AI Marketing

Sign up free for NitroSend via this link Marketing dashboards were built for humans to click through. George Hartley thinks AI agents will make most of that clicking unnecessary. In this episode of AI Marketing, Mark Fidelman talks with George Hartley, co-founder of Nitro Send, about the shift from traditional marketing software to agent-first systems that work directly through Claude, Codex and other AI assistants. George explains why his team designed Nitro Send with the agent as the primary user and the human interface as the backup. The result: 98% of the activity on the platform last month was completed through AI agents rather than its dashboard. The conversation goes beyond email. Mark and George discuss what happens when CRMs become little more than databases, agents monitor buying signals automatically, follow-ups write themselves and marketers stop spending half their day bouncing between browser tabs. What you'll learn Why traditional marketing dashboards may become largely irrelevant How AI agents can build complete email lifecycle campaigns in minutes instead of weeks Why most CRM software could eventually become a background data layer How agents can enrich leads, identify buying signals and draft follow-ups Why outbound email requires different safeguards than newsletters and transactional email How Nitro Send handles customer data and reduces the risk of inaccurate results What goal-based marketing could look like when agents optimize campaigns autonomously Why George believes much of traditional SaaS will be pushed behind the AI assistant Episode highlights 00:31 George's background and the launch of Nitro Send 01:51 Why existing email marketing tools were painful to use 03:52 Building software where the AI agent is the primary user 04:16 Why 98% of Nitro Send activity now happens through agents 05:41 The problems with AI-powered prospecting and follow-up 06:58 Building complete customer lifecycle campaigns with an agent 09:47 Creating and redesigning newsletters through a single prompt 10:38 The move toward autonomous, goal-based marketing 11:43 Will AI agents replace traditional CRMs? 14:10 Why expensive CRM dashboards may become unnecessary 17:00 Lead enrichment, lookalike audiences and automated prospecting 18:57 How Nitro Send approaches AI hallucinations and data accuracy 22:01 Product availability, outbound beta and the roadmap 23:19 How to try Nitro Send 24:39 Connecting your business domain and email About George Hartley George Hartley is a repeat technology founder and co-founder of Nitro Send, an agent-first email marketing platform designed to run through tools such as Claude and Codex. He previously helped build Australia's largest online art marketplace and co-founded SmartrMail, an ecommerce email automation company that was acquired in 2022. Try Nitro Send Sign up free for NitroSend via this link or ask your AI agent to install Nitro Send. The platform offers a free account that includes up to 5,000 emails. George is also on X at @GTHartley. Get AgentShock AgentShock: Surviving and Profiting from the Rise of AI Agents and Robots, by Jas Dhillon and Mark Fidelman, explains what happens as AI moves from answering questions to completing work, directing workflows and running entire business functions. Learn more and get the book at Agentized.com/book.

Episode Show Notes: AI in Real Estate Leasing with Ran Fridman Episode: AI Marketing Podcast — AI in Real Estate Leasing Host: Mark E. Fidelman Guest: Ran Fridman, founder of MyRemotely Website: myremotely.ai Episode overview Ran Fridman joins Mark to discuss how the challenges of managing rental properties across multiple states led him to build an AI-powered leasing and property-management workflow. The conversation covers self-guided property tours, identity verification, connected lockboxes, automated lead follow-up, and how human staff and landlords remain involved in application decisions. What they discuss Ran's real estate journey [05:06–07:00]: Originally from Ukraine, Ran moved to Chicago after living in China for eight years. He began investing by purchasing and renovating six foreclosures on Chicago's South Side, then expanded his personal portfolio to 22 units across Illinois, Indiana, and Wisconsin. The challenge of remote showings [07:13–09:54]: With properties in three states, Ran couldn't personally handle every showing. After struggling to find a property manager suited to the logistics, he and his wife started their own technology-focused property management company. How the leasing system works [10:02–11:04]: Ran describes an AI agent that responds to leads from platforms such as Zillow and Apartments.com, reportedly in under 30 seconds, and helps prospects schedule self-guided tours. Identity verification and property access [08:00–08:41; 11:42–12:29]: Before a tour, prospective renters verify their identity using identification and face recognition. Ran says the system uses a connected digital lockbox to provide time-limited access, and that visitors are notified that tours are monitored by video and audio. After-tour follow-up [13:44–15:08]: The system can follow up by text, email, or phone. Interested prospects can receive an application link; those who aren't interested can be asked for feedback about the property. Human review and landlord decisions [15:08–15:59]: Ran says staff monitor the process and review submitted applications. The landlord retains the final decision on applicants. From internal tools to a public product [16:36–17:56]: Ran explains that the software and lockbox were built to solve problems in his own business and are now being offered to other landlords and property managers. He directs interested listeners to myremotely.ai. Key takeaways Remote leasing can help property owners and managers serve prospective tenants across different locations and schedules. Ran's workflow combines AI lead response and follow-up with identity checks, self-guided tours, and a connected lockbox. Automation supports the leasing process, but people remain involved: staff review applications and landlords make the final approval decision. MyRemotely's tools grew out of operational challenges in Ran's own rental portfolio and property management business.

