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:

1. The Infinity Machine - Demis Hassabis - Amazon.com: The Infinity Machine: Demis Hassabis, DeepMind, and the Quest for Superintelligence: 9780593831847: Mallaby, Sebastian: Books
2. The Thinking Machine - Jensen Huang - The Thinking Machine: Jensen Huang, Nvidia, and the World's Most Coveted Microchip: Witt, Stephen: 9780593832691: Amazon.com: Books
3. Sapiens - Yual Noal Harari - Sapiens: A Brief History of Humankind eBook : Harari, Yuval Noah: Amazon.ca: Kindle Store
4. The Apple Podcast that I have curated - https://podcast.ashish-bhatia.com/feed.xml
5. 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

Get featured on the show by leaving us a Voice Mail: https://bit.ly/MIPVM 
 
AI is shifting from a tool to an operating system, enabling individuals to move faster, build bespoke solutions, and dramatically increase productivity. The biggest advantage now comes from curiosity, not technical depth. Those who experiment, learn a few tools deeply, and treat AI as a collaborator can compress hours into minutes and unlock new business models. Meanwhile, large organisations risk falling behind due to governance, inertia, and slow decision-making. 

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/835    

🎙️ What you’ll learn 

• Use AI as an operating system to replace and create software 
• Move from idea to working solution in minutes, not hours 
• Build capability by mastering a few tools, not chasing every new model 
• Apply curiosity-driven workflows to unlock better AI outcomes 
• Avoid common enterprise pitfalls around governance and tool sprawl 

✅ Highlights  

• "This software rewards the patient and the curious." 
• "Learn two or three of these tools really well." 
• "Are you using these tools to improve your quality of life or aren’t you?" 
• "This is the last software that I’ll ever train." 
• "We can create bespoke applications through any of these tools." 
• "It’s eating other software." 
• "People who choose to be left behind." 
• "From idea to iteration in 30 minutes." 
• "I feel like I’m becoming a bionic person." 
• "The barriers to entry are just gone." 

🧰 Mentioned 

• ChatGPT – https://chatgpt.com/ 
• Bing (Copilot Search) – https://www.microsoft.com/en-us/bing/copilot-search 
• Google – https://www.google.com 
• Gemini – https://gemini.google.com/ 
• Claude – https://claude.ai/ 
• Copilot – https://copilot.microsoft.com/ 
• Perplexity – https://www.perplexity.ai/ 
• Stability AI (Stable Diffusion) – https://stability.ai/ 
• Ethan Mollick (Wharton profile) – https://mgmt.wharton.upenn.edu/profile/emollick/ 
• Co-Intelligence (book) – https://www.penguinrandomhouse.com/books/741805/co-intelligence-by-ethan-mollick/ 
• Suno (AI music generator) – https://suno.com/ 

✅Keywords 
ai tools, generative ai, chatgpt, ai productivity, solopreneur ai, ai governance, llm workflows, ai operating system, automation, business ai, ai adoption, digital transformation 

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 explores why data governance must come before enabling Microsoft 365 Copilot, with insights from Khurram Hafeez. It breaks down how sensitivity labels, data loss prevention, and Microsoft Purview reduce the risk of unintended data exposure. You will hear practical guidance on preparing your environment, protecting sensitive information, and managing AI use across Microsoft tools and third‑party AI sites. The focus is on real‑world decisions organisations must make to safely adopt Copilot at scale.

🎙 Full Show Notes
https://www.microsoftinnovationpodcast.com/834

👉 What you’ll learn     

• Why Copilot increases the impact of poor data governance 
• How sensitivity labels affect what Copilot can access and summarise 
• When to use DLP versus inline DLP for AI risk management 
• How organisations can limit data sharing with third‑party AI tools 
• What licensing choices matter for Copilot and Purview governance 

✅ Highlights     

• “With the intro of the AI, the importance of the data governance compliance has much increased.” 
• “The first defense layer that you should be apply, that is the sensitivity label.” 
• “If a user doesn’t have permission, Copilot can’t actually extract the data.” 
• “Standard policy actually is not sufficient these days.” 
• “Users copy and paste or upload a sensitive file to third‑party AI sites.” 
• “Inline DLP policy is one step ahead of endpoint DLP policy.” 
• “Microsoft focus not to block something, to protect something.” 
• “Before enabling the copilot, they ensure that their environment is ready.” 
• “Copilot certainly honors the permissions the user have.” 

