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Tech Talks Daily

If every company is now a tech company and digital transformation is a journey rather than a destination, how do you keep up with the relentless pace of technological change?

Every day, Tech Talks Daily brings you insights from the brightest minds in tech, business, and innovation, breaking down complex ideas into clear, actionable takeaways.

Hosted by Neil C. Hughes, Tech Talks Daily explores how emerging technologies such as AI, cybersecurity, cloud computing, fintech, quantum computing, Web3, and more are shaping industries and solving real-world challenges in modern businesses.

Through candid conversations with industry leaders, CEOs, Fortune 500 executives, startup founders, and even the occasional celebrity, Tech Talks Daily uncovers the trends driving digital transformation and the strategies behind successful tech adoption. But this isn’t just about buzzwords.

We go beyond the hype to demystify the biggest tech trends and determine their real-world impact. From cybersecurity and blockchain to AI sovereignty, robotics, and post-quantum cryptography, we explore the measurable difference these innovations can make.

Whether improving security, enhancing customer experiences, or driving business growth, we also investigate the ROI of cutting-edge tech projects, asking the tough questions about what works, what doesn’t, and how businesses can maximize their investments.

Whether you’re a business leader, IT professional, or simply curious about technology’s role in our lives, you’ll find engaging discussions that challenge perspectives, share diverse viewpoints, and spark new ideas.

New episodes are released daily, 365 days a year, breaking down complex ideas into clear, actionable takeaways around technology and the future of business.

Copyright: © Neil C. Hughes - Tech Blog Writer 2015

Latest Episodes:

3416: DEUNA: From One-Click Checkout to Intelligent Payments Infrastructure Sep 10, 2025

Show notes

Here's the thing. Payments only look simple from the outside. In this Tech Talks Daily episode, I sit down with Roberto "Reks" Kafati, CEO and co-founder of DEUNA, to unpack how a scrappy one-click checkout idea grew into an intelligent payments infrastructure that now touches a large slice of Mexico's online economy.

Reks explains why Latin America's high decline rates aren't just an inconvenience but a growth killer, and how DEUNA's early focus on orchestration and checkout opened the door to something bigger. When a region routinely sees more than four out of ten online transactions knocked back, the bar for reliability sits in a different place. That practical problem set the stage for what came next.

Athia, Real-Time Decisions, and 638 Signals per Transaction

DEUNA's pivot point came when merchants asked a fair question. With all this payment data flying through the system, what should we do with it? The answer is Athia, DEUNA's AI-powered layer that watches every transaction and feeds merchants real-time insight, routing choices, and suggested actions.

It is not another dashboard you promise to check and then ignore by Friday. It is a reasoning engine that sits on top of 638 data points per transaction and turns mess into movement. That is how you recover revenue without punishing good customers with extra friction, how you avoid surprise fees from networks, and how you protect recurring revenue when a processor wobbles. Reks walks us through results that speak plainly.

Ramped merchants saw conversion lift from the original one-click experience. The infrastructure tier recovers meaningful GMV and trims fees. Enterprise clients report double-digit ROI and stick around for the compounding effect.

Building Through Adversity and Betting on the Right Layer

What resonated most was the human story behind the metrics. DEUNA was born in the first months of the pandemic, shaped by the shock that hit real-world businesses when revenue fell off a cliff and marketplaces became a lifeline with strings attached. Reks shares an unvarnished look at a tough 2023, the kind of year founders rarely talk about on record.

Revenues dipped, deals went sideways, life got complicated. The team chose resilience and doubled down on a two-year vision. That bet is paying off. Over the past twenty-four months the company has grown at a pace that would bend a chart, and the focus has shifted from commoditizing orchestration to productizing intelligence. Put simply, earn trust at checkout, then make the data work for the merchant in real time.

Agentic Commerce, US Expansion, and What Comes Next

We also look forward. If chat interfaces begin to mediate more buying decisions, merchants will need infrastructure that can think, not just connect endpoints. That is the territory DEUNA calls intelligent infrastructure, and it is where Athia operates every day.

The company is now in active conversations with major US retailers, confident after winning head-to-head enterprise evaluations. Reks frames the opportunity without hype. If you can see acceptance trends by processor, by country, by card type, and act in the moment, you keep customers, protect margins, and avoid death by a thousand false declines. If you cannot, competitors will gladly welcome your frustrated shoppers.

