Tech Talks Daily

What happens when the weakest link in your technology supply chain becomes the entry point for a national security incident?
In this episode of Tech Talks Daily, I welcome back Haydn Brooks, CEO and founder of Risk Ledger, to discuss why supply chain security has moved from an IT concern to a boardroom and government priority. As organizations race to adopt AI, connect more systems, and depend on increasingly complex ecosystems of vendors, partners, cloud providers, and third-party services, the attack surface continues to expand in ways many businesses still struggle to understand.
Haydn explains why supply chains remain one of the largest blind spots in cybersecurity, despite years of warnings and a growing list of high-profile incidents. We explore how attackers increasingly target smaller suppliers that lack the resources and expertise of larger enterprises, using them as stepping stones to reach critical infrastructure, government agencies, and major corporations.
The conversation also examines how AI is reshaping the risk equation. As organizations rapidly integrate AI tools, APIs, and third-party models into existing technology stacks, many are creating new forms of concentration risk. What happens when multiple services rely on the same AI provider? And how can businesses maintain visibility over technology dependencies that are constantly evolving?
Haydn shares his perspective on why collaboration and information sharing have become far more common across the cybersecurity community, and why security leaders are beginning to recognize that defending against modern threats requires collective action rather than isolated efforts. We also discuss accountability, resilience, and why organizations must move beyond simply identifying risk and develop the ability to understand the impact of incidents when they occur.
Along the way, Haydn offers practical advice for security leaders, explains why now is the time to reassess supply chain security strategies, and shares insights into Risk Ledger's international expansion as the company grows its presence in the United States.
As AI accelerates innovation and organizations become increasingly interconnected, are businesses truly prepared for the risks that come with that progress? And could an overlooked supplier become the starting point for the next major cybersecurity crisis?

Have you ever stopped to think about the technology powering almost every text box you interact with online?
Whether you're applying for a job, drafting a legal contract, publishing content, or updating a website, there's a good chance a rich text editor is quietly working behind the scenes. In this episode of Tech Talks Daily, I caught up with Fredrik Danielsson, Product Manager at TinyMCE, to discuss how one of the internet's most widely used editing platforms is evolving for the AI era.
Frédéric shares the remarkable story behind TinyMCE, a tool that traces its roots back to the early days of the web and has played a role in creating much of the internet's human-generated content. From the days of hand-coded websites and Flash applications to today's AI-powered content workflows, we explore how the company has continually adapted to changing developer and user needs.
Our conversation focuses on the launch of TinyMCE AI and why the company believes artificial intelligence belongs inside the content creation experience rather than in a separate chatbot window. We discuss the hidden productivity costs of constantly switching between applications, copying and pasting content between AI assistants and business tools, and why bringing AI directly into the editor creates a more natural and efficient workflow.
We also examine the growing challenges around AI governance, content ownership, compliance, and accountability. As organizations race to adopt AI tools, how can they maintain visibility into which content was AI-assisted, who made changes, and how information flows through the business? Frédéric explains why features such as revision history, track changes, and audit trails may become increasingly important as regulations and expectations mature.
Along the way, we discuss context-aware AI, model flexibility, developer experience, and the future of content creation. Frédéric also shares his thoughts on why AI adoption is becoming more natural for everyday users and what the next phase of AI-powered productivity could look like as these tools become deeply embedded in the software people already use.
If AI is changing how we create, edit, review, and collaborate on content, what happens when the editor itself becomes the smartest participant in the room? And how will that reshape the way we work over the next few years?