 🧰 Mentioned     

• Microsoft 365 Copilot: https://learn.microsoft.com/microsoft-365/copilot/ 
• Microsoft Entra Suite: https://www.microsoft.com/security/business/microsoft-entra-suite  
• E5 licence: https://www.microsoft.com/microsoft-365/enterprise/e5  
• Pay‑as‑you‑go Purview licensing: https://learn.microsoft.com/purview/purview-billing-models 
• ChatGPT: https://chatgpt.com/ 
• Gemini: https://gemini.google.com/ 
• DeepSeek: https://www.deepseek.com/  
• Microsoft MVP YouTube Series - How to Become a Microsoft MVP: https://www.youtube.com/playlist?list=PLzf0yupPbVkqdRJDPVE4PtTlm6quDhiu7 

✅ Keywords 
microsoft copilot, microsoft purview, data governance, sensitivity labels, data loss prevention, inline dlp, endpoint dlp, ai security, m365 e5, third party ai, information protection, enterprise ai 

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 

A practical rethink of how teams use Power Platform and Dynamics 365 to reduce technical debt, improve governance, and build sustainable solutions. The discussion centres on shifting from tech-first thinking to business outcomes, balancing low-code and pro-code principles, and preparing for AI and Copilot. The key insight is that long-term success comes from disciplined governance, reuse, and choosing when to adopt versus adapt. 

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/833

🎙️ What you’ll learn   

• Shift from technology-first to outcome-first solution design 
• Decide when to adopt vs adapt to reduce complexity 
• Apply coding principles inside low-code environments 
• Manage technical debt through governance and architecture 
• Evaluate where AI and Copilot add real value today 

✅ Highlights 

• "taking a step back and looking at business need and use a process rather than technology first." 
• "a term we're using in the department more and more is kind of adopt versus adapt." 
• "the more you’re restricting yourself off from these possibilities." 
• "it's treating it as a tool, a set of tools we can use rather than the default." 
• "governance to me means more preventative." 
• "it's really difficult to then stay on top of things like the Wave releases." 
• "it’s more a matter of time than anything." 
• "it's not the same thing as code, but it's not meant to be." 
• "there's still a level of maturity that we need to get to." 
• "what does Power Platform mean really and what is it there for?" 

 🧰 Mentioned 

• Power Virtual Agents (now part of Copilot Studio): https://www.microsoft.com/en-us/microsoft-copilot/blog/copilot-studio/microsoft-power-virtual-agents-now-part-of-microsoft-copilot-studio/ 
• AI Builder: https://learn.microsoft.com/en-us/ai-builder/overview 
• Copilot: https://copilot.microsoft.com/ 

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 explores how AI is accelerating both productivity and cyber risk. As attacks become faster and more automated, traditional perimeter security no longer holds. The conversation focuses on why organisations must assume compromise, adopt zero trust thinking, and build visibility before scaling AI. It highlights practical steps to govern AI use, reduce insider risk, and modernise access models beyond legacy VPNs. The core message is clear: embracing AI without security foundations can move your business backwards.

👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/832   

🎙️ What you’ll learn 

• Why AI has shortened breach timelines from days to minutes 
• How to shift from perimeter defence to a zero trust mindset 
• Practical ways to gain visibility over AI tools and data use 
• Where unplanned AI adoption creates insider risk 
• Why VPN-only security models struggle in cloud-first work 

✅ Highlights 

• “From the time of compromise to data exfiltration, we’re seeing 30 minutes.” 
• “Cybercrime is doing the same thing with AI that businesses are.” 
• “You can’t protect what you can’t see.” 
• “You can’t govern what you don’t know about.” 
• “We almost have to assume we’re going to get hit.” 
• “Security by obscurity doesn’t work anymore.” 
• “AI is introducing far more risk when there’s no planning.” 
• “Once you’re in with a VPN, there’s zero control on the inside.” 
• “The volume and scale and speed is what really concerns me.” 

🧰 Mentioned  

• Zero trust: https://learn.microsoft.com/security/zero-trust/zero-trust-overview 
• VPN (virtual private network): https://www.cisco.com/learn/topics/security/what-is-a-virtual-private-network-vpn.html  
• SASE (secure access service edge): https://www.microsoft.com/security/business/security-101/what-is-sase  
• Booz Allen: https://www.boozallen.com/  
• Gartner: https://www.gartner.com/en  
• Anthropic Claude: https://claude.ai/  

✅Keywords 
ai security, cybersecurity, zero trust, ai risk, data governance, cybercrime, vpn security, sase, insider risk, cloud security, ai adoption, threat landscape 

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 explores how business leaders are actually using AI inside organisations, and why adoption of tools like Microsoft 365 Copilot remains low. Chris shares practical insight from the frontline, covering Copilot strategy, Work IQ, agentic thinking, and how AI now enables teams to build internal tools faster than buying SaaS. The focus is not hype, but how to reimagine business models, reduce cost, and unlock new value with applied AI capability.