If you care about the real mechanics of growth, this conversation is for you. We talk conversion lift, recovered revenue, and the gritty bits of building a payments company that merchants actually rely on. We also talk about the days that test your resolve and the tenth day that reminds you why you started.

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3415: Secure GenAI for SAP: Syntax Systems CodeGenie on BTP Sep 09, 2025

Show notes

I sat down with Leo de Araujo, Head of Global Business Innovation at Syntax Systems, to unpack a problem every SAP team knows too well.

Years of enhancements and quick fixes leave you with custom code that nobody wants to document, a maze of SharePoint folders, and hard questions whenever S/4HANA comes up. What does this program do. What breaks if we change that field. Do we have three versions of the same thing. Leo's answer is Syntax AI CodeGenie, an agentic AI solution with a built-in chatbot that finally treats documentation and code understanding as a living part of the system, not an afterthought.

Here's the thing. CodeGenie automates the creation and upkeep of custom code documentation, then lets you ask plain-language questions about function and business value. Instead of hunting through 40-page PDFs, teams can ask, "Do we already upload sales orders from Excel," or "What depends on this BAdI," and get an instant explanation. That changes migration planning. You can see what to keep, what to retire, and where standard capabilities or new extensions make more sense, which shortens the path to S/4HANA Cloud and helps you stay on a clean core.

We also talk about how this is delivered. CodeGenie runs on SAP Business Technology Platform, connects through standard APIs, and avoids intrusive add-ons. It is compatible with SAP S/4HANA, S/4HANA Cloud Private Edition through RISE with SAP, and on-premises ECC. Security comes first, with tenant isolation for each customer and no custom code shared externally or used for AI model training. The result is a setup that respects enterprise guardrails while still giving developers and architects fast answers.

Clean core gets a plain explanation in this episode. Build outside the application with published APIs, keep upgrades predictable, and innovate at the edge where you can move quickly. CodeGenie gives you the visibility to make that real, surfacing what you actually run today and how it ties to outcomes, so you can design a migration roadmap that fits the business rather than guessing from stale documents.

Leo also previews the Gen AI Starter Pack, launching September 9. It bundles a managed, model-flexible platform with workshops, use-case ideation, and initial builds, so teams can move from curiosity to working solutions without locking themselves into a single provider. Paired with CodeGenie and Syntax's development accelerators, the Starter Pack points toward something SAP leaders have wanted for years, a practical way to shift from in-core customizations to clean-core extensions with much less friction.

If you are planning S/4HANA, balancing hybrid and multi-cloud realities, or simply tired of tribal knowledge around critical programs, this conversation is for you. We get specific about how CodeGenie works, where it saves time and cost, and how Syntax is shaping a playbook for AI that helps teams deliver results they can trust.

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3414: Self-Healing Machines and Robotics with Grace Technologies Sep 08, 2025

Show notes

Drew Allen, CEO of Grace Technologies, shares real stories from the floor, the ideas shaping safer plants, and why culture matters more than slogans. Drew's background stretches from a family line linked to Samuel Morse to teenage years in China to global business development at 3M. That range shows up in how he leads. He listens, he moves fast, and he expects teams to work on things that matter. In his world that means saving electricians from shocks and arc flash while helping manufacturers modernize without losing their soul.

Grace started with mechanical and analog products, then took the hard road into fully digital systems. The shift took time and patience. Today their platform brings sensors, AI, and cloud tooling into maintenance and safety. The example that stuck with me is a proximity band for electricians. It lights, beeps, and vibrates as a worker approaches live voltage. At TriCity, that band prevented three near misses in a three month pilot.

A fourth incident still ended in a hospital visit and a costly outage because the worker left the band in his car. Another apprentice nearly placed a hand on a live bus bar until the band told him something was wrong. These moments remind you that technology can change a day and a life.

Drew's take on culture is refreshingly direct. Values are not a poster. They are a filter for who you hire. He looks for customer obsession, ownership, curiosity, and candid communication. Then he pairs that with high expectations and real care. Autonomy comes with accountability. Impact matters. If someone does not want to work on meaningful problems, this is not their place. It sounds firm. It also explains why the company keeps earning top workplace recognition while raising the bar on performance.

