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        <title>Data Stars &amp; Scars</title>
        <link>https://redcircle.com/shows/data-scars-and-stars</link>
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        <itunes:subtitle>The wins, the wounds and the wisdom of data leadership.</itunes:subtitle>
        <itunes:author>Ignite Data Solutions</itunes:author>
        <itunes:summary>Join host Harj Chand as he sits down with the data leaders and executives across the stack – the people who’ve changed how decisions get made and how the work gets done.

Every episode gets down to the wins and the wounds: the calls that paid off, and the ones they’d take back.

If your job is making data count, this is the room.</itunes:summary>
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        <description><![CDATA[<p>Join host Harj Chand as he sits down with data leaders and people who change how decisions are made and how work gets done.</p><p>Every episode inspects the wins and highlights the wounds: the calls that paid off, and the ones they’d take back.</p><p>If your job is making data count, this is the room.</p>]]></description>
        
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            <itunes:name>Ignite Data Solutions</itunes:name>
            <itunes:email>communications@ignitedata.com.au</itunes:email>
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                <itunes:title>Industrial AI, and the Human in the Loop</itunes:title>
                <title>Industrial AI, and the Human in the Loop</title>

                <itunes:episode>1</itunes:episode>
                
                <itunes:author>Ignite Data Solutions</itunes:author>
                
                <description><![CDATA[<p>Twenty years ago, Julien Debard was running a rig that cost a million dollars a day. At 23. Offshore in Nigeria. With his best data arriving by USB stick in someone’s pocket on a chopper. Now he’s a 2026 S&amp;P Global Energy Awards finalist and the person a lot of energy leaders call to work out where AI actually earns its keep.</p><p>This episode is the throughline of his career: technology only creates value when it changes how the work gets done. Harj Chand and Emily Kucukalic get him on the hard questions; who holds the decision rights when AI is in the loop, why senior leaders still won’t ask their own data a question, and why “industrial AI” is its own beast when a wrong call shuts a safety valve rather than ruins your dinner.</p><h4>IN THIS EPISODE</h4><p><br></p><ul><li>Julien’s field years running a rig that cost a million dollars a day offshore Nigeria at 23, when getting data to shore meant a USB stick on a helicopter.</li><li>The retirement cliff facing energy, and why the old phone-a-mentor model is running out of mentors.</li><li>Who actually holds the right to make a decision on site once AI is in the loop, and how you know the call is a good one.</li><li>Why AI should augment people rather than replace them, and the case for solving small before shooting for the moon.</li><li>The productivity problem energy hasn’t faced yet, with an ageing workforce and fewer active people funding more retirees.</li><li>Why you should back the experienced person’s gut over the data when the two disagree.</li><li>Why senior leaders still won’t ask their own data a question, and why it’s habit rather than fear of the tech.</li><li>How the Strait of Hormuz closure separated the companies that were ready from the ones that weren’t.</li><li>The two kinds of companies that win with AI, and the ways the rest get stuck.</li><li>The valley of death between a single use case and a scalable platform, and why it bites harder in Australia.</li><li>Why a proof of concept is really a proof of competency, and what that changes about how you start.</li><li>What industrial AI actually means when a wrong call shuts a safety valve, and why AI needs the industries as much as they need it.</li><li>The physics advantage legacy players are sitting on, and why good enough beats perfect.</li><li>Supplier concentration, frontier labs that won’t all survive, and building an architecture you can pivot.</li><li>Julien’s advice to leaders to dive in and not trust the vendors, and to newcomers to learn the domain first.</li><li>What’s next with GREJU, the venture connecting executives who want value with the smaller players who can deliver it.</li></ul>]]></description>
                <content:encoded>&lt;p&gt;Twenty years ago, Julien Debard was running a rig that cost a million dollars a day. At 23. Offshore in Nigeria. With his best data arriving by USB stick in someone’s pocket on a chopper. Now he’s a 2026 S&amp;amp;P Global Energy Awards finalist and the person a lot of energy leaders call to work out where AI actually earns its keep.&lt;/p&gt;&lt;p&gt;This episode is the throughline of his career: technology only creates value when it changes how the work gets done. Harj Chand and Emily Kucukalic get him on the hard questions; who holds the decision rights when AI is in the loop, why senior leaders still won’t ask their own data a question, and why “industrial AI” is its own beast when a wrong call shuts a safety valve rather than ruins your dinner.&lt;/p&gt;&lt;h4&gt;IN THIS EPISODE&lt;/h4&gt;&lt;p&gt;&lt;br&gt;&lt;/p&gt;&lt;ul&gt;&lt;li&gt;Julien’s field years running a rig that cost a million dollars a day offshore Nigeria at 23, when getting data to shore meant a USB stick on a helicopter.&lt;/li&gt;&lt;li&gt;The retirement cliff facing energy, and why the old phone-a-mentor model is running out of mentors.&lt;/li&gt;&lt;li&gt;Who actually holds the right to make a decision on site once AI is in the loop, and how you know the call is a good one.&lt;/li&gt;&lt;li&gt;Why AI should augment people rather than replace them, and the case for solving small before shooting for the moon.&lt;/li&gt;&lt;li&gt;The productivity problem energy hasn’t faced yet, with an ageing workforce and fewer active people funding more retirees.&lt;/li&gt;&lt;li&gt;Why you should back the experienced person’s gut over the data when the two disagree.&lt;/li&gt;&lt;li&gt;Why senior leaders still won’t ask their own data a question, and why it’s habit rather than fear of the tech.&lt;/li&gt;&lt;li&gt;How the Strait of Hormuz closure separated the companies that were ready from the ones that weren’t.&lt;/li&gt;&lt;li&gt;The two kinds of companies that win with AI, and the ways the rest get stuck.&lt;/li&gt;&lt;li&gt;The valley of death between a single use case and a scalable platform, and why it bites harder in Australia.&lt;/li&gt;&lt;li&gt;Why a proof of concept is really a proof of competency, and what that changes about how you start.&lt;/li&gt;&lt;li&gt;What industrial AI actually means when a wrong call shuts a safety valve, and why AI needs the industries as much as they need it.&lt;/li&gt;&lt;li&gt;The physics advantage legacy players are sitting on, and why good enough beats perfect.&lt;/li&gt;&lt;li&gt;Supplier concentration, frontier labs that won’t all survive, and building an architecture you can pivot.&lt;/li&gt;&lt;li&gt;Julien’s advice to leaders to dive in and not trust the vendors, and to newcomers to learn the domain first.&lt;/li&gt;&lt;li&gt;What’s next with GREJU, the venture connecting executives who want value with the smaller players who can deliver it.&lt;/li&gt;&lt;/ul&gt;</content:encoded>
                
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                <link>https://ignitedata.com.au/podcast/</link>
                <pubDate>Thu, 15 Oct 2026 05:48:33 &#43;0000</pubDate>
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