ZERO SHOT - AI & Business. Anti-Hype.

Glass Box

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 & Digital Produced by Yennia La Rotta.

  1. 5d ago

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

    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 decisionUse it to compress the research phase, not replace your judgmentTurn AI into an adversarial analyst to surface your blind spotsHiring done right: crunch the thinking, never outsource the verdictAutomation bias, anchoring, and groupthink are the real trapsWrite your own view down before you let AI speak firstKnow your patch before trusting AI in a domain you don't ownAccountability 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.⚡

  2. Aug 9

    EP 29: AI Agents for Business - What They Are and When to Deploy One

    You have probably nodded along in a meeting about autonomous AI agents without being totally sure what one actually is. You are not alone. In Episode 29 of ⁠ ⁠⁠Zero Shot⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠James Gauci⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Llew Jury ⁠⁠ cut through the most hyped and least understood term in AI right now: the agent. This is the honest, no-jargon picture of what an AI agent really is, how you actually build one, where they earn their keep in a business, and where they quietly fall apart. From the difference between a chatbot, an automation, and a truly autonomous agent, to why roughly forty percent of agent projects get pulled, this episode gives you a clear way to decide what to hand an agent and what to keep a human on. Key Highlights Autonomy is a dial, not a switch, and it defines what makes an agentThe bright line: does it make a plan and use tools on its ownModel plus context, prompt, tools, and memory equals an agentChatbots and automations are often mislabelled as agentsMost failed agent projects die from hype and poor scoping, not techHigh performers gain from AI, low performers can go backwardsBefore you hand over a task, ask how costly it is to catch and fixTreat an agent like an employee, not an experimentTools and Frameworks Mentioned ⁠Claude Cowork⁠ - Anthropic's agentic harness, now available in the browser, that plans and executes multi-step work rather than just answering. ⁠n8n⁠ - Workflow automation builder with new native MCP support and human-in-the-loop approval steps, bridging automation and agentic AI. ⁠Model Context Protocol (MCP)⁠ — The open standard connecting agents to your key data and systems, now supported natively across major automation tools. ⁠Microsoft Azure CLI⁠ - A command line tool used with Claude Code to programmatically build agents and sandbox environments. ⁠OECD⁠ AI System Definition - The framework James uses to scope agents, defining an AI system by its degrees of autonomy and adaptiveness after deployment. ⁠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.⚡

  3. Jul 26

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

    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 tasksThe mental shift: forget what you assumed AI could not doReal use cases: overnight financial reports that took analysts weeksHigher effort is not always better, max effort can trigger hallucinationCost per task is the metric that now matters mostTop and tail big jobs with a powerful model, workhorse in the middleFable hands off sensitive domains like cybersecurity to Opus 4.8Build 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.⚡

  4. Jul 19

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

    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 problemHow a prompt reshapes the model's internal landscape of weightsMaking the implicit explicit is now a core professional skillThe four pillars: role, context, task, formatSet the role at world-class level to lift the outputLess context done well beats more context done poorlyThe four parts of an agent brain: short memory, long memory, instructions, knowledgePrompting an agent is continuous improvement, not a one-time writeTools 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.⚡

  5. Jul 12

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

    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 targetAutomating a broken process just makes bad permanent, fasterFailed early automations burn organizational trust and kill momentumThe five triggers: repeat, sentence, dread, messy input, apologyLet the AI do the dread work, not just the grunt workSeven questions that separate worth it from should weIn regulated sectors, accountability is the governance question that mattersThe 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.⚡

  6. Jul 5

    EP 24: Process Automation with AI Agents - How to Think Before You Build

    What actually changed between the automations businesses built ten years ago and the AI agents being built today? In Episode 24 of Zero Shot⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠James Gauci⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Llew Jury go back to first principles on process automation. They trace the shift from rigid, rules-based workflows to AI agents that reason over messy, unstructured data, and unpack what that unlocks for automation, autonomy, and agentic workflows inside real organisations, including regulated and compliance heavy sectors. It is a durable mental model for deciding what to build and when, not a tool tour that dates in six months. Key Highlights Automation no longer requires structured data to be usefulDeterministic rules have given way to systems that reasonAutomation and autonomy are different capabilities that nest togetherData lakehouses feed agents directly through MCP connectionsReal time finance agents end month end reconciliation waitsRegulated sectors can build sovereign, onshore, fully controlled AIThe four Ps framework leaves tool selection until lastStart with the messiest high value process first Tools and Frameworks mentioned in this episode OpenWhispr, open source dictation that runs speech models locally with no data egress. Model Context Protocol (MCP), the open standard for connecting agents to data sources like lakehouses. Microsoft 365 Copilot Cowork, the agentic layer inside Copilot for scheduled, delegated work. Data lakehouse architecture, the blended structured and unstructured data foundation agents feed on. Widely documented across major cloud platforms.The Four Ps, Llew's sequence of problem, people, process, then product for automation projects. A working framework from the episode. 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.⚡

  7. Jun 27

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

    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 tool68 percent of brands now receive zero click trafficLarge language models trust reviews and reputation over marketing speakSetting up AI to push back on you produces better outcomesTime, tools, and tokens are the new pricing variablesTangible demos make ideas unstoppable in the client roomThe backlash against AI is a needed correction, not just noisePersonal agency, not the tool, is what takes you somewhereTools and Frameworks Mentioned NotebookLM: Google's context-building tool for organising and connecting knowledge across projectsPerplexity: AI-powered search and news discovery platform, personalised by topic and interestElevenLabs: Voice AI platform used to train, license and scale branded voiceover at the production levelGrok: xAI's model with native access to X (Twitter) data, useful for real-time knowledge miningSchema 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.⚡

  8. Jun 21

    EP 22: Frameworks for Using AI Right - The Questions to Ask Before You Start

    What are the questions worth asking before you trust AI with anything important in your business? In Episode 22 of Zero Shot⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ , ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠James Gauci⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Llew Jury lay out the practical frameworks they wish someone had handed them when they started: the questions to ask before you choose a tool, before you trust an output, and before you scale AI across an organisation. Broken into three clear acts, before you start, before you trust, and before you scale, this episode is a working checklist for making AI decisions that protect your business, your data, and your customer relationships. Honest, specific, and grounded in real consulting experience across regulated and high-stakes sectors. Key Highlights Start with the problem, not the tool or the modelOnly two to five percent of businesses are doing real AITool choice matters less than people, process, and data alignmentTurning off model training is the first trust stepData hosted in Australia can still be subject to US lawGovernance done right is a value driver, not a costAccountability across the team costs almost nothing to implementPick any decision making framework, the act of choosing matters mostTools and Frameworks Mentioned Open Whisper: Free, open source dictation tool that runs the model locally on your device, keeping sensitive audio off the cloud. Excalidraw: Collaborative virtual whiteboard for diagrams and mind mapping, with an MCP connector that lets Claude design directly into the canvas. ISO 42001: The international standard for AI management systems, referenced as a practical starting framework for businesses building AI governance. National AI Centre Frameworks: Australian government resources and policies offering free, credible starting points for small businesses building AI governance and usage policies. NextDC: Australian data centre operator referenced in the discussion on data sovereignty and onshore hosting for sensitive workloads. 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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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 & Digital Produced by Yennia La Rotta.

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