NETWORKING + PODCST: EVENT HIGHLIGHTS
Thursday, January 29, 2026

In this episode of The AI Space Podcast, host Sanjay Kalluvilayil speaks with Steve Deeb, founder and CEO of Lonestar Ascent AI, about why “the future of conversation is visible” heading into 2026. Steve breaks down the shift from chatbots and rigid call flows to multimodal, customer-led interactions that fuse voice, visuals, and context in real-time. He explains how high-fidelity data and strong design philosophy drive accuracy, low latency, and trust, and why the next wave of AI advantage will come less from model hype and more from delivering precise, emotionally coherent experiences that feel intuitive and human.

A major takeaway is how this transformation shows up on mobile: the conversation becomes the interface. Instead of clicking through flat pages, customers can speak, see, and explore in a single flow where visuals update alongside the dialogue, guiding discovery and decision-making like a concierge experience. Steve outlines how these “visual conversations” can bridge online and in-store journeys, reduce friction and cart abandonment, and turn AI from a cost-saving support tool into a revenue driver that boosts loyalty and lifetime value. He also notes the business-model shift toward outcome-based pricing and tighter unit economics as multimodal experiences raise the importance of inference costs.

INSIGHT #1

The Shift to Immersive, Brand-Defining AI Experiences
AI is moving beyond simple utility and efficiency into fully immersive customer experiences that differentiate brands. Through visible conversation and multimodal interaction, AI becomes part of the brand environment itself, creating emotionally resonant moments that deepen connection, build trust, and drive long-term loyalty rather than one-off task completion.

INSIGHT #2

Data Fidelity Becomes the True Competitive Advantage
In 2026, AI performance is no longer defined by the model alone but by the fidelity of the interaction. High-resolution inputs and outputs that integrate tone, visual context, and intent allow AI systems to understand complex, multi-layered goals instantly. This level of precision enables responses that feel intuitive, human, and decisively useful at scale.

INSIGHT #3

Customer-Owned Dialogue Replaces Scripted Automation
Immersive AI eliminates rigid if-then workflows in favor of customer-led interaction. By allowing users to guide conversations through voice, text, and visual cues, businesses shift from reactive support to proactive, guided journeys. The result is higher conversion, stronger engagement, and increased lifetime value driven by autonomy rather than automation.

AI implementation often goes sideways due to unclear goals and a lack of a clear framework. This AI Training Checklist from You.com pinpoints common pitfalls and guides you to build a capable, confident team that can make the most out of your AI investment.

What you'll get:

Get the checklist.

Multimodal Conversational AI
Steve emphasizes that the future of AI interaction is not text-only or voice-only, but a synchronized fusion of voice, visuals, and context. These “visual conversations” allow users to speak, see, gesture, and explore in real-time, creating frictionless experiences that feel intuitive and human rather than transactional.

Customer-Owned Dialogue
A core framework in the episode is that the customer owns the conversation. Unlike chatbots or predefined call flows, multimodal AI allows users to guide the interaction based on their intent and curiosity. The system responds dynamically, asks clarifying questions when needed, and adapts the experience without forcing users down scripted paths.

Agentic Workflows Behind the Scenes
While the experience feels conversational, Steve explains that agent-based architectures manage state, intent, and orchestration underneath. Agents coordinate voice, visuals, and context in real time, enabling scalable and responsive experiences without exposing complexity to the user.

High-Fidelity Inputs and Outputs
Steve repeatedly stresses that the quality of AI systems depends on the fidelity of data and signals. Accurate voice recognition, low latency, emotional coherence, and precise visuals all contribute to experiences that feel trustworthy and immersive rather than artificial or generic.

Human-in-the-Loop by Design
Human guidance remains essential. When intent is high or situations become sensitive, the system can warm-transfer to a human expert, concierge, or in-store associate. AI reduces friction and gathers context, while humans handle judgment, reassurance, and final decisions.

Risk of Low-Fidelity or “AI Slop” Experiences
Steve warns against blindly publishing or deploying AI outputs without curation. Low-quality, unedited AI responses erode trust and damage brand credibility. Authentic voice, validation, and thoughtful design are required to avoid disingenuous or unreliable interactions.