We also talked about Maple Studios, the startup incubator Drew launched in Davenport, Iowa. He sees gaps in the industrial ecosystem. Fewer big exits. Slow adoption cycles. Founders stuck inside large companies. Maple gives them tools, space, and hard feedback so they can iterate faster and build things factories will actually deploy. His advice is simple. Ship, learn, and repeat. Do customer reviews early. Expect a thousand small gotchas. Move through them rather than pretending they will not appear.

Looking ahead, Drew expects robotics to accelerate for a very practical reason. Companies cannot find enough people. Dangerous work will be automated. He imagines maintenance tasks shifting toward humanoid robots, with machines designed so robotic agents can service them. He also references GM's self healing language to point at a coming blend of sensing, prediction, and automated repair.

On AI, he shares Satya Nadella's challenge. Measure productivity and GDP impact rather than hype. The promise is there. The scoreboard will tell the story.

If you work in industrial tech, this conversation lands close to home. You will hear how to bring digital tools into legacy environments, how to design for safety from the start, and how to keep teams motivated without losing kindness. You will also catch an open invitation.

Drew wants to partner with builders who care about this space. If that is you, reach out to him on LinkedIn or visit graceport.com. And if you are curious about the band that vibrates before a bad day begins, this episode is a good place to start.

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3413: Why Medium-Range Forecasts Could Save Millions: Lessons from Planette AI Sep 07, 2025

Show notes

I spoke with Kalai Ramea at a timely moment. We recorded this conversation during a heatwave in the UK, which made her work at Planette AI feel very real. Kalai calls herself an all-purpose scientist, with a path that runs through California climate policy, Xerox PARC, and now a startup focused on the forecast window that most people ignore. Not tomorrow's weather. Not far-off climate scenarios. The space in between. Two weeks to two months out, where decisions get made and money is on the line.

Kalai explains Planette AI's idea of scientific AI in plain words. Instead of learning from yesterday's weather patterns and hoping the future looks the same, their models learn physics from earth system simulations. Ocean meets atmosphere, energy moves, and the model learns those relationships directly. That matters in a warming world where history is a shaky guide. It also shortens time to insight. Traditional models can take weeks to run. If the output arrives after the risky period has passed, it is trivia. tte AI is building for speed and usefulness.

The value shows up in places you can picture. Event planners deciding whether to green-light a festival. Airlines shaping schedules and staffing. Farmers choosing when to plant and irrigate. Insurers pricing risk without leaning only on the past. Kalai shared a telling backcast of Bonnaroo in Tennessee, where flooding forced a last-minute cancellation. Their system showed heavy-rain signals weeks ahead. That kind of lead time changes outcomes, budgets, and stress levels.

From Jargon To Decisions

What I appreciate most about this story is the focus on access. Too many forecasts live in papers that only specialists read. Kalai and team are working to strip away jargon and deliver answers people can act on. Will it rain enough to trigger a payout. Will a heat threshold be crossed. Will the next month bring the kind of wind that matters for grid operations. The delivery matters as much as the math. NetCDF files might work for researchers, but a map, a simple number, or a chat interface is what users reach for when time is short.

There is also a financial thread running through this work. Climate risk now shapes crop insurance, carbon programs, and balance sheets. Parametric insurance is growing because it is simple. Set a threshold. If it hits, the policy pays. Better medium-range signals make those products fairer and more useful. Kalai describes Planette AI's role as a baseline layer others can build on, a kind of AWS for climate intelligence. That framing fits. No single company will build every app in this space. A reliable core makes the rest possible.

Kalai's path ties it all together. Policy taught her how decisions get made. PARC sharpened her instincts for practical AI. PlanetteAI is the result. If you care about planning beyond next week, this episode will give you a new way to think about forecasts and the tools that power them. I will add the blog link Kalai shared in the show notes. In the meantime, if you are in agriculture, travel, energy, or insurance, ask yourself a simple question. What would you change if you had a trustworthy signal three to eight weeks ahead.

