The Intelligence Age

Build AI That Works

Full Show Notes
https://www.theintelligenceagepodcast.com/840

Mark Smth talks with James Diekman about how Accelerate Tech has scaled, where AI is actually creating value in government workflows, and why most successful projects are targeted workflow changes rather than broad rollout tools. They also dig into Australia’s growing caution around AI governance, data residency, and the practical push toward local models and sovereign infrastructure.

We discuss how AI is being used inside engineering and marketing, why many Copilot-style deployments lose momentum, and how project management itself may evolve as agents take on governance, reporting, and coordination tasks. James shares what’s working in production, what keeps failing before launch, and where the next 6 to 12 months of AI adoption is heading.

Key topics
James Diekman shares that Accelerate Tech has grown to about 32 staff in the last six months, driven by demand in government projects and AI-enabled solutions.
The conversation contrasts AI use in engineering and marketing versus more passive consumption in functions like HR and finance.
James explains that the strongest results come from embedding AI into specific workflows, rather than treating it as a standalone chatbot or a broad deployment.
They discuss why many Copilot rollouts see mixed adoption and usage drop-off when the tool sits outside the daily workflow.
James describes the most successful approach as identifying a business process, pulling apart a sub-workflow, and then applying AI, automation, or judgment-based reasoning to that narrow area first.
He notes that many AI projects never reach production, and says that out of 30-plus AI projects delivered, only five or six have made it fully into production.
The discussion turns to local government systems, with James outlining how his team often acts as the integration layer, or “the plumbers,” between older council platforms and newer software.
They cover Australia’s increasing AI governance maturity, including state frameworks, federal requirements, and the rise of dedicated AI roles inside agencies.
Mark and James debate public concerns around data centers, water use, and energy, with James emphasizing the need for better policy and the practical constraints of local compute.
They explore the move toward local models, onshore hosting, and reserving compute capacity as organizations seek more control, lower risk, and better throughput.
James makes the case that teams do not always need frontier models like Opus for every task and that model choice should match the job, cost, and risk.
The episode closes on project management, where James outlines a “project brain” concept using agents, shared knowledge, registers, ticketing, and workflow automation to support or partially replace manual PM effort.
If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Full Show Notes
https://www.theintelligenceagepodcast.com/839
Mark Smth speaks with Ashish Bhatia about how his move from Microsoft to Audible changed the way he thinks about customers, AI, and product design. The conversation centers on personal AI, running OpenClaw locally, and why owning your memory, workflows, and data matters more as AI systems become more capable.

They also explore Audible’s role in learning, the future of interactive audio, and how agents are beginning to replace clunky app-based workflows with more direct, personalized experiences.

Key topics
Ashish explains the shift from B2B at Microsoft to B2C at Audible, and how that changes the way you learn from customers
He shares why personal AI matters to him more than ever, especially when it involves health data, finances, and memory
Mark describes building a large OpenClaw setup with 26 agents, including a nine-agent DevOps team and automated bug fixing
They discuss why running AI locally teaches real systems thinking through failure, debugging, and repeated iteration
Ashish talks about using OpenClaw to manage daily life, including lunch ordering through Grubhub as a mission-critical workflow
The conversation highlights the importance of owning your memory and being able to move your AI system across machines and platforms
They explore the idea of the death of UI, where agents increasingly bypass app interfaces and handle tasks directly
Mark raises concerns about AI companies ingesting books and content, leading to a discussion of copyright, hypocrisy, and cultural attitudes toward books
Ashish shares how Audible supports different learning styles, especially for commuters, slow readers, and people who learn better through audio plus text
He outlines Audible’s direction toward interactive, multilingual audiobooks with AI-powered recall, discovery, and personalization
Resource Recommendations:
The Infinity Machine - Demis Hassabis - Amazon.com: The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence: 9780593831847: Mallaby, Sebastian: Books
The Thinking Machine - Jensen Huang - The Thinking Machine: Jensen Huang, Nvidia, and the World's Most Coveted Microchip: Witt, Stephen: 9780593832691: Amazon.com: Books
Sapiens - Yual Noal Harari - Sapiens: A Brief History of Humankind eBook : Harari, Yuval Noah: Amazon.ca: Kindle Store
The Apple Podcast that I have curated - https://podcast.ashish-bhatia.com/feed.xml
Ashish Bhatia's website - ashish-bhatia.com
If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Full Show Notes
https://www.theintelligenceagepodcast.com/838

AI is about to replace bloated SaaS, and most businesses are still only playing with chatbots

Sean G Muller says the next wave of AI is not about better prompts or prettier copilots. It is about rebuilding business around context, agents, and what actually creates value - before your software stack becomes the expensive middleman.
Mark Smth and Sean unpack why the last six months have been a genuine shift: agentic loops are now good enough to handle real business work, not just experiments. Sean explains how he moved from traditional technical architecture into building full application pipelines, MCP servers, and background agents that review email, track social signals, draft responses, and keep business moving without adding more human overhead.

You'll discover why context is the missing ingredient in almost every failed AI project, how Sean uses a simple meal-planning example to explain it, and why companies that scatter knowledge across laptops, SharePoint, Google Cloud, and people's heads are sitting on hidden risk. Sean also breaks down the difference between AI as a feature and AI as a business transformation engine, including the mistake many firms make when they bolt chat onto old workflows and call it progress.

