What's Up with Tech?

• Turning AI Hype Into Enterprise ROI

  Interested in being a guest? Email us at [email protected] is loud, but outcomes win. We sit down with Smartling CEO Bryan Murphy to explore why the center of gravity in AI is shifting from raw models to the application layer where workflows, data, and governance translate into real business value. If you’ve been stuck in pilot purgatory, you’ll hear how to move from experiments to production with clear ROI.Bryan draws sharp parallels to earlier waves—the internet and cloud—and explains how today’s “chips and data centers” moment mirrors the 90s buildout, with a familiar follow-up: purpose-built apps that make the infrastructure usable. We dig into translation as a top-tier AI use case and unpack Smartling’s results: translating 3x more content at about 60 percent less cost and six times faster than traditional methods. The secret isn’t a flashy bolt-on; it’s re-architecting around an AI hub and agentic workflows that integrate directly with enterprise stacks.We also challenge the “AI will kill SaaS” headline. Foundational models like GPT and Claude are treated as infrastructure, while the real differentiation comes from orchestration—selecting the best model for the job, routing data safely, learning from feedback, and guaranteeing quality. Bryan shares how governance protects brand voice at scale, from hallucination detection to automated language QA and custom-trained models honoring glossaries and style guides. With 7 billion words translated a year, reliability isn’t a feature—it’s the product.Looking ahead, we explore multimodal translation across text, audio, and video, and a future where translation functions as a service embedded in everyday tools. For founders, Bryan offers practical advice: target a 10x problem, verify there’s real TAM, and build applications that customers will happily pay for. For enterprise leaders, the message is simple: stop chasing models, invest in orchestration, and pick solutions that measure and deliver outcomes.If this conversation helps you think clearer about where AI value is headed, follow the show, share it with a colleague, and leave a quick review so others can find it.Support the showMore at https://linktr.ee/EvanKirstel

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• How AI Chatbots Go Off The Rails And What To Do About It

  Interested in being a guest? Email us at [email protected] most powerful product might also be your biggest liability: an AI agent making decisions you can’t see and answers you can’t predict. We sat down with Andre Scott of Coralogix to unpack how to make black-box systems measurable, accountable, and—most importantly—improvable over time.We trace the journey from monoliths to microservices to LLMs and explain why old-school “index everything, analyze later” monitoring breaks under today’s data explosion. Andre introduces an analytics-first approach that processes telemetry in-stream and then stores what matters in your own object storage. That shift delivers cost control and true data ownership, turning observability from an insurance policy into a growth engine. We dig into open tooling like an LLM trace kit built on OpenTelemetry that captures prompts, responses, and metadata, so you can evaluate correctness, flag prompt injection, and enforce guardrails at runtime.Bias and hallucinations don’t announce themselves; they creep in through context loss, retrieval misses, and model updates. The fix is continuous evaluation with small, purpose-trained models that run outside your app to score tone, safety, factuality, and leakage risks. Think of agents like employees: give them performance reviews, train them with real data, and escalate when risk spikes. We also explore Olly, CoraLogix’ agentic SRE that reads your telemetry, answers business-grade questions, and recommends alerts and remediations—especially handy when cloud outages ripple through your stack.Regulation is coming fast, and accountability rests with the teams who ship AI into production. If you deploy it, you own the risk. The practical playbook is clear: embrace analytics-first observability, capture LLM telemetry, make evaluators your crown jewels, and keep the data that teaches your models to improve. Subscribe, share this with your engineering and product teams, and leave a review with the one place you’d add guardrails first.Support the showMore at https://linktr.ee/EvanKirstel

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• Inside Tupl’s Explainable, Agentic AI Transforming Global Telecom