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3412: PuppyGraph at the IT Press Tour: Graph Power Without the Pain Sep 06, 2025

Show notes

During the IT Press Tour, I had the pleasure of speaking with Weimo Liu, CEO and co-founder of PuppyGraph, and hearing firsthand how his team is rethinking graph technology for the enterprise.

In this episode of Tech Talks Daily, Weimo joins me to share the story behind PuppyGraph's "zero ETL" approach, which lets organizations query their existing data as a graph without ever moving or duplicating it.

We discuss why graph databases, despite their promise, have struggled with mainstream adoption, often because of complex pipelines and heavy infrastructure requirements. Weimo explains how PuppyGraph borrows from his time at TigerGraph and Google's F1 engine to build something new: a distributed query engine that maps tables into a logical graph and delivers subsecond performance on massive datasets. That shift opens the door for use cases in cybersecurity, fraud detection, and AI-driven applications where latency and accuracy matter most.

We also unpack the developer experience. Instead of rewriting schemas or reloading data every time requirements change, PuppyGraph allows teams to define nodes and edges directly from existing tables. That design lowers the barrier for SQL-focused teams and accelerates time to value. Weimo even touches on the role of graph in reducing AI hallucinations, showing how structured relationships can make enterprise AI systems more reliable.

What struck me most in our conversation is how PuppyGraph's playful branding belies its serious engineering depth. Behind the "puppy" name lies a distributed engine built to scale with today's data volumes, backed by strong early adoption and a team that listens closely to customer needs. Whether you're exploring graph for cybersecurity, AI chatbots, or supply chain analytics, this discussion offers a glimpse of how the next generation of graph tech might finally break free from its niche and go mainstream.

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3411: Why The Browser Is The New Security Perimeter Sep 06, 2025

Show notes

When I invited Or Eshed, CEO and co-founder of LayerX Security, onto Tech Talks Daily, I wanted to challenge a blind spot most teams carry into work each day. We talk about phishing, ransomware, and endpoint controls, yet we skip the place where employees actually live online. The browser. That quiet tab bar has become the front door to identities, payments, SaaS, and now AI. Or calls it a different operating system in its own right, and once you hear his examples of how extensions can intercept cookies, mimic logins, or even meddle with AI chats, the penny drops fast.

Here's the thing. Blocking extensions across the board no longer fits how people work. Developers, marketers, sales teams, and support agents all lean on extensions for real productivity gains. Or's argument is simple. If the business depends on extensions, security has to meet people where they are with continuous, risk-based controls inside the browser itself. That means assessing code, permissions, ownership changes, and live behaviors, not relying on a static allow list that grows and grows while attackers slip through the cracks.

We also unpack Extensionpedia, LayerX's free resource that lets anyone look up the risk profile of a specific extension. It is part education, part early warning system, and it serves a wider mission to raise the floor for everyone. Or shares how a technology alliance with Google has helped the team analyze extensions at serious scale, and why better data beats clever slogans in a space where signals change hour by hour.

Malicious Extensions, AI Shortcuts, And The Culture Shift Security Needs

One of the standout moments is a real-world story that starts at home and ends inside a corporate network. A spouse installs a screen-recording extension on a personal device, the browser profile syncs at work, and suddenly corporate credentials and sensitive sessions are mirrored to an untrusted machine. No shadowy APT needed. Just everyday sync doing exactly what it was designed to do. It is messy, human, and exactly why policy needs to be paired with continuous visibility in the browser.

We explore the gray zone where productivity tools collide with privacy. Password managers, VPN helpers, and AI-everywhere extensions promise convenience, yet they can scrape data across SaaS apps or sync credentials in ways security leaders never intended. Or's advice is refreshingly pragmatic. Assume extensions are staying. Instrument the browser, score risk in real time, and adapt access based on what an extension actually does, not what it claims on a store page.

Looking ahead, Or sees the browser taking an even bigger role as email, SaaS, and AI agents converge in one place. With AI companies building their own browsers, the last mile of user interaction gets denser, faster, and more valuable to protect. If 99 percent of enterprise users already run at least one extension, the task is clear. Know which ones are in play, understand how they behave, and keep policy dynamic. If this conversation sparks a rethink of your own approach, check your extensions in Extensionpedia, and then consider what modern, in-browser controls would look like in your environment. After this episode, you may never look at that tidy row of icons the same way again.