Trust Through Experience Consistency
Trust is not just technical accuracy; it is experiential consistency. AI-driven interactions must align with a brand’s identity, tone, and expectations across digital and physical touchpoints to feel credible and premium.

Sell Experiences and Outcomes, Not Technology
Steve makes it clear that customers do not buy AI models, they buy outcomes. AI creates value when it drives revenue, reduces friction, improves conversion, or enhances customer confidence, not when it is positioned as a technical novelty.

Turn the Buying Journey Into the Product
Rather than treating AI as a backend efficiency tool, the episode reframes AI as part of the buying experience itself. Multimodal conversations guide discovery, educate customers, and reduce hesitation, especially for high-intent and high-value purchases.

Reduce Friction to Increase Revenue
By answering questions in real-time, visualizing options, and maintaining conversational flow, AI reduces cart abandonment and uncertainty. Steve highlights how this approach shortens decision cycles and increases completion rates.

Outcome-Based Pricing and Value Creation
The discussion notes a shift away from traditional SaaS pricing toward value-based models. Pricing is tied to outcomes created, revenue lift, reduced returns, or improved conversion, rather than seats or feature access.

Unit Economics Matter
As multimodal AI increases inference and compute demands, Steve emphasizes understanding unit economics. Sustainable growth requires balancing experience quality with cost efficiency, especially for founders and bootstrapped teams.

Enterprise-Grade Experience Wins
Businesses adopt AI when it integrates cleanly into existing workflows, respects brand identity, and delivers measurable results. Mature, experience-driven AI solutions are more likely to gain traction than experimental tools.

Over-Automation Without Judgment
Steve cautions against fully autonomous systems that remove human accountability. AI should assist, not override, especially when decisions carry financial, emotional, or reputational risk.

Loss of Authentic Voice
Publishing AI-generated content without human editing leads to inauthentic communication. Steve stresses the importance of maintaining a genuine voice when AI represents a brand.

Trust Breakdown From Poor Experiences
Errors in voice quality, latency, or visual accuracy quickly break immersion and trust. In high-touch experiences, small failures feel amplified and can undermine confidence in the system.

Data Quality and Context Gaps
Garbage in still produces garbage out. Without high-quality data and contextual understanding, AI systems fail to deliver meaningful or accurate outcomes.

Security and Brand Risk
AI experiences that mishandle customer data or behave unpredictably damage trust. Responsible deployment requires thoughtful architecture and guardrails.

Build With Intentional Design
Steve highlights that success comes from design philosophy as much as technology. Leaders must decide what experience they want to create and use AI intentionally to support it.

Focus on Signal Over Noise
With rapid tool releases and constant hype, leaders must identify what truly adds value. Chasing every new capability leads to fragmentation and burnout.

AI as a Force Multiplier for People
AI scales impact when it frees humans to focus on creativity, strategy, and relationships. The goal is leverage, not replacement.

Faith, Resilience, and Perspective
Steve closes with a grounded leadership perspective: stay focused, stay grateful, and keep moving forward even when the path is unclear. Big visions require patience, humility, and consistent action.

Platforms & Companies

Apple
Referenced as a benchmark for brand consistency and aesthetic-driven design, illustrating how digital experiences must align with brand expectations across products and touchpoints.

Google
Used as an example of cohesive product ecosystems and consistent user experience, and referenced in the broader discussion around the shift from keyword-based search toward semantic and generative discovery.

Luxury Retail & Hospitality Brands (General Reference)
Steve references luxury retail, jewelry, travel, and hospitality brands as primary use cases, where immersive, concierge-style digital experiences are critical to driving conversion, loyalty, and lifetime value.

Lonestar Ascent AI
Steve’s company and core platform discussed throughout the episode. Lonestar Ascent AI focuses on multimodal conversational AI that blends voice, visuals, and context to create immersive, revenue-driving customer experiences.

AI, Cloud & Agentic Stack

Agent Orchestration Frameworks (General Reference)
Steve discusses agent-based systems that manage conversational state, intent, and workflow coordination behind the scenes, including:

These are referenced conceptually as part of the modern agent ecosystem rather than specific endorsements.

