Tech Insider Weekly

AI as a Thinking Partner: ADHD, Agents, and Human-Centered AI with Adam Federman

14 min · I går
episode AI as a Thinking Partner: ADHD, Agents, and Human-Centered AI with Adam Federman cover

Beskrivelse

In this episode of Tech Insider Weekly, host Derek sits down with Adam Federman, an enterprise AI practitioner at Accenture with a background spanning CDW and Remark Systems, to explore what it really means to use AI as a thinking partner rather than a productivity shortcut. Adam opens up about living with ADHD and how generative AI became the first tool that could genuinely keep pace with a fast, nonlinear mind. He explains why the ability to do a continuous brain dump into an AI system, and have it reflect structured ideas back, changed the way he works. The conversation then shifts to the enterprise world, where Adam shares hard-won lessons from building and eventually consolidating over 50 internal AI agents down to five that actually survived real-world use. He unpacks why most early agents failed not because the technology was wrong, but because they were built for one person, could not scale, and were solving problems that should have been features of something larger. AI as a cognitive partner: For people with ADHD or fast-moving thought patterns, AI can handle the volume and branching detail that overwhelms human listeners, making it a uniquely effective thinking tool. The agent consolidation reality: Building 50 AI agents is easy. Knowing which five are worth keeping, and why, requires understanding how skills should be grouped, not siloed. Human bottleneck in enterprise AI: As AI handles more execution, the human becomes the new constraint. Adoption cycles slow not because of technology gaps but because of trust, habit, and office politics. Artistry cannot be automated: AI produces high-probability answers drawn from aggregated data. The unique career perspective, judgment, and contextual artistry each person brings is something no model can replicate. Designing for cognition, not convenience: The most durable AI tools force users to keep thinking rather than outsourcing thought entirely, removing repetitive burden while preserving human ownership of decisions. If you found this episode useful, subscribe wherever you listen to podcasts and leave a review. Have a guest suggestion or topic idea? Tag us on social media or send us a message. New episodes drop every Wednesday.

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episode AI as a Thinking Partner: ADHD, Agents, and Human-Centered AI with Adam Federman cover

AI as a Thinking Partner: ADHD, Agents, and Human-Centered AI with Adam Federman

In this episode of Tech Insider Weekly, host Derek sits down with Adam Federman, an enterprise AI practitioner at Accenture with a background spanning CDW and Remark Systems, to explore what it really means to use AI as a thinking partner rather than a productivity shortcut. Adam opens up about living with ADHD and how generative AI became the first tool that could genuinely keep pace with a fast, nonlinear mind. He explains why the ability to do a continuous brain dump into an AI system, and have it reflect structured ideas back, changed the way he works. The conversation then shifts to the enterprise world, where Adam shares hard-won lessons from building and eventually consolidating over 50 internal AI agents down to five that actually survived real-world use. He unpacks why most early agents failed not because the technology was wrong, but because they were built for one person, could not scale, and were solving problems that should have been features of something larger. AI as a cognitive partner: For people with ADHD or fast-moving thought patterns, AI can handle the volume and branching detail that overwhelms human listeners, making it a uniquely effective thinking tool. The agent consolidation reality: Building 50 AI agents is easy. Knowing which five are worth keeping, and why, requires understanding how skills should be grouped, not siloed. Human bottleneck in enterprise AI: As AI handles more execution, the human becomes the new constraint. Adoption cycles slow not because of technology gaps but because of trust, habit, and office politics. Artistry cannot be automated: AI produces high-probability answers drawn from aggregated data. The unique career perspective, judgment, and contextual artistry each person brings is something no model can replicate. Designing for cognition, not convenience: The most durable AI tools force users to keep thinking rather than outsourcing thought entirely, removing repetitive burden while preserving human ownership of decisions. If you found this episode useful, subscribe wherever you listen to podcasts and leave a review. Have a guest suggestion or topic idea? Tag us on social media or send us a message. New episodes drop every Wednesday.

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