We also get into the coming SaaS pocalypse - the idea that tools like HubSpot, Salesforce, Xero, Slack, and Atlassian may face a serious reckoning as businesses realize they can build leaner, custom, agent-first systems for less than the cost of endless licenses and modules. Sean shares how he built a headless, agent-driven CRM and why he thinks greenfield builds will replace expensive transformation projects much sooner than most executives expect. This conversation matters if you lead a business, run operations, own a small or mid-sized company, or simply suspect your current software is forcing you to work the wrong way. If you want to understand where AI is actually delivering leverage right now - and how to avoid wasting money on shallow pilots - this episode is essential listening.

Mark Smth hosts the conversation and brings the enterprise and product lens, pushing Sean to get specific about what success looks like for real businesses in New Zealand.

Sean G Muller is an AI and enterprise architecture specialist based in New Zealand, known for helping organizations build practical AI systems, implement agentic workflows, and rethink business process from the ground up.

Resources
1. The Cuckoo's Egg: Tracking a Spy Through the Maze of Computer Espionage - https://www.amazon.com.au/dp/0385249462?ref_=mr_referred_us_au_nz
2. Gemini: A Family of Highly Capable Multimodal Models — 2312.11805.pdf ⁠https://arxiv.org/abs/2312.11805
3. On the Measure of Intelligence — 1911.01547.pdf - https://arxiv.org/pdf/1911.01547
If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM

AI adoption fails when it stops at access to tools. This episode introduces a practical model that bridges the gap between AI tools like Copilot and measurable business outcomes. The focus shifts from technology to people, addressing key blockers such as time, confidence, and relevance. By grounding AI in real workflows, tailoring role-specific use cases, and measuring outcomes, organisations can move from low usage to meaningful impact fast.

🎙 Full Show Notes
https://www.microsoftinnovationpodcast.com/837
👉 What you’ll learn     
Identify the real blockers stopping AI adoption in teams 
Shift from tool access to measurable business outcomes 
Design role-specific AI use cases that drive daily value 
Build AI training that fits real work, not theory 
Measure AI adoption with practical KPIs and usage data 
✅ Highlights     
"These two things are very, very different" 
"Some things really need to happen in between those two places" 
"This is not about the tech. This is about the people" 
"They didn't know how to use the tool" 
"They didn't know what they were allowed to do" 
"When would they sit and just learn a link" 
"To actually tailor use cases that are relevant" 
"We have to measure how they are moving" 
"We moved a department from 15% to 83%" 
"It shifts how you are working" 
🧰 Mentioned     
Microsoft Copilot (https://copilot.microsoft.com/)  
Copilot Notebooks (https://support.microsoft.com/en-us/topic/get-started-with-microsoft-365-copilot-notebooks-0775e693-11c6-4d80-8aba-fcc81a737a06)  
ChatGPT (https://chatgpt.com/)  
AI Boost Academy (https://hannabergstrom.com/) [ 
Vattenfall (https://group.vattenfall.com/) 
Microsoft MVP YouTube Series - How to Become a Microsoft MVP - https://www.youtube.com/playlist?list=PLzf0yupPbVkqdRJDPVE4PtTlm6quDhiu7 
✅ Keywords      
ai adoption, copilot, generative ai, ai training, business transformation, ai use cases, digital productivity, ai skills, organisational change, ai strategy, workplace efficiency, ai literacy 
If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM 
 
This episode dives into why large CRM and ERP projects keep failing and how AI is reshaping consulting, software delivery, and platform decisions. The core insight is simple. Organisations fail when they buy software instead of outcomes. With AI, experienced teams can move faster, strip away legacy complexity, and build only what the business actually needs. The conversation explores outcome-based thinking, flawed RFP processes, and why AI is accelerating the gap between great and average practitioners. 
👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/836   

🎙️ What you’ll learn   
How to frame technology decisions around outcomes, not vendors or features 
Why traditional RFP processes drive cost blowouts and failed projects 
The four core business problems most systems are really trying to solve 
How AI tools are changing the speed and shape of consulting work 
When building custom solutions now beats buying off-the-shelf software 
✅ Highlights 
“So many people are still buying software like it’s a software decision rather than a business decision.” 
“You’re really only trying to solve one of four business problems.” 
“Most organizations aren’t even thinking in terms of what is the root of what I’m trying to solve.” 
“Your highest qualified people are not even in the game because you’ve already excluded quality.” 
“AI is now to the developer what Visual Studio was in the 90s.” 
“It made the good developers really good and the bad developers a lot faster.” 
“Low code was developed because we couldn’t get enough developers.” 
“There’s a third option now, and that is vibe code your own add-on.” 
“I think we’re less than 18 months away from this changing enterprise software.” 
🧰 Mentioned 
Microsoft Power Platform: https://learn.microsoft.com/power-platform  
Microsoft Dynamics CRM (Dynamics 365 CRM):
https://www.microsoft.com/dynamics-365/solutions/crm  
Microsoft Business Central:
https://www.microsoft.com/dynamics-365/products/business-central  
Microsoft Finance and Operations (Dynamics 365 Finance):
https://www.microsoft.com/dynamics-365/products/finance 
Notebook LM: https://notebooklm.google  
LinkedIn Sales Navigator: https://business.linkedin.com/sales-solutions/sales-navigator 
DynamicConsultantsGroup.com: https://dynamicconsultantsgroup.com 
✅Keywords   
ai in consulting, outcome-based software, crm failures, erp projects, power platform, low code vs pro code, vibe coding, rfp process, enterprise software, applied ai skills, digital transformation, consulting strategy
If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith