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Product Impact Podcast | AI Strategy, KPIs, Future of Work

Presented by PH1
Product Impact Podcast | AI Strategy, KPIs, Future of Work
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  • Product Impact Podcast | AI Strategy, KPIs, Future of Work

    12. How Atlassian's Chief Design Officer Builds for Agents

    28-05-2026 | 32 Min.
    Every 1% increase in the context your agents receive produces a 0.38% improvement in output quality. LangChain's State of AI Agents 2026 report makes that measurable — and it makes interface design the highest-leverage investment most product teams aren't treating it as. At Atlassian Team '26 in Anaheim last week, Chief Design Officer Charlie made the case: the interface is what determines how context gets captured, which means every design decision your team makes is now directly setting a ceiling on how well your agents perform. Eighty-eight percent of enterprise agent pilots fail to reach production, with context fragmentation as the top blocker. That is a design problem.

    For 25 years, adaptive interfaces were the holy grail — software that reads who you are and adjusts to how you work. Charlie's announcement at Team '26: the technology limitation is gone. What remains is a design question about where to set the balance point between a system that adapts and a system a team can actually share. And at the same time, designing for agents and designing for humans has converged into nearly the same problem — Atlassian's design system is consumed by agents and human users from the same object, with 10% variation. Every shortcut taken on design quality now shows up twice.

    Charlie Sutton is Chief Design Officer at Atlassian, where he leads design across Jira, Confluence, Rovo, and the newly announced Dia browser. He sat down with us at Team '26 in Anaheim. 

    In this episode:
    Why 783 tab interactions a day means even tiny friction changes produce outsized aggregate gains — and where to look first
    The 25-year holy grail of adaptive interfaces is technically solved — what remains is the design question of how much is right for teams
    Why structured objects (goals, strategy, people) beat expensive inference — and why most vendors are paying more for worse results
    How Atlassian's design system serves agents and humans from the same object with 10% variation — and what the 10% tells you
    Why vibe coding raised the floor so everyone can build, which is exactly why the ceiling on what design must deliver also rose
    Why video captures intent that text never can — and how Atlassian is encoding it into the Teamwork Graph

    "The floor goes up — everyone can make things awesome. But the ceiling has also gone up. Expectations increase, what is possible has increased. Design is still focusing on that ceiling."

    Charlie Sutton is Chief Design Officer at Atlassian, where he leads design philosophy and execution across the company's full product suite — including Jira, Confluence, Rovo, and the newly announced Dia browser. He was involved in building the demos showcased at Atlassian Team '26 and works at the intersection of enterprise product design and AI-native interface development. (Verify Charlie's full name before publishing.)

    Guest resources:
    Atlassian: https://www.atlassian.com
    Dia browser: https://www.atlassian.com/software/dia
    Charlie on LinkedIn: https://au.linkedin.com/in/charliesutton

    We built productimpactpod.com to be your AI product insights and strategic playbook hub. Check it out.
    Thank you for listening to the Product Impact Podcast — if you have feedback, guest recommendations, or want to chat — contact us.

    Hosted by:
    Arpy Dragffy Guerrero — https://www.linkedin.com/in/adragffy/
    Brittany Hobbs — https://www.linkedin.com/in/brittanyhobbs/

    Go to Substack to get AI strategy frameworks, news, and jobs: https://productimpactpod.substack.com

    This episode was brought to you by:
    PH1 (https://ph1.ca) — a strategy & research consultancy specialized in delivering evidence about the highest value use cases and customer profiles.

    AI Value Acceleration (https://aivalueacceleration.com) — The consultancy specialising in enterprise value creation. Make sure that your spending doesn't go to waste. Find out exactly where the value creation of adopting AI products stalls.
  • Product Impact Podcast | AI Strategy, KPIs, Future of Work

    11. Context Graphs Will Reshape How We Work [Jamil Valliani - VP AI, Atlassian]

    20-05-2026 | 29 Min.
    The fastest teams didn't switch to a better AI model. They gave their AI memory. At Atlassian Team 2026 they showed us the next evolution of AI capabilities: 150 billion connected objects across an organization, an agent reviewing 2 billion lines of code in 2 minutes, and 44% better answers using half the tokens. Inside teams, the change is concrete: a junior analyst gets years of knowledge instantly, and a product leader can oversee an entire enterprise's deployment.