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3410: Smartly CEO Laura Desmond on how AI is Rewriting the Rules of AdTech Sep 05, 2025

Show notes

I invited Laura Desmond, CEO of Smartly, to make sense of what feels like the biggest shake-up in marketing since the mobile era. She has led through every cycle I can remember, from the early internet to the rise of social, and she sees AI changing the rules faster than any previous wave. Across our conversation we unpack how AI is rewriting creative work, buying, and measurement, while forcing brands to rebuild trust with clear rules on data, models, and creator rights.

Here's the thing. Attention is shorter, and the thumb moves fast. Most people give an ad about two seconds, and video is taking over the feed. Laura expects video to account for three quarters of digital ads by 2026, which tracks with what I am seeing across every platform. Smartly is betting on that shift with tools that turn Shorts or TikToks into personalized CTV spots, and bring CTV signal back into social. The goal is simple to say and hard to pull off. Show every person something that feels made for them, then learn from the response and improve the next piece of creative in near real time.

We also talk about why the ground is moving under search. A growing number of people, especially younger users, skip the front page of Google and ask an AI assistant instead. That changes how discovery works, how queries appear, and where ad products live. Laura thinks we are heading toward campaigns that cut across search, social, retail media, and CTV as one flowing video-first effort, with creative and media stitched together by software rather than teams tossing files over the wall.

Results matter, and Laura shared two proof points I kept coming back to. Smartly's platform has been validated by PwC for a 13 percent ROI lift across clients. The same study confirmed time savings that add up to 42 minutes a day for hands-on users. That reclaimed time funds the work that actually moves the needle, like faster A/B tests, sharper creative decisions, and better budget moves across channels. We also dig into conversational ads. In a recent test with Boots, Smartly's format delivered roughly four times the return on investment versus business as usual, which speaks to how fast query-style interactions are shaping expectations.

Trust sits in the middle of all this. Laura is clear that responsible AI is table stakes. Brands need controls to tune or override generated assets, clarity on data sources and model choice, and a stance on creator rights before any content goes live. Her view of AI is creative first. Automate the tedious parts. Keep people in charge of taste, tone, and brand. Use the feedback loop to learn faster, not to replace the team.

We close on where this all leads. Expect brand experiences that blur physical and digital without losing the human spark. Stadiums full, stores buzzing, and at the same time richer virtual touchpoints, snackable video, and one-to-one conversations that feel helpful rather than creepy.

If this is your world, Laura is hosting Smartly's ADVANCE on September 17 in Brooklyn, and it looks set to be a real working session for marketers who want results, not theater. You can find details here: https://bit.ly/4fRgWEE.

Tune in if you want a candid, practical map for where creative, media, and AI are heading next, and how to measure what matters while keeping your brand worthy of trust.

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How Fugro is Using Tech to Chart the Ocean Floor Sep 04, 2025

Show notes

What does it take to map the oceans when most of the world's seabed remains unseen and unmapped? That's the question I explored with Mike Liddell from Fugro, a company using technology to reveal what lies beneath the waves.

In our conversation, Mike explained why surveying the ocean is like "working in heavy fog on a roller coaster" and how traditional tools like light and radio signals are useless underwater. Instead, sonar, robotics, and increasingly AI are stepping in to make sense of this hidden world.

Mike described the huge scale of the challenge, from mapping areas larger than major cities to supporting offshore wind farms that power our clean energy transition.

With labour shortages and younger generations less willing to spend months at sea, Fugro is shifting to remote operations centres and uncrewed surface vessels. These new approaches not only widen the talent pool but also cut fuel use dramatically—by as much as 95 percent compared to older ships.

What really struck me was the pace of change. A few years ago, offshore vessels struggled with internet speeds reminiscent of dial-up modems.

Today, satellite systems like Starlink make real-time collaboration between sea and shore possible. Add in AI that can process data at the edge and make instant decisions about where and how to collect information, and you begin to see how marine surveying is entering a new era.

This episode is a glimpse into that frontier and into how technology is reshaping the way we understand and care for our blue planet.

