ZERO SHOT - AI & Business. Anti-Hype.

ZERO SHOT gives leaders clarity on AI without the hype. Hosts James (The Technical Realist) and Llew (The Boardroom Proxy) unpack what truly matters at the intersection of AI, business and strategy in Australia. From sovereign capability to agentic workflows, we break down the decisions shaping the country’s technological future and why they matter for Boards and executives. No noise, no jargon, just grounded insight. James: Chief AI Officer at Cadent | AI Governance & Strategy Executive (Ethical AI)Llew: Managing Director at Advancer | AI Strategy & DigitalProduced by Yennia La Rotta.

ZERO SHOT - AI & Business. Anti-Hype. is a business podcast hosted by Glass Box, with 28 episodes on record and a Required Pod Score of 80. PitchCentric scores this show on Booking Probability, Listen Score, and live audience signals refreshed every 24 hours.

Glass Box hosts ZERO SHOT - AI & Business. Anti-Hype., a business show with 28 episodes published.

Our AI reads these to draft pitches. Use them as grounding for a pitch that cites a real guest and a specific topic.

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  Episode #30

  EP 30: AI as a Decision Partner - Sharpen Your Judgment, Don’t Outsource It

  Aug 16, 202646 minS3

  Every business is thousands of decisions stacked on top of each other. So what actually changes when AI pulls up a seat at the table? In Episode 30 of ⁠⁠ Zero Shot ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury move past productivity and into something bigger: how AI is reshaping the way leaders make decisions. When people hear AI decision making, they assume it means AI makes the call, and that is the least interesting and most dangerous use of it. This episode is about using AI as a thinking partner to sharpen a decision, where it can quietly lead you astray through bias and confident errors, and why the decision and the accountability always stay firmly with you. Key Highlights AI as a thinking partner, not the pilot of the decision Use it to compress the research phase, not replace your judgment Turn AI into an adversarial analyst to surface your blind spots Hiring done right: crunch the thinking, never outsource the verdict Automation bias, anchoring, and groupthink are the real traps Write your own view down before you let AI speak first Know your patch before trusting AI in a domain you don't own Accountability never transfers to a model, it stays with the human Tools and Frameworks Mentioned Meta Muse Glimmer: Meta's newly released open weight model, benchmarking close to the current Qwen generation and marking their return to open source AI. RCTF Framework (Advancer): Llew's Role, Context, Task, Format prompt structure for briefing AI properly on complex decisions. DMAIC and the Deming Cycle: Classic lean process management frameworks James applies to structured, higher-quality decision making with AI. ⁠⁠ Shape the show ⁠⁠ Connect with the Hosts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CEO of Cadent. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Managing Director of Advancer at the AI Agency. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Zero Shot: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow us on LinkedIn for clarity in a complex landscape. Sponsor : This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Prompt Cowboy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , the agentic prompting tool that helps teams build structured, precise prompts before they hit whichever model they are using. Head to promptcowboy.ai and stop leaving results on the table. Produced by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Yennia La Rotta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ .⚡

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  Episode #27

  EP 27: Inside Fable 5 - How to Actually Use the Most Powerful AI Model Yet

  Jul 26, 202649 minS2

  Most people with access to the most powerful AI model available are using it at about two percent of what it can do. What would you do with the rest? In Episode 27 of ⁠ Zero Shot ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury ⁠ demystify Fable 5, Anthropic's most capable frontier model, and the class of model that now includes OpenAI's Sol and Moonshot's Kimi K3. This is not a hype reel. It is an honest, practical breakdown of what Fable actually unlocks, the finance and consulting work it can now do overnight, why it sometimes overthinks itself into hallucinating, and how to use it responsibly without burning through your token budget in an afternoon. Key Highlights Why Fable is built for persistent, thorough, long-running looping tasks The mental shift: forget what you assumed AI could not do Real use cases: overnight financial reports that took analysts weeks Higher effort is not always better, max effort can trigger hallucination Cost per task is the metric that now matters most Top and tail big jobs with a powerful model, workhorse in the middle Fable hands off sensitive domains like cybersecurity to Opus 4.8 Build redundancy, keep a fallback model ready if Fable goes dark Tools and Frameworks Mentioned Claude Fable 5 - Anthropic's most capable frontier model, built for orchestration, persistence, and deep multi-step work, now available on Max and Teams premium plans. Kimi K3 (Moonshot AI) - A 2.8 trillion parameter open weight model challenging the frontier at roughly eighty percent of the cost, with open weights targeted for release. ChatGPT with Sol 5.6 - OpenAI's flagship high-power model in the Fable class, benchmarked closely against Fable and strong on image generation. Cost Per Task - An emerging evaluation metric comparing dollar cost across models, useful for managing total cost of ownership as token prices climb. RCTF Framework (Ep 26 Zero Shot) - Role, Context, Task, Format prompt structure, essential for getting quality output from a model this powerful. Connect with the Hosts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CEO of Cadent. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Managing Director of Advancer at the AI Agency. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Zero Shot: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow us on LinkedIn for clarity in a complex landscape. Sponsor : This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Prompt Cowboy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , the agentic prompting tool that helps teams build structured, precise prompts before they hit whichever model they are using. Head to promptcowboy.ai and stop leaving results on the table. Produced by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Yennia La Rotta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ .⚡

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  Episode #26

  EP 26: Prompt Engineering - How to Actually Prompt AI and Stop Getting Average Answers

