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Cloud Dialogues

Cloud Dialogues

Von: Georgia Smith and Matthew Gillard
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Navigating business and contemporary tech in the Cloud. Join Georgia and Matt as they unpack and simplify an important Cloud topic aimed at executives and business leaders. Along with the occasional special guest they will cover all things Cloud from strategy, execution, practical business use cases and much more!Copyright 2023 All rights reserved.
  • Entering 2026 - The operational state of AI & Cloud
    Jan 23 2026
    The Operational State of AI & Cloud We’re kicking off 2026 with a reality check. In this episode, Matt, Georgia, and special guest Allen Helton (Ecosystem Engineer at Memento, AWS Hero, and, yes - farmer) dig into what’s actually happening in AI and cloud right now. Less hype, more hard truths. From AI pilots that won’t scale to power grids that can’t keep up, this conversation explores what it really takes to move from experimentation to production. 🎙️ Hosts & Guest Matt — Host (Texas)Georgia — Host (London)Allen Helton — Ecosystem Engineer at Memento, AWS Hero, and farmer 🗞️ Cloud & AI News: What’s Worth Paying Attention To GPT Health: Innovation or Repackaging? The team unpacks OpenAI’s GPT Health launch, questioning whether it’s a genuinely differentiated product or simply a safer wrapper around existing capabilities. Georgia shares how ChatGPT proved unexpectedly useful for post-surgery aftercare - sometimes outperforming traditional medical guidance. AWS Is Back in Growth Mode AWS reported ~20% year-on-year growth in Q3, its strongest in nearly three years. The consensus? AWS has finally caught up on AI - largely thanks to its Anthropic partnership and global access to Claude through Bedrock. Quantum Computing: Is 2026 the Tipping Point? IBM predicts quantum computers will outperform classical systems as early as 2026. The group discusses what that could mean for cryptography, banking, and security - while openly admitting that quantum still needs more expert decoding. Power Is the Real Bottleneck Google flags US transmission infrastructure as the biggest blocker for data-center expansion. That sparks a broader sustainability discussion: hyperscalers can’t depend on aging grids forever, and renewables aren’t optional - they’re inevitable. 🧠 The Operational Reality of AI & Cloud Your Data Foundation Still Isn’t Ready A recurring theme: organizations move “two steps forward, one step back” when AI exposes weak data governance and cloud foundations. As Georgia puts it: AI will not solve your data governance problems. The Education Gap Is the Silent Killer AI initiatives fail when business teams don’t understand the technology they’re adopting. Outsourcing isn’t enough - successful organizations immerse their entire teams so AI outputs are interpreted, validated, and trusted. Are We Really Past Pilots? Some say the pilot phase is over. Alan disagrees. Large parts of the industry are still early on the adoption curve - but the difference now is maturity: guardrails, retrieval systems, and meta-agents are production-ready. 👩‍💻 How AI Is Changing Software Careers AI isn’t just changing how software is built - it’s changing who gets hired. Key shifts discussed: Programming language choice matters less than everCode review, comprehension, and reasoning now outweigh writing from scratchSystems thinking is becoming table stakes - even for junior roles“Tech-lead thinking” is creeping into every level Alan’s advice to students and early-career engineers: You still need to understand how it all works - everything you write is part of something bigger. 🧩 Developer Operating Models: What Actually Scales? Ralph at Scale Matt introduces Geoffrey Huntley's Ralph Wiggum development approach: giving an LLM an ordered backlog and letting it execute autonomously across fresh context windows. Powerful - but expensive and hard to sustain. The “Gas town” Model An alternative approach uses 30-40 agents working in parallel across a stack. Fast, impressive… and extremely token-hungry and even more expensive! The Sensible Middle Ground Our hosts argue for balance: AI-accelerated delivery with strong human oversight. Think weeks of work compressed into afternoons - without sacrificing quality, maintainability, or understanding. 🔮 Looking Ahead Regional Model Availability Is a Deal-Breaker Many regulated organizations simply can’t adopt AI due to regional model restrictions. Australia, for example, has access to just one local foundation model - highlighting a global compliance challenge. Sustainability & Reliability Risks If models became unavailable or prohibitively expensive, productivity would fall off a cliff. Competition should help manage costs - but reliability at scale may be the bigger risk. The Adoption Curve Has Never Been Wider AI adoption now spans: Teams using autonomous coding agents dailyEnterprises still waiting for approval to touch an LLM Most regulated industries haven’t even started formal approval processes. ✅ Key Takeaways Data governance is still the biggest blocker to AI successDeveloper roles are shifting toward systems thinking and code comprehensionEnterprise AI adoption is far lower than headlines suggestRegional model availability is a serious global constraintPower and sustainability will shape the future of cloud growthThere’s no single “right” AI operating modelBusiness teams must deeply understand the ...
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    50 Min.
  • AWS re:Invent 2025 Wrapped
    Dec 8 2025

    Matt and Georgia recap AWS re:Invent 2025 with special guest Michael Walmsley, AWS Serverless Hero and Global Technology Architect at Accenture. Fresh from the Vegas event with 70,000 attendees, they discuss the major announcements, the shift toward AI agents, and Michael's wild experience coding on a bus for a $100K hackathon prize.