Kubernetes
Described as the de facto operating system for modern enterprise AI and agentic workflows, enabling scalability and operational reliability.

Multimodal Generative Systems
Used to dynamically generate images, short video clips, and visual assets that update in real time alongside voice-based conversations, forming the backbone of “visual conversations.”

Voice, Audio & Multimodal Technologies

ElevenLabs
Referenced as an example of advanced voice synthesis technology focused on acoustic modeling, emotional coherence, inflection, and realism beyond basic text-to-speech.

Noise Cancellation
Discussed as essential for clean, real-world audio input, especially in mobile and ambient environments.

Real-Time Voice Streaming
Steve emphasizes streaming voice input and output in real time rather than waiting for full utterances, enabling conversations that feel natural and responsive.

Voice Activity Detection (VAD)
Referenced as a critical capability for detecting pauses, interruptions, and conversational turn-taking in immersive voice experiences.

AI Models, Research & Discovery Tools

ChatGPT
Mentioned as a general-purpose LLM used for reasoning, experimentation, and early GenAI exploration.

GEO (Generative Engine Optimization)
Discussed as the evolution of discovery, where content is optimized for AI-generated answers rather than traditional search rankings. GEO prioritizes semantic relevance, clarity, and structure so generative AI systems can accurately retrieve, interpret, and synthesize information when responding to users.

OpenAI
Referenced in the context of early generative AI momentum and the rapid acceleration of model capabilities.

Perplexity
Referenced as a semantic research and discovery tool, highlighting the move beyond traditional keyword-based search.

Semantic Search
Focuses on understanding user intent, context, and meaning rather than matching exact keywords. Semantic search enables AI systems to surface relevant information even when queries are exploratory, conversational, or loosely defined.

Creative & Media Tools

NightCafe
Mentioned by the host as a creative AI tool used to test and compare image-generation models for podcast visuals and media assets.

Business Models & Economics

Inference Cost & Unit Economics
Highlighted as a critical constraint when building multimodal AI systems, requiring careful balance between experience quality and operational cost.

Outcome-Based Pricing Models
Steve discusses the shift away from traditional SaaS seat-based pricing toward pricing based on value created, such as revenue lift, conversion improvement, or friction reduction.

Leadership, Mindset & Ecosystem

AI Founder & Builder Community
Steve praises The AI Space Podcast for fostering intellectual curiosity and real-world knowledge sharing among founders, technologists, and builders.

Faith, Resilience & Long-Term Vision
Discussed as guiding principles for staying grounded, focused, and persistent while building through rapid technological change.

This episode reinforces that staying relevant in an AI-first enterprise is not about chasing larger models or flooding products with automation, but about designing intelligence into the experience itself. Steve Deeb makes it clear that the real differentiator in 2026 will be how effectively organizations blend voice, visuals, and context to reduce friction, build trust, and guide high-intent decisions. AI becomes most powerful when it enhances clarity and confidence for the customer, rather than replacing human judgment or brand identity.

For customer-facing and revenue-driving environments, relevance comes from treating conversation as the interface and mobile as the primary stage. Multimodal AI that is low-latency, high-fidelity, and customer-led allows businesses to scale white-glove experiences without sacrificing authenticity or control. The organizations that win will balance experimentation with discipline, maintain strong unit economics, and deploy AI as a force multiplier that reinforces brand consistency, trust, and long-term value instead of chasing novelty or unchecked automation.

I will be attending DSS ATX | GENAI & INTELLIGENT AGENTS IN THE ENTERPRISE this month. We are partnering with DSS Salon for you to attend the show. Please PROMO CODE: THEAISPACEPODCAST30 for 30% off your ticket price!

Akshay Mittal spoke about leading ACM Austin events in the last episode.

I have been invited to be the moderator for a panel discussion at the Mind & Machine x Mythworx event: Beyond the Model | The AGI Moment. Please join me in attending. Great to partner with Tori Begg and Tim Mata on future events.

