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Scaling w/ Agility Podcast

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by Yuval Yeret | Yeret Agility

44 episodes

Updated Daily

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Podcast Overview

Scaling AI: From Activity to Impact is for technology, product, and business leaders asking a hard question: how do we turn all this AI activity theater into real business impact? Yuval and his guests explore what needs to change in how organizations choose, fund, learn, and work with AI — including how native AI capabilities can help scale AI itself. Building on its roots in scaling with agility, the podcast applies adaptive, product-oriented thinking to the biggest operating-model challenge facing organizations today.

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Publishing Since

12/7/2022

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Podcast Authority

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PoorBased on show quality, social media presence, reviews, charts, and more

Quality22

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excellent

Episode Length

27 minutes

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21 episodes over 2.7 years

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Every 47 days

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Recent Episodes

June 2, 2026

Why the Pivot? Tracing the Line from Scaling Agility to AI Impact

In this special episode, host Yuval Yeret flips the script with guest Philip Morgan, an expert on positioning and point of view. They discuss the recent rebranding of the podcast and dive deep into the striking parallels between historical Agile Theater and the emerging risks of AI Theater. Discover why measuring raw activity—like tokens consumed or lines of code written—is a trap, and how organizations can shift toward measuring tangible business outcomes and flow efficiency. You'll also learn about Unreasonable Agility and what happens when R&D goes on the offense. Chapters00:08 The Agile Shift in AI and Podcast Rebranding01:07 Philip Morgan's Background in Positioning02:36 Yuval's Role as a Plumber for Engineering Pipelines06:53 How Pain and Opportunity Drive Change (Gillette & Biotech Examples)15:51 Introspective and Compound Engineering 17:08 Exploring AI Theater vs. Agile Theater21:44 Shifting Bottlenecks: From Coding to Code Review and Adoption28:04 The Trap of Vanity Metrics and Token Maxing33:26 Moving from Output to Outcomes and Business Impact40:50 Breaking the Status Quo and Resisting AI Mandates56:21 Unreasonable Agility: Taking R&D on the Offense Notable Quotes"If you want to succeed with it, find somebody who talks about the principles, who understands it in depth, who can make changes while still being aligned to the spirit." - Yuval Yeret "People will find a way to use AI without really getting any value. They will find a way to generate a lot of activity, but not really create any change in the impact." - Yuval Yeret "There's a sense in which it seems like Agile was sort of waiting for AI." - Philip Morgan Ready to stop measuring tokens and start measuring real business outcomes? Reach out to Yuval at <a href="yuvalyeret.com" target="_blank" rel="noopener noreferer">yuvalyeret.com</a> or <a href="mailto:yuval@yeretagility.com" target="_blank" rel="noopener noreferer">yuval@yeretagility.com </a>to discuss how to build unreasonable agility into your organization. About PhilipPhilip Morgan is a positioning and point-of-view expert who helps independent service providers thrive by leveraging effective market positioning. He is the author of multiple books on the topic and shares his insights freely at <a href="https://philipmorgan.net/">⁠philipmorgan.net⁠</a>.Scaling AI: From Activity to Impact — yuvalyeret.comThe Scaling w/ Agility Newsletter – yuvalyeret.com/insightsYuval's Linkedin – https://www.linkedin.com/in/yuvalyeret/

May 27, 2026

Claude's /goal Feature Just Exposed A Real Challenge With AI Agents

Claude and Codex have a relatively new feature — `/goal` — that lets you set a completion condition and keep the AI running autonomously until it's met. This capability exposes a real challenge with agentic AI and explains why its shifting the bottleneck to its assymetric capabilities in different stages and domains of value creation. 00:09 The new /goal capability — what it does and how it works02:07 What the official examples reveal: all output, no outcome03:02 The missing examples — what outcome-oriented goals would actually look like04:00 Output vs. outcome: why the gap matters for AI impact04:45 The real bottleneck — observability and closing the feedback loop05:45 Live demo: setting an outcome-oriented /goal on a blog post08:30 What the loop did — changes made, open items, what's next Are your AI goals output-oriented or outcome-oriented? What are you doing to enable outcome-oriented goals in your AI sessions? And as a final thought - What would happen if your human teams were empowered to seek a /goal? <a href="yuvalyeret.com/insights" target="_blank" rel="noopener noreferer">Insights on Scaling AI from Activity to Impact</a><a href="https://www.linkedin.com/in/yuvalyeret/" target="_blank" rel="noopener noreferer">Join the Activity to Impact Conversation on Linkedin</a>

May 21, 2026

You can 10x engineering and still not 10x the business

AI coding assistants are genuinely good now — coding, debugging, tests, docs. But faster engineering output doesn't automatically become faster business impact. AI has quietly moved the bottleneck: from building working software to validating whether that software creates value for anyone who adopts it.This episode uses flow thinking, cumulative flow, and the theory of constraints to help leaders see where AI speed is creating congestion — and where human + AI effort should be aimed next.Key takeaways:• AI creates speed, not automatic value — speed only counts if it improves end-to-end flow• AI impact is asymmetric: engineering scales faster than discovery, adoption, and value validation• Local productivity can create system-level congestion once the bottleneck moves• Tech debt hides the new bottleneck — engineering absorbs extra capacity into easy-to-validate cleanup• Inventory is the signal: watch where work waits, loops, or gets reworked• Subordinate human and AI effort to the current constraint — don't spread enablement evenlyChapters:00:00 — The promise of AI in engineering02:04 — Why AI's impact is asymmetric05:02 — Spotting the moved bottleneck07:56 — From activity to impact: visualizing flow10:19 — Driving adoption, not just output13:15 — Subordinating people and AI to the constraint15:47 — Continuous improvement and real valueMonday morning diagnostic — pick one AI initiative and ask: What outcome should it improve? Where does work wait or get reworked? If this team gets 2x faster, which group becomes the constraint — and what AI support should be redirected toward them?"You can 10x engineering and still not 10x the business. Don't force everybody to scale - help the constraint scale."If this helped, share it with a leader trying to turn AI activity into real business value.

44 total episodes available

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Jesper Boeg

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Yuval Yeret

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Michael Gerharz

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Jonathan Stark

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What is Scaling w/ Agility Podcast?: Scaling AI: From Activity to Impact is for technology, product, and business leaders asking a hard question: how do we turn all this AI activity theater into real business impact? Yuval and his guests explore what needs to change in how organizations choose, fund, learn, and work with AI — including how native AI capabilities can help scale AI itself.

Building on its roots in scaling with agility, the podcast applies adaptive, product-oriented thinking to the biggest operating-model challenge facing organizations today.
How often does this podcast release new episodes?: This podcast updates daily.
Where can I listen to this podcast?: This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
Does this podcast accept guests?: Yes, this podcast regularly features guests.

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