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3408: Lightricks, Open Source Video, and the Race for Faster Creativity Sep 03, 2025

Show notes

Here's the thing. Generative AI for visuals has shifted from a party trick to everyday craftwork, and few people sit closer to that shift than Ofir Bibi, VP of Research at Lightricks.

In this conversation, I wanted to understand how a company famous for Facetune, Photoleap, and Videoleap is building for a future where creators expect speed, control, and choice without a headache. What I found was a story about building core technology that serves real creative workflows, not the other way around.

Ofir traces Lightricks' journey from clever on-device tricks that made small screens feel powerful to today's foundation models running in the cloud. The constant thread is usability. Making complex editing feel simple requires smart decisions in the background, and that mindset has shaped everything from their early mobile apps to LTX Studio, the company's multi-model creative platform. Across the last three years, generative features moved from novelty to necessity, and that reality forced a bigger question: when do you stop stitching together other people's models and start crafting your own?

That question led to LTXV, an open-source video generation model designed for speed, efficiency, and control. Ofir explains why Lightricks built it from scratch and why they shared the weights and trainer with the community. The result is a fast feedback loop where researchers, developers, and even competitors try ideas on a model that runs on consumer-grade hardware and can generate clips faster than they can be watched. The new LTXV 2B Distilled build continues that push toward quicker iteration and creator-friendly control, including arbitrary frame conditioning that suits animation and keyframe-driven workflows.

We also talk about the changing data diet for training. Quantity is out. Quality and preparation matter. Licensed, high-aesthetic datasets and tighter curation produce models that understand prompts, motion, and physics with fewer weird edges. That discipline shows up in the product too. LTX Studio blends Lightricks tech with options from partners like Google's Veo and Black Forest Labs' Flux, then steers users toward the right model for the job through thoughtful UI. If you want the sharpest single shot, you can choose it. If you want fast, iterative tweaks for storytelling, LTXV is front and center.

Looking ahead, Ofir sees a near future where models become broader and more multimodal, while creators and enterprises ask for local and on-prem options that keep data closer to home. That makes efficiency a feature, not a footnote. If you care about the craft of making, not just the spectacle, this episode offers a grounded view of how AI can actually serve creators. It left me convinced that speed and control are the real differentiators, and that open source can be a very practical way to get both.

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How Altair's AI Fabric Helps Businesses Move Beyond Pilot Projects Sep 02, 2025

Show notes

Artificial intelligence is no longer confined to experiments in labs or one-off pilot projects. For many enterprises, it is becoming the backbone of how they operate, innovate, and compete. But as companies race to deploy AI, the biggest challenge is not whether the technology works, but whether the foundations exist to scale it safely and effectively.

In this episode of Tech Talks Daily, I'm joined by Christian Buckner, Senior Vice President of Data and AI Platform at Altair, a company known for combining rocket science with data science. Christian unpacks the concept of an AI Fabric, a framework that harmonizes enterprise data and embeds AI directly into a universal model. Rather than scattered tools and isolated projects, the AI Fabric acts as a living system of intelligence, helping organizations move faster, make better decisions, and unlock new kinds of automation.

We talk about how global enterprises from automotive suppliers to petrochemical giants are already using Altair's technology to improve safety, optimize production, and cut costs. Christian shares examples including a transportation company that boosted revenue by $50 million in its first year of AI-driven dynamic pricing and a healthcare provider that saved $17 million in analysis time using knowledge graphs for drug discovery.

The conversation also explores the hype and the risks around AI agents. While it is easy to spin up a proof of concept with a Python library, Christian explains why real enterprise impact requires governance, monitoring, and infrastructure to make agents trustworthy and sustainable. He likens it to building HR systems for AI, where agents need onboarding, oversight, and performance evaluation to operate alongside humans.

We also touch on Altair's acquisition by Siemens and what this means for the future of industrial AI. By integrating Altair's data and AI expertise with Siemens' deep industrial systems, enterprises can add intelligence without ripping out existing infrastructure. The result is not about replacing workers but enabling them to become what Christian calls "10x employees," augmented by AI tools and agents that multiply their effectiveness.

For anyone curious about how AI will change product design, operations, and enterprise decision-making, this episode offers a rare inside look at the technology foundations being built today. You can learn more at altair.com/ai-fabric.

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