The cameras stopped, the planes grounded, and fashion’s content machine stalled. That shock didn’t end creativity, it rewired it. We sit down with founder and creative technologist Jill Asamota to trace how a career spanning fashion journalism, athlete styling, and brand strategy led to Parallel Pictures, a studio where human art direction meets AI-scale production for premium and luxury brands.

Jill takes us behind the curtain on the moment COVID exposed the fragility of global shoots and how that pushed her to rebuild workflows in virtual space. We compare early 3D and photogrammetry pipelines to today’s diffusion models, unpacking why Midjourney, Stable Diffusion, and controlled environments made hyper-real, brand-consistent imagery viable. From e-commerce expansions to campaign variations and backdrop replacements, Jill explains how teams pair traditional shoots with AI to move faster without losing identity.

We also get practical about risk. Data privacy for unreleased collections, permissions around likeness and virtual models, and the reality of bias baked into training sets, none of this can be left to chance. Jill shares the playbook: curated templates, secure pipelines, human review, and deliberate prompts that bake inclusion into outputs. She makes a strong case for labeling synthetic content and shows how human taste still decides framing, lenses, poses, and light, only now those choices live in prompts and nodes.

As her studio shifts from bespoke services to a scalable platform, Jill reveals what brands really need: education, repeatable workflows, and trust. We talk leadership in AI, clear decisions, outcome focus, and resilience, and peek at what’s next as cutting-edge video models make cinematic storytelling possible without a full set. The future looks hybrid: machines for scale, people for meaning.

If this conversation sparks ideas for your team, follow the show, share it with a builder who cares about craft and ethics, and leave a quick review so more creators can find it.

✨ Stay Connected with Jill & Parallel Pictures:

🔗 LinkedIn Jill: https://www.linkedin.com/in/jillasemota/?originalSubdomain=de
🔗 Instagram Jill: https://www.instagram.com/jill_asemota/?hl=en
🔗 Website Parallel Pictures: https://www.parallelpictures.ai/
🔗 LinkedIn Parallel Pictures: https://www.linkedin.com/company/parallelpicturesai/
🔗 Instagram Parallel Pictures: https://www.instagram.com/parallelpictures.ai/?hl=en

Imagine telling your assistant, I need a new phone and plan, please handle it—then watching it compare carriers, apply credits, and schedule delivery while you sip coffee. That’s the promise of agentic commerce, and in this episode we unpack how it’s moving from hype to a real, secure transaction layer shaping how we buy everything from groceries to luxury fashion.

We start by demystifying what “agentic” really means for shoppers: AI that doesn’t just advise but acts, using shared rules like the Agentic Commerce Protocol to authenticate, check inventory, process payments, and confirm orders without the messy back-and-forth. Then we tackle the elephant in the checkout lane: a high-stakes clash between Amazon and Perplexity that could set the precedent for how third-party AI agents access closed ecosystems. Is your AI an extension of you, or an uninvited bot? We weigh the legal, security, and customer experience angles and ask who truly owns the customer relationship when a bot holds the cart.

From there, we go global. Alibaba’s Dian Xiaomi handled an eye-popping 300 million customer queries during Singles Day, showcasing how AI scales service without losing speed. In Europe and the U.S., Mango’s AI Stylist and Ralph Lauren’s Ask Ralph blend brand voice with real buying power, folding inspiration, sizing advice, and shoppable looks into a single conversation that follows through to delivery and returns. Along the way we share lessons from 2025 rollouts, highlight diversity as a driver of better AI outcomes, and sketch what 2026–27 could bring: proactive agents, AR-enhanced stores, agent-to-agent negotiation, and loyalty that measures your trust in a retailer’s assistant.

If you’re curious about where autonomy meets accountability—and how your next purchase might be just a sentence away—this is your roadmap. Subscribe, share with a friend who loves retail tech, and leave a review with your take: should retailers gatekeep third‑party agents or open the lanes for user choice?

Shopping just crossed a line: the bot doesn’t only recommend, it remembers, compares, and buys with your permission. We unpack a pivotal year where AI agents went from reactive chat to proactive concierge, reshaping how intent turns into a purchase across Amazon, Walmart, Google, and OpenAI’s expanding ecosystem.

We kick off with Amazon’s Rufus and its late‑2025 leap: activity-aware recommendations, hands-free price‑drop purchases, cart‑to‑doorstep execution, visual search that converts a messy fridge into a grocery plan, and list autopilot from a scribbled note. With model orchestration, real‑time retrieval, and side‑by‑side comparisons, Rufus aims to reduce doubt and win checkout with transparency and speed. Then we shift to Walmart’s Sparky, a companion that meets you in the app and, through a bold OpenAI partnership, inside ChatGPT. From occasion dressing to meal plans and service bookings, Sparky embodies “agentic commerce,” anticipating needs and acting across channels without friction.

Google’s AI shopping mode brings Gemini-powered results directly into search: natural-language queries, review summaries, live price tracking, visual try‑ons, and even “let Google call” to confirm local inventory. With early tests of AI-led checkout, Google compresses the journey from discovery to payment, keeping trust by emphasizing relevance over ads. Finally, we dive into OpenAI’s instant checkout and the open Agentic Commerce Protocol with Stripe and PayPal, opening conversational buying to Etsy, Shopify merchants, and beyond—bringing small businesses into chat-driven commerce without custom builds.

We spotlight women-led startups redefining the experience: Phia for radical price transparency and secondhand value, Gensmo for mood-driven fashion and real-time avatars, Alta for closet‑aware styling, and Doji for social, hyper‑real try‑ons. Along the way, we map how shoppers adapt—verifying AI advice, embracing seamless purchases, and blending AI groundwork with human nuance—as trust features like citations and comparisons close the last mile to buy. If you care about the future of retail, personalization, and the new rules of intent, this conversation gives you the playbook.

Enjoyed the show? Follow, share with a friend who loves great tools, and leave a quick review—what would you let an AI buy for you next?