Have you ever wondered why political campaigns can send millions of text messages but still struggle to have meaningful conversations with voters?
In this episode of Tech Talks Daily, I sit down with Tom Carroll, Co-Founder of Convos, a startup rethinking how political campaigns communicate through SMS. While political texting has become a standard part of modern campaigning, Tom argues that the industry has spent years solving the problem of message delivery while largely ignoring what happens when voters actually respond.
We explore how Convos is building a conversational SMS infrastructure that helps campaigns manage thousands of voter interactions simultaneously. Rather than focusing solely on message volume, the platform analyzes replies, identifies sentiment and alignment, prioritizes urgent conversations, and helps campaigns understand what voters are really talking about. Tom shares how this approach is helping campaigns move beyond one-way broadcasts and toward genuine engagement at scale.
During our conversation, we discussed why traditional political texting often breaks down once campaigns begin receiving large volumes of replies, how AI-powered conversational systems can help manage those interactions responsibly, and why transparency remains essential when introducing AI into political communications. Tom also explains how Convos uses campaign-approved knowledge bases and multiple validation checks to reduce misinformation and maintain message consistency.
We also examine the broader implications of conversational AI in politics, from voter education and turnout efforts to balancing automation with authenticity. Tom shares examples of how campaigns have used conversational SMS to answer voter questions, provide election information, and create opportunities for meaningful engagement without overwhelming campaign staff.
As AI continues to influence how organizations communicate with large audiences, this conversation offers an interesting look at how technology can help people listen at scale rather than talk louder.
What role should AI play in political engagement, and where should the line be drawn between helpful voter communication and automated persuasion? Share your thoughts and join the conversation.

How do you move beyond AI experimentation and start building systems that can genuinely reason, act, and create value across an enterprise?
Recorded at Adobe Summit in Las Vegas, this episode features Daniel Sheinberg, who leads cross-portfolio product initiatives for Adobe's Customer Experience Orchestration business.
Daniel is at the center of Adobe's AI and agentic strategy, helping shape how some of the world's largest organizations think about the next generation of customer experiences.
During our conversation, Daniel cuts through the hype surrounding agentic AI and explains what actually separates an AI assistant from an AI agent.
We explore how advances in reasoning, memory, context awareness, and tool usage are enabling systems that can move beyond generating content to actively helping organizations achieve business goals. Daniel shares practical examples of how enterprises are using these capabilities to personalize customer journeys at a level that would have been impossible with traditional workflows.
We also discuss the rise of AI-powered brand concierges, including how are using agentic experiences to create more meaningful customer interactions.
Daniel explains why context is becoming one of the most valuable assets in enterprise AI, how businesses can prepare their data and systems for agentic workflows, and why governance, trust, and brand intelligence will play such an important role in successful deployments.
If you're trying to understand where AI is heading next, what customer experience orchestration really means, and how businesses can safely deploy agentic AI at scale, this conversation offers a valuable look at both the opportunities and the challenges ahead.

What does better analytics actually mean when your mission is protecting the planet?
At SAS Innovate, I sat down with John Blackwell, Director of Strategic Analytics at The Nature Conservancy, to explore how data, AI, and marketing intelligence are helping one of the world's largest conservation organizations raise more money, operate more efficiently, and ultimately direct more resources toward protecting land, water, and ecosystems across more than 80 countries.
In this episode, John explains how analytics has become a critical part of modern conservation strategy. With fundraising supporting everything from habitat protection to climate resilience projects, improving donor retention and increasing fundraising efficiency directly impacts how much work The Nature Conservancy can do around the world. John shares how the organization improved donor retention by 10 percent and increased year-over-year giving by 30 percent by moving away from siloed systems and toward a more connected, data-driven approach.
We discuss how analytics helps identify long-term donor potential, personalize supporter journeys, optimize fundraising asks, and create a clearer 360-degree view of donor engagement across email, direct mail, telemarketing, and digital channels. John also explains why personalization in the nonprofit world requires a very different balance than in commercial marketing. Trust and authenticity matter just as much as performance metrics.
The conversation also explores how AI is quietly changing the way nonprofit analytics teams operate. From speeding up model development to improving feature selection and identifying rare high-value donor opportunities through synthetic data generation, John shares where he sees AI creating immediate practical value without compromising the human voice of the organization.
What stood out most to me is how this is ultimately a story about efficiency creating impact. The more effective The Nature Conservancy becomes at fundraising and donor engagement, the more money can go directly toward conservation rather than operational overhead.
And in a world where every nonprofit is competing for attention, funding, and trust, analytics may quietly become one of the most important tools available for protecting the future of our planet.
So, as organizations continue investing in AI and analytics, are they focusing enough on the real-world outcomes those technologies can help create?