    Our guest, Jamil Valliani leads AI product at Atlassian, where he has spent three years building the context layer that will help 300,000 companies. They also shocked everyone by announcing that the Teamwork Graph — is open to be connected to your work in Microsoft, Adobe, and Google.

    In this episode you'll learn:
    Why Atlassian made their context graph open
    Evidence that context improves token usage
    What the future of work will look like
    The key to delivering value at scale

    We built https://productimpactpod.comproductimpactpod.com to be your AI product insights and strategic playbook hub. Check it out.
    Thank you for listening to the Product Impact Podcast — if you have feedback, guest recommendations, or want to chat — contact us.

    About Jamil Valliani: Jamil Valliani is VP / Head of Product, AI at Atlassian, where he leads Rovo and the Teamwork Graph across the company's full product suite. He has been building AI product strategy at Atlassian since before the Rovo launch and works across the enterprise customer base to understand where AI adoption is actually working and where it stalls. Atlassian's tools — Jira, Confluence, Bitbucket, and connected third-party systems — are used by over 300,000 companies worldwide.
    Atlassian: https://www.atlassian.com
    Rovo: https://www.atlassian.com/software/rovo
    Jamil Valliani on LinkedIn: https://www.linkedin.com/in/jamil-valliani-b131881/

    Hosted by:
    Arpy Dragffy Guerrero — https://www.linkedin.com/in/adragffy/
    Brittany Hobbs — https://www.linkedin.com/in/brittanyhobbs/
    Go to Substack to get AI strategy frameworks, news, and jobs: https://productimpactpod.substack.com

    This episode was brought to you by:
    PH1 (https://ph1.ca) — an strategy & research consultancy specialized in delivering evidence about the highest value use cases and customers profiles.
    AI Value Acceleration (https://aivalueacceleration.com) — The consultancy specialising in enterprise value creation. Make sure that your spending doesn't go to waste. Find out exactly where the value creation of adopting AI products stalls.
  • Product Impact Podcast | AI Strategy, KPIs, Future of Work

    10. Why Most AI Customer Experiences Fall Flat [Rikki Singh, Twilio]

    11-05-2026 | 45 Min.
    Most enterprise AI investments in customer experience are stuck somewhere between a demo and a disappointment. The Qualtrics 2026 Customer Experience Trends Report found that nearly one in five consumers who used AI customer service saw zero benefit from the interaction. The bar for what enterprises are calling AI innovation is shockingly low, and customers feel it every time they're routed to a bot that reads from an FAQ.

    Rikki Singh leads product innovation at Twilio. Before Twilio she was at McKinsey, where she co-authored the definitive research on what makes a great PM. Before that she was a PM at Microsoft. She's now running the team behind what Twilio is calling its biggest launch in 17 years — an agent-native channel with conversation memory across voice, text, and email.

    In this episode we cover:
    ➜ Why most AI customer experiences are still just RPA with better packaging — and the right metric to anchor on instead
    ➜ Why token consumption made AI spend as unpredictable as AI ROI, leaving enterprise decisions with uncertainty on both sides
    ➜ Why the LLM wrapper creates false confidence — the model is not thinking, it's generating strings non-deterministically
    ➜ Vitamins vs painkillers: how to parse the signals customers don't say out loud from the ones that don't actually matter
    ➜ How to protect long-horizon bets inside a public company: separate PMs by horizon and celebrate what you disprove
    ➜ Why the brand owns the accountability when AI gets a high-stakes interaction wrong, regardless of which vendor caused it

    ..................

    If you found this episode useful, please like, share, and send it to anyone on your team who'd find it helpful.