🎙️For full Show Notes  
https://www.microsoftinnovationpodcast.com/831 

👉 What you’ll learn     

• Why low Copilot adoption is an opportunity, not a failure 
• How to think beyond productivity to AI-enabled business models 
• When building internal AI tools beats buying SaaS 
• What Work IQ enables that other AI systems cannot 
• How agentic systems change OKRs, dashboards, and execution 

✅ Highlights     

• “AI is transformative, it is expensive, and it requires several years of exposure to capital budgets” 
• “It’s not just about doing things better, but doing things you never could do before” 
• “Microsoft is the largest commercial AI company on the planet” 
• “Copilot can orchestrate over your information in a way that other AI can’t” 
• “Work IQ would be a little bit better than the word graph” 
• “I love the term vibe coding” 
• “It would have been a couple of hundred thousand dollars two years ago” 
• “I’ve taken over two thousand dollars of subscription costs out of my business” 
• “They do exactly what I needed to do and no more” 

🧰 Mentioned     

• Microsoft 365 Copilot: https://www.microsoft.com/microsoft-365-copilot 
• Host - Polaris podcast: https://polaris.synozur.com 
• Co-Host Microsoft’s Intrazone podcast: https://aka.ms/TheIntrazone 
• Microsoft MVP YouTube Series - How to Become a Microsoft MVP - https://www.youtube.com/playlist?list=PLzf0yupPbVkqdRJDPVE4PtTlm6quDhiu7 

✅ Keywords      
ai adoption, microsoft copilot, work iq, agentic ai, internal tools, ai strategy, okrs, vibe coding, business transformation, saas replacement, applied ai, enterprise ai 

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 with Christian Segurado explores how agentic AI is reshaping ERP and enterprise delivery. The discussion covers deploying Copilot Studio agents in Teams, reducing ERP UI friction, accelerating fit gap and requirements work, and why multi agent orchestration matters. It focuses on where AI delivers real operational value today, the foundations required to unlock it, and what this shift means for people, process, and technology decisions in 2026. 

 👉 Full Show Notes
https://www.microsoftinnovationpodcast.com/830   

🎙️ What you’ll learn   

• How agentic AI changes how users interact with ERP systems 
• Where Copilot Studio and Azure Foundry fit in real implementations 
• How AI accelerates requirements gathering and fit gap analysis 
• Why clean data foundations are critical for agentic scenarios 
• What multi agent, multi model AI means for enterprise teams 

 ✅ Highlights 

• “ERP being actually more the layer on the back where the agent inquires knowledge” 
• “It is probabilistic, not deterministic” 
• “We are deploying is on Teams” 
• “It will fundamental change how we interact with the ERP” 
• “You cannot start with the roof if you don’t have the foundation” 
• “We have an agentic driven methodology” 
• “Consistency creates predictability” 
• “It does have a soul” 
• “Multi agent, multi model will be the norm” 

🧰 Mentioned 

• Dynamics 365: https://www.microsoft.com/dynamics-365 
• Copilot: https://www.microsoft.com/microsoft-copilot  
• Copilot Studio: https://www.microsoft.com/microsoft-365-copilot/microsoft-copilot-studio  
• Azure Foundry (Microsoft Foundry): https://ai.azure.com  
• Microsoft Fabric: https://www.microsoft.com/microsoft-fabric  
• Medallion architecture: https://learn.microsoft.com/azure/databricks/lakehouse/medallion  
• Azure DevOps: https://azure.microsoft.com/products/devops  
• Microsoft Learn: https://learn.microsoft.com  
• Microsoft Mesh: https://www.microsoft.com/microsoft-mesh

✅Keywords   
agentic ai, erp, dynamics 365, copilot studio, microsoft teams, multi agent systems, enterprise ai, ai governance, fit gap analysis, microsoft power platform, azure foundry, digital transformation 

If you want to get in touch with me, you can message me here on Linkedin.

Thanks for listening 🚀 - Mark Smith