  Interested in being a guest? Email us at [email protected] doesn’t need another AI science project; it needs outcomes. That’s the thread running through our conversation with kishore bobbarjung from Tupl, where explainable, agentic automation is delivering real wins: faster resolution of customer issues at a US tier one and double-digit energy savings across more than ten European networks—without sacrificing KPIs. We walk through how connecting customer signals to network data shrinks time-to-fix, how policy-aware power optimization lets radios sleep smart, and why trust and transparency with engineering teams are the real force multipliers for scale.We dig into the design choices that matter: building AI around workflows engineers already use, surfacing every step so fixes are understandable and safe, and promoting repeatable investigations into closed-loop automations. That’s how costs stay predictable and knowledge compounds. We also unpack the tough parts—workforce concerns, governance, security, and the surprise bill that can come from token-heavy agents—and show how Tupl contains exposure by localizing processing and turning one-off agent work into durable scripts.The roadmap gets bold: a “no tools” North Star where an agentic co‑pilot interrogates data, guides deep investigations, and then codifies proven remedies back into Network Advisor for ongoing, low-cost execution. With AI moving deeper into the RAN, we explore early gains in radio design, optimization, and critical-site resilience, as major vendors push intelligence closer to the edge. If you care about cutting OPEX, boosting customer experience, and replacing tool sprawl with a coherent AI layer, this conversation lays out a practical playbook.Enjoy the episode, then subscribe, share with a colleague, and leave a quick review to help others find the show. What would you automate first in your network?Support the showMore at https://linktr.ee/EvanKirstel

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• Agentic CX, Real Results

  Interested in being a guest? Email us at [email protected] of chatbots that stall when customers need real help? We dive into how agentic AI flips the script by taking actions inside your systems—issuing refunds within limits, updating orders, authenticating users, and escalating with intent—while humans handle complex, high-empathy moments. Joe Anderson, Senior Director and Head of CX and Digital Transformation at TaskUs, breaks down a practical playbook: choose the right high-volume use cases, embed guardrails and escalation paths, and integrate platforms like Decagon and Regal to ship in weeks, not quarters.We walk through safety by design, from prompt hardening and policy constraints to continuous human evaluation that tunes agents over time. Regulated industries like healthcare and financial services come up often, and we outline how to meet compliance standards while delivering faster resolutions and better customer outcomes. The conversation also tackles a persistent myth: AI won’t erase your support team. It will elevate them. As tier-zero and tier-one tickets automate, human experts shift to white-glove support, retention saves, and nuanced sales where judgment and empathy pay off.The business model is evolving too. Instead of hourly rates, TaskUs leans into outcome-based pricing and gain share, aligning incentives around first contact resolution, containment, CSAT, and cost per resolution. For leaders just starting, we offer a clear path: pick a major contact driver, launch to a small percent of traffic, measure rigorously, and scale as accuracy climbs. You’ll learn how to convert insights from AI interactions into product fixes and journey improvements that reduce avoidable contacts and lift satisfaction across the board.If you’re ready to transform customer experience with real action, not just conversation, this episode is your blueprint. Subscribe, share with your CX and product teams, and leave a review telling us which high-impact use case you’ll tackle first.Support the showMore at https://linktr.ee/EvanKirstel

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• If Identity Becomes Portable, Does Trust Become Universal?

  Interested in being a guest? Email us at [email protected] has become the entry ticket to the internet, and users are now choosing safety over price and speed. We sit down with Raj from Trua to dig into the 2025 Trust Survey and why verification has shifted from a nice-to-have to a must-have. From shocking stats on consumer expectations to the real reasons fear and fatigue are rewriting behavior, we map out what it takes to build platforms people will actually use—and pay for.We walk through the practical playbook: make safety the first thing users see, put verified badges and last-checked timestamps front and center, and adopt “friction by design” to deter bad actors without punishing good ones. Raj breaks down progressive checks that scale with risk—identity and address for low-stakes, licenses and criminal screens when necessary, and liveness for high-impact flows like dating and hiring. He explains why trust tech is emerging as its own category and how a reusable, tokenized credential can follow you across apps, slashing repeated data collection while boosting conversion and confidence.AI and deepfakes add urgency. With bots posing as people, human identity verification becomes essential for high-risk interactions, and continuous authentication helps separate real users from synthetic scams. We also explore the regulatory landscape, why co‑opting consumers is cheaper and more effective than piling on rules, and how brands like Apple translate privacy into loyalty. The gig economy emerges as the flash point: tens of millions move across platforms that need fast, safe onboarding and fewer data silos to breach.If you care about growth, retention, and brand resilience, now is the time to operationalize trust. Subscribe, share this episode with a product or security leader, and leave a review with one change you’ll make to bring safety to the surface.Inspiring Tech Leaders - The Technology PodcastInterviews with Tech Leaders and insights on the latest emerging technology trends.Listen on: Apple Podcasts SpotifySupport the showMore at https://linktr.ee/EvanKirstel

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