    We built ⁠https://productimpactpod.com⁠ to be your AI product strategy and AI product news hub. Check it out.

    Thank you for listening to the Product Impact Podcast — if you have feedback, guest recommendations, or want to chat — contact us.

    Hosted by:

    ➜ Arpy Dragffy Guerrero — ⁠https://www.linkedin.com/in/adragffy/⁠

    ➜ Brittany Hobbs — ⁠https://www.linkedin.com/in/brittanyhobbs/⁠

    Go to Substack to get AI strategy frameworks, news, and jobs: ⁠https://productimpactpod.substack.com⁠

    This episode was brought to you by:

    ➜ PH1 (⁠https://ph1.ca⁠) — an AI strategy consultancy specialized in improving the measurable success of AI products.

    ➜ AI Value Acceleration (⁠https://aivalueacceleration.com⁠) — The consultancy specialising in enterprise value creation. Make sure that your spending doesn't go to waste. Find out exactly where the value creation of adopting AI products stalls.
  • Product Impact Podcast | AI Strategy, KPIs, Future of Work

    9. Shipping AI Fast Without Breaking Everything [John Willis, 6x author]

    30-04-2026 | 48 Min.
    Most companies are running AI in production right now without any plan to govern and secure their businesses. This week Claude Code wiped out a business' entire database in 9 seconds. Anything is possible when an agent is given access to everything without governance. John Willis co-wrote The DevOps Handbook a decade ago because software teams were shipping code the same way — fast, manual, no visibility. He sees the same pattern repeating with AI, and he has spent five decades watching what happens when the gap between vendor promises and operational reality gets this wide. He's written 6 books and also happens to be a historian about AI.
    In this episode we cover:
    Why shadow AI — no ban, no guidance, company data on personal phones — is the most dangerous place to be
    Why higher throughput and higher instability at the same time is the predictable outcome of speed without feedback loops
    Why governance creates flow instead of stopping it — and how that lesson from DevOps applies directly to AI now
    Why most teams think they have AI observability when they actually have ML evaluation tools solving a different problem
    Why every team — even a five-person startup with no CTO — needs digitally signed audit trails for agent decisions
    What the history of AI winters and springs tells us about where we actually are in the current cycle
    If you found this episode useful, please like, share, and send it to anyone on your team who'd find it helpful.
    We built https://productimpactpod.com to be your AI product strategy and AI product news hub. Check it out.

    Thank you for listening to the Product Impact Podcast — if you have feedback, guest recommendations, or want to chat — contact us.

    Hosted by:
    Arpy Dragffy Guerrero — https://www.linkedin.com/in/adragffy/
    Brittany Hobbs — https://www.linkedin.com/in/brittanyhobbs/

    Featured guest:
    John is an accomplished author and innovative entrepreneur with over 35 years of experience in enterprise IT and research, driven by a deep passion for exploring the intersection of Generative AI and the transformative principles of Dr. W. Edwards Deming. He is the author of Rebels of Reason, a book that traces the history of artificial intelligence while uncovering the human stories behind its rise, connecting today’s AI landscape to the ideas and people that shaped the field and offering a unique perspective on its future in business. As a co-author of foundational DevOps works, John brings a rare blend of technical expertise and insight into the human dynamics of innovation, helping leaders cut through hype to focus on creating real customer value through a deeper understanding of AI’s context and systems.

    John’s LinkedIn: https://www.linkedin.com/in/johnwillisatlanta/

    Link to John’s Book Rebels of Reason: https://www.amazon.com/Rebels-Reason-Aristotle-ChatGPT-Heroes-ebook/dp/B0FCD8TW8R

    Go to Substack to get AI strategy frameworks, news, and jobs: https://productimpactpod.substack.com
    This episode was brought to you by:
    PH1 (https://ph1.ca) — an AI strategy consultancy specialized in improving the measurable success of AI products.
    AI Value Acceleration (https://aivalueacceleration.com) — The consultancy specialising in enterprise value creation. Make sure that your spending doesn't go to waste. Find out exactly where the value creation of adopting AI products stalls.
  • Product Impact Podcast | AI Strategy, KPIs, Future of Work