    Highlights

    Road to re:Invent Hackathon

    • 50 developers coded on buses traveling LA to Vegas over 5 hours
    • Michael's team built "Lucky Loo.me" - an AI bathroom finder using facial recognition
    • Winning team created "Oric" - an IDE that turns 3 lines into 3,000 lines of AI slop
    • Prize: $100K split among the winning team

    The Big Theme: AI Agents Everywhere

    • "Agents" was the dominant word at every booth
    • AWS pushing agent capabilities into every service team
    • Evolution from general AI (2024) to production agent platforms (2025)

    Announcements we covered:

    Agent Core Updates

    • New policy controls for blocking unauthorized actions
    • Evaluation tools for inspecting agent behavior
    • Progressive adoption - use pieces without adopting the whole platform

    AWS Agent Marketplace

    • Vendors can now sell pre-built agents
    • Example: Cloud Zero cost management agent

    Lambda Updates

    • Lambda managed instances
    • Durable functions for long-running workflows in code
    • Alternative for developers who don't want Step Functions

    S3 Vectors (GA)

    • Store 20 trillion vectors in one bucket
    • 90% cost savings vs traditional vector databases
    • Sub-100ms query times for frequent queries
    • "S3 is the cheapest database on the planet"

    CloudWatch Unified Data Store

    • All logs and metrics exposed in S3 Tables
    • Cheap, structured SQL querying of observability data

    AWS Interconnect ⭐ Biggest Surprise

    • High-speed encrypted links between AWS and Google Cloud
    • Azure support coming 2026
    • Free during preview (pricing TBA)
    • Major shift from AWS's anti-multi-cloud stance
    • Acknowledges multi-cloud reality in enterprises

    Kiro

    • Rebranding away from confusing "Amazon Q" umbrella
    • Kiro Powers: AI-activated tool modules
    • Reduces context bloat in coding agents
    • Active hackathon scene with significant prize pools
    Guest

    Michael Walmsley - AWS Serverless Hero, Global Technology Architect at Accenture, specializing in serverless and SaaS architecture. Fourth year attending re:Invent.

    Key Takeaway

    AWS is maturing from general AI capabilities to production-ready agent platforms while finally embracing multi-cloud architectures. The focus has shifted to making agents secure, manageable, and practical for enterprise use.

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    30 Min.
  • Powering AI Data Centers, Energy Demand, and the Renewable Revolution
    Nov 19 2025

    In this episode, Matt and Georgia sit down with Brad Young (Capgemini Invent) and Alistair Adams (Solution Energy) for a fast-moving conversation about AI’s exploding energy appetite and what it means for the future of data centers, power grids, and sustainability. From geopolitical tension to geothermal innovation, this one covers the full energy spectrum.

    What We Covered:

    - AI’s Energy Crunch AI growth is driving unprecedented demand for power. Hyperscalers like Meta, Google, and Microsoft are signing multi-billion-dollar infrastructure contracts at record pace, stretching grids and reshaping global infrastructure priorities. - The Rise of “Power-First” Google’s “power-first strategy” shows the new reality: build data centers where the power is, not where the people are. Nvidia’s Jensen Huang agrees—co-locating at generation sites may be the future. Reliable, renewable baseload power is now the real competitive edge. - Water: The Silent Crisis Energy gets the headlines, but water is just as critical. Google already uses ~70 billion litres annually for cooling—on track to rise tenfold. Innovations like geothermal heat rejection (e.g., the Pawsey supercomputer in WA) offer promising alternatives. - Renewables: What Actually Works Not all green energy is created equal. Wind and solar can’t deliver the 24/7 baseload those massive GPU clusters require. That leaves geothermal and nuclear as the only scalable clean options—though nuclear remains politically fraught in markets like Australia.

    Regional Realities

    - Australia: Victoria faces a looming 1.5 GW gap with coal retirement. - UK: Grid constraints limit data center growth. - US: Federal policy is leaning hard into nuclear and geothermal for AI. - Europe: Regulation is reshaping the tech landscape—for better or worse.

    Cloud’s Hidden ESG Problem

    Most cloud usage sits in companies’ Scope 3 emissions. As ESG rules tighten, lack of transparency from hyperscalers becomes a real compliance exposure. - Social License Becomes Strategy Community pushback is halting billion-dollar projects. The new game: secure energy, protect water, and bring the community with you. “Permission-based infrastructure” is quickly becoming the norm. - AI, Talent & the Enterprise Gap We discuss the widening skills challenge—junior staff struggle to validate AI outputs, and enterprises claiming “we don’t have use cases” are already falling behind. - Greener Compute Through Smart Pricing Dynamic cloud pricing tied to renewable availability is on the horizon—think “off-peak compute,” automatically routing workloads to greener grids.

    Standout Insights

    - We’re in the “Nokia 3210 era” of AI—25+ years of disruption ahead. - Robotics is still more marketing than reality. - Enterprise AI adoption is early; the real environmental impact is still to come.

    Key Takeaways

    - Data center location will follow energy, not geography. - Community permission is as critical as capital. - Water use must be part of every sustainability conversation. - Geothermal and nuclear are the only viable clean baseload options. - The next decade will be messy as demand outpaces grid upgrades. - Hyperscalers are accelerating renewable markets—out of necessity. - ESG exposure from opaque cloud emissions is rising fast.

    Conclusion

    AI’s growth is forcing a complete rethink of how we power digital infrastructure. The winners will be those who can solve the combined puzzle of clean energy, water management, community trust, and transparent reporting—at a speed the grid has never been asked to move before.

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    1 Std. und 19 Min.
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