Data & AI Podcast from Indicium AI cover art

Data & AI Podcast from Indicium AI

Data & AI Podcast from Indicium AI

Written by: Indicium AI
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A podcast that explores the developments, insights and trends across data, AI and the technology that powers it. Join the Indicium AI team and special guests as they delve into the latest news and discuss the challenges on how enterprises are reimagining how they use data and AI to benefit their customers. Whether you're an experienced practitioner or just wanting to find out more about this constantly changing space, our podcast has something for everyone.

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Indicium AI
Economics
Episodes
  • The Myth of the Magic Model
    Jun 5 2026

    Enterprise AI initiatives frequently stall between pilot and production, even when the underlying models perform well. Kareem Al-Hakeem traces that pattern back to two recurring failures: investing in the wrong use cases without validating return early, and underestimating the governance and security overhead that real operational data demands.

    The episode covers how enterprises can qualify use cases faster, where workforce enablement delivers underrated returns, and what getting AI out of the pilot phase actually requires organizationally.



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    19 mins
  • International Women's Day: Career lessons from Women in Tech
    Mar 6 2026
    In celebration of International Women's Day, we brought together a group of women from across Indicium AI — from data scientists and AI advisors to people experience managers and partnership leads — to talk honestly about their journeys in technology.

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    33 mins
  • AI-Assisted Coding: From Autocomplete to Autonomous Agents
    Jan 15 2026

    In this episode of the Data & AI Podcast, host Alex Juarez, Director of Engineering at Mesh-AI, is joined by Elliot Budd (Lead AI Engineer), Millie Wan Marriott (Data Engineer), and Maartens Lourens (Principal AI Engineer) for a deep dive into the rapidly evolving world of AI-assisted coding.

    The team explores how AI coding tools have transformed from basic autocomplete suggestions to sophisticated development partners - and what that means for the future of software engineering. From the early days of GitHub Copilot to today's agentic coding systems, they discuss the trust, limitations, and best practices that are shaping how developers work alongside AI.

    This episode covers:

    • The evolution from autocomplete to agentic coding systems
    • Why trust is the critical factor in adopting AI coding tools
    • The gap between "vibe coding" and proper engineering practices
    • Current limitations: context management, hallucinations, and when AI changes the wrong code
    • Emerging best practices and the concept of "guardrail engineering"
    • What junior developers need to learn in an AI-assisted world
    • The future of verification, testing, and developer satisfaction

    Whether you're sceptical about AI coding tools or already using them daily, this conversation offers honest insights into what works, what doesn't, and where the industry is headed.

    "Developer satisfaction is at an all-time high with these tools. If five years ago it took you a week to build an API, and now you can do it in an hour - that's really satisfying."



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    36 mins
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