  Jul 19, 202655 minS2

  Why does AI give some people sharp, useful output and everyone else a generic, average answer? In Episode 26 of ⁠ ⁠ Zero Shot ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury ⁠ go deep on prompt engineering, the skill that separates people getting real value from AI and people quietly disappointed by it. The honest truth is it is almost never the model. The models are astonishing. It is the brief. This episode covers why prompts underperform at a technical level, the four pillars of a strong prompt, and how everything changes when you move from a single prompt to designing the full context environment of an AI agent. Key Highlights Why weak output is a briefing problem, not a model problem How a prompt reshapes the model's internal landscape of weights Making the implicit explicit is now a core professional skill The four pillars: role, context, task, format Set the role at world-class level to lift the output Less context done well beats more context done poorly The four parts of an agent brain: short memory, long memory, instructions, knowledge Prompting an agent is continuous improvement, not a one-time write Tools and Frameworks Mentioned RCTF Framework (Advancer) - Llew's prompt structure covering Role, Context, Task, and Format, designed to be printed and reused across a team. ChatGPT Work with Sol - OpenAI's flagship high-power model in its new work mode, reviewed live against Fable 5 for leadership briefing tasks. Hermes - An agent harness that prompts and improves itself between sessions, tuning its own skills and memory as a continuous improvement loop. Retrieval Augmented Generation and Data Lakehouses, The shift from classic RAG toward trusted single-source-of-truth architectures like Snowflake and Databricks for real business context. Shape the show: https://zeroshot.com.au/shape Connect with the Hosts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CEO of Cadent. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Managing Director of Advancer at the AI Agency. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Zero Shot: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow us on LinkedIn for clarity in a complex landscape. Sponsor : This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Prompt Cowboy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , the agentic prompting tool that helps teams build structured, precise prompts before they hit whichever model they are using. Head to promptcowboy.ai and stop leaving results on the table. Produced by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Yennia La Rotta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ .⚡

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  Episode #25

  EP 25: What AI Should Actually Be Doing in Your Business

  Jul 12, 202642 minS2

  How do you tell the difference between a task worth handing to AI and one that should stay human? In Episode 25 of Zero Shot ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury tackle the decision most businesses get wrong: choosing what to actually point AI at. The instinct is to reach for the shiny, visible task: customer service, the website, email, but that is rarely where the value lives. This episode gives you a practical way to sort any task in your business into three piles: hand it to AI, keep it human, or a bit of both. Five fast triggers to spot the real candidates, seven questions to run each one through, and an honest look at the cost of automating the wrong thing. Key Highlights Why your gut instinct to automate is usually the wrong target Automating a broken process just makes bad permanent, faster Failed early automations burn organizational trust and kill momentum The five triggers: repeat, sentence, dread, messy input, apology Let the AI do the dread work, not just the grunt work Seven questions that separate worth it from should we In regulated sectors, accountability is the governance question that matters The should conversation is where the real value lives Tools and Frameworks Mentioned Claude Fable - Anthropic's high-capability model, restored last week in a stripped-back format outside the US, referenced for producing report and website work that would take an analyst weeks. Gemma 4 (Google DeepMind) - Google's open source model, cited as the kind of on-hardware model deployed in high-classification defense settings where public models are not permitted. The REWIRE Framework (Advancer) - Advancer's method for AI transition, moving through Reveal, Envision, and Weave to test viability and feasibility before building. System 1 and System 2 Thinking - Daniel Kahneman's model, referenced by James to frame when to let AI steer a fast call versus when deep human judgment is required. Connect with the Hosts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CEO of Cadent. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Managing Director of Advancer at the AI Agency. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Zero Shot: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow us on LinkedIn for clarity in a complex landscape. 🤠 Sponsor : This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Prompt Cowboy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , the agentic prompting tool that helps teams build structured, precise prompts before they hit whichever model they are using. Head to promptcowboy.ai and stop leaving results on the table. Produced by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Yennia La Rotta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ .⚡

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  Episode #23

  EP 23: Beyond Automation: AI and the Future of Creative Work with Ben Cooper, R/GA

  Jun 27, 202652 minS2

  What if the way most people are using AI is actually the lowest value thing it can do? In Episode 23 of ⁠ Zero Shot ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury sit down with their second-ever guest, Ben Cooper, Global Executive Director of AI Products at R/GA and one of Australia's most original applied AI builders. From the world's first AI shark detection system to brand context protocols that make companies machine-readable, Ben shares a genuinely contrarian view: that the real value of AI is not generating faster and cheaper, but treating intelligence as a raw material you build with. This is an honest conversation about what survives contact with a real client, how creative work is priced and protected, and the human reckoning underneath the whole AI debate. Key Highlights Why treating intelligence as a material beats treating it as a tool 68 percent of brands now receive zero click traffic Large language models trust reviews and reputation over marketing speak Setting up AI to push back on you produces better outcomes Time, tools, and tokens are the new pricing variables Tangible demos make ideas unstoppable in the client room The backlash against AI is a needed correction, not just noise Personal agency, not the tool, is what takes you somewhere Tools and Frameworks Mentioned NotebookLM: Google's context-building tool for organising and connecting knowledge across projects Perplexity: AI-powered search and news discovery platform, personalised by topic and interest ElevenLabs: Voice AI platform used to train, license and scale branded voiceover at the production level Grok: xAI's model with native access to X (Twitter) data, useful for real-time knowledge mining Schema and Markdown Files: Foundational web standards that make a brand machine-readable and discoverable inside answer engines. Connect with the Hosts: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ James Gauci: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ CEO of Cadent. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Llew Jury: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Managing Director of Advancer at the AI Agency. ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Zero Shot: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Follow us on LinkedIn for clarity in a complex landscape. 🤠 Sponsor : This episode is brought to you by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Prompt Cowboy⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , the agentic prompting tool that helps teams build structured, precise prompts before they hit whichever model they are using. Head to promptcowboy.ai and stop leaving results on the table. Produced by ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Yennia La Rotta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ .⚡

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