, and adaptive" infrastructure. It combines information from the AI with the user's experience and knowledge, forming a "paired perspective approach." This structured approach ensures consistent output, tone, and quality, making the AI's assistance truly repeatable and reliable across a team. It's about designing "thinking blocks" that scale clarity, not just fill-in-the-blank hacks.

  • Internal audits are crucial for understanding the current state and identifying opportunities for AI integration. They should be simple, short snapshots, taking only about 5-15 minutes, and accessible to everyone. Key audit areas include:


    Cultural Audit: Understanding how AI fits into the company's culture and where communication gaps or preconceived silos exist.

    Personal Audit: Assessing individual comfort with AI tools and how people are currently using them (e.g., daily, weekly, never).

    ROI Audit: Evaluating how AI usage ladders up to the company's overall goals and return on investment.

    These audits help identify where improvements can be made, foster buy-in by demonstrating clear advantages, and empower both individuals and teams by providing concrete insights into their current AI landscape.

Process Of Elimination Episodes