If you’re new here, this playlist explains Guest motivation for sharing their journey to AI and insights on this show. We focus on practical conversations with founders, operators, and investors who are building real AI businesses and systems, not just discussing the hottest trends and moving beyond the AI hype.

👉Watch the “Why The AI Space Podcast?” playlist on YouTube.

👉Watch curated playlists on YouTube.

🎬Binge on Season 1.

🎬Watch Season 2

🎧Listen on your favorite platforms like Spotify & Apple

📱Stay connected: Facebook | Instagram | LinkedIn | Tik Tok | X

See the top-performing Facebook ads in your niche and replicate them using AI. Gethookd shows you what’s actually working so you can increase ROI and scale ad spend with confidence.

See the winning ads

👉Listen here

We will share the best responses in the next issue.

🟩🟩🟩🟩🟩🟩 Lack of trust and explainability (5)
🟨🟨🟨⬜️⬜️⬜️ Weak security and governance (3)
🟨🟨🟨⬜️⬜️⬜️ Over-automation without humans in the loop (3)
🟩🟩🟩🟩🟩🟩 Poor integration with existing systems (5)

Community Insight: Last week, the conversation split clearly between two core challenges of AI at scale. Both lack of trust and explainability and poor integration with existing systems led the poll, each capturing 31.3% of responses, signaling that AI adoption continues to break down when systems can’t be trusted or embedded cleanly into real-world operations.

Weak security and governance and over-automation without humans in the loop followed closely behind at 18.8% each, reinforcing that while automation is powerful, the absence of guardrails, oversight, and accountability still creates meaningful risk for organizations.

Taken together, the results suggest the community sees AI failure less as a model problem and more as an execution and design problem. Trust, integration, and human-guided systems are emerging as the true requirements for scaling AI responsibly and sustainably.

👉 Partner with us! Explore Sponsorships and Schedule an intro call now:

👉 Use the affiliate or referral links to unlock discounts, promos, or special access as you explore AI apps and tools.

🌐Connect with Sanjay Kalluvilayil

🌐 Learn more about Stonehaas Advisors

🔗Follow Stonehaas Advisors on LinkedIn

📅 Schedule a FREE Strategy Session

What’s the secret to staying ahead of the curve in the world of AI? Information. Luckily, you can join 2,000,000+ early adopters reading The Rundown AI — the free newsletter that makes you smarter on AI with just a 5-minute read per day.

Sign up to start learning.

Why am I getting this newsletter?
You are on this list because you have previously subscribed to or interacted with our content. You may have joined through the podcast, our website, or one of our previous updates.

How often is the newsletter published?
Weekly

Where can I listen to episodes?
Anywhere you listen to podcasts.

What topics are covered in each episode?
Each episode separates signal from noise, exploring the latest AI developments and the vision, strategy, and mindset required to scale a business and thrive in life and work. Guests share how to architect the AI tech stack, apply proven methodologies, leverage practical tools, and strengthen sales, marketing, and operations by building intelligent systems.

The show explores how to grow and scale a business with AI. Beyond the strategy and technology aspects, we explore the human dimension of AI. Topics include the future of work, shifts in labor markets, utopian and dystopian scenarios, the role of purpose in an AI-enabled world, and the long-term impact of intelligent systems on society and culture.

Beyond AI and tech, what other topics do you cover?
The AI Space Podcast is building a movement and a community focused on creating value, driving economic impact, and shaping an AI-powered future that is ethical, responsible, and beneficial for business and society.

Who is this podcast for?
The result is a high-signal, zero-hype platform offering practical insights, technical clarity, and thoughtful perspectives leaders can apply as they build confidently in The AI Space. The podcast is dedicated to helping founders, innovators, technologists, and innovators to create a lasting and positive legacy in a rapidly transforming world.

Do you discuss democratization, ethical & responsible AI?
We cover democratization, ethical responsible AI, governance models, and guardrails that promote safe and transparent deployment. We also explore Utopian vs. Dystopian scenarios, balancing the risks and benefits to reduce unintended impact on humanity.

How do I manage my subscription?
Use the e-mail Preferences link in the footer to update your e-mail settings or unsubscribe at any time.

Until the next episode, Space Cowboy!

The AI Space Podcast