    8. The Most Important Data Points in AI Right Now

    24-04-2026 | 18 Min.
    Stanford's 2026 AI Index just dropped. China closed a thirty-point AI performance gap to under three percent — on twenty-three times less investment. Apple picked their head of hardware as the next CEO. Anthropic's Mythos model found 271 zero-day vulnerabilities in Firefox. And Vercel and Lovable both got breached this month.
    We break down the numbers that should be on every product leader, designer, and founder's desk this week — what they mean, and exactly what to do about each one.
    In this episode we cover:
    ➜ Stanford AI Index 2026: 88% organizational adoption, $581 billion in investment, and why China closing the gap on a fraction of the budget is the most important data point in the report
    ➜ Token economics explained — what tokens are, what they cost, and why the shift from flat-rate licensing to usage-based pricing changes your AI budget math overnight
    ➜ Why replacing Figma with Claude Design costs $0.22 for a first draft and $2,600 at refinement scale — and what that reveals about real-world AI costs
    ➜ Why Apple chose John Ternus as CEO and elevated Johny Srouji to Chief Hardware Officer — and what that says about where AI value will actually live
    ➜ Mythos, Vercel, Lovable: why vibe coding has never been easier and information security has never been more important
    ..................
    If you found this episode useful, please like, share, and send it to anyone on your team who'd find it helpful. ⁠https://productimpactpod.com⁠ — Our news platform just launched. It is the best place to get the AI product news that matters.
    Hosted by:
    ➜ Arpy Dragffy Guerrero — ⁠https://www.linkedin.com/in/adragffy/⁠ 
    ➜ Brittany Hobbs — ⁠https://www.linkedin.com/in/brittanyhobbs/⁠
    Go to Substack to get AI strategy frameworks, news, and jobs: ⁠https://productimpactpod.substack.com⁠

    This episode was brought to you by:
    ➜ PH1 (⁠https://ph1.ca⁠) — an AI strategy consultancy specialized in improving the measurable success of AI products.
    ➜ AI Value Acceleration (⁠https://aivalueacceleration.com⁠) — The consultancy specialising in enterprise value creation. Make sure that your spending doesn't go to waste. Find out exactly where the value creation of adopting AI products stalls.
    ...........
    Sources referenced in this episode:
    Stanford AI Index 2026 — https://productimpactpod.com/news/stanford-ai-index-2026-product-team-takeaways 
    Stanford: US can't buy an AI lead — https://productimpactpod.com/news/stanford-ai-index-proves-us-cant-buy-ai-lead 
    Claude Design vs Figma — https://productimpactpod.com/news/figma-claude-design-source-of-truth-for-design 
    Apple CEO transition — https://productimpactpod.com/news/how-tim-cook-leaves-apple-future-of-ai 
    Anthropic Mythos Preview — https://techcrunch.com/2026/04/07/anthropic-mythos-ai-model-preview-security 
    Vercel breach — https://techcrunch.com/2026/04/20/app-host-vercel-confirms-security-incident 
    Lovable vulnerability — https://thenextweb.com/news/lovable-vibe-coding-security-crisis-exposed 
    AI token pricing — https://www.cnbc.com/2026/04/17/ai-tokens-anthropic-openai-nvidia
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Over Product Impact Podcast | AI Strategy, KPIs, Future of Work
AI product strategy for product leaders, designers, and founders who need to make AI work — not just talk about it. Every week we break down enterprise AI adoption, agentic systems, physical AI, token economics, and real AI costs. Evidence-first — what's working, what's failing, and what to do about it. Built for the people responsible for shipping AI products that actually perform and proving the value when they do. News: https://productimpactpod.com Hosted by Arpy Dragffy Guerrero (PH1 — https://ph1.ca) and Brittany Hobbs (AI Value Acceleration — https://aivalueacceleration.com).
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