Guest: Nikhil Vimal   Host: Mark Fidelman Starting an e-commerce company used to mean assembling a small army: researchers, marketers, content creators, media buyers, customer-support reps, and operations people. AI has changed that equation. In this episode, Mark Fidelman sits down with AI strategist, entrepreneur, and author Nikhil Vimal to map out how they would build an e-commerce business today. Their playbook starts with AI-powered market research, moves through content creation and campaign execution, and closes the loop with monitoring systems that learn from every result. The bigger opportunity is a connected system of AI agents that can watch competitors, spot cultural moments, create and repurpose content, re-engage customers, and improve over time—with a human responsible for every important approval. Mark's take: Founders who use AI for isolated tasks will save time. Founders who build a learning system around it will build an advantage. ## What You'll Learn - Why AI agents can replace much of the early infrastructure once required to launch a direct-to-consumer brand - How to automate competitive research across promotions, ads, creators, partnerships, and adjacent industries - How AI can turn market intelligence into seasonal campaigns, product images, video, copy, and content calendars - Why "clipping" and content repurposing can turn 20 original assets into 100 distribution-ready pieces - How to react quickly to viral cultural moments without forcing a founder to live on social media - Why every agent still needs a human owner who approves consequential work - How observability and monitoring help the system learn from wins, misses, and customer behavior - Where AI voice agents fit into 24/7 customer support - Why Shopify, Perplexity, Claude, ChatGPT, HubSpot, Buffer, and Zapier are practical places to begin - What Zapier still does well: visual workflow design, collaboration, connection monitoring, and operational visibility ## Episode Chapters - **00:00** — Welcome and Nikhil Vimal's background - **01:42** — The challenge: build an e-commerce company with today's AI tools - **02:12** — AI agents as an on-demand marketing and growth team - **04:34** — Step 1: continuous research and market analysis - **06:02** — Learning from winning ads and adjacent industries - **07:16** — Step 2: campaign preparation and generative content - **08:22** — Why a human must own every AI agent - **09:08** — Step 3: execution, outreach, UGC, and content calendars - **09:52** — Scaling content through clipping and repurposing - **10:53** — Using AI to react to viral moments in real time - **13:32** — Step 4: observability, monitoring, and continuous improvement - **14:54** — The central lesson: build systems, not scattered automations - **15:54** — AI voice agents and the customer-support opportunity - **17:35** — Where a new e-commerce founder should start - **19:19** — The practical starter stack - **20:25** — Why Zapier still matters in the era of connected LLMs - **23:00** — Final lessons and a preview of agentic AI at enterprise scale - **24:18** — Where to find Nikhil and his forthcoming book ## The Operating Model 1. **Research:** Track competitors, adjacent categories, creators, ads, promotions, and market shifts. 2. **Prepare:** Convert that intelligence into campaign concepts, product visuals, video, copy, and calendars. 3. **Execute:** Publish, distribute, follow up with customers, recruit creators, and repurpose the best material. 4. **Observe:** Measure results, identify why something worked or failed, and feed those lessons back into the next cycle. 5. **Approve:** Keep a named human accountable for the decisions that can affect customers, pricing, reputation, or revenue. ## Tools Mentioned - Perplexity for research and market analysis - ChatGPT and Claude for preparation, execution, and connected workflows - Shopify for commerce infrastructure and educational resources - Zapier for visual automation, workflow orchestration, and monitoring - HubSpot for marketing and customer operations - Buffer for content calendars and publishing workflows - Notion, ClickUp, and Asana for project and workflow management - Midjourney, Higgsfield, and Seedance for image and video creation - Meta Business Suite and Marketo for marketing operations and analytics ## About Nikhil Vimal Nikhil Vimal is an AI strategist, entrepreneur, investor, advisor, and author who has spent roughly 15 years working across startups, e-commerce brands, agencies, and large enterprises. His forthcoming book, *The Essential Pivot*, focuses on navigating change and separating signal from noise. Connect with Nikhil on [LinkedIn](https://www.linkedin.com/in/nikhilvimal) and visit [nvimal.com](https://nvimal.com). ## Closing Thought AI can help one founder operate with the reach of a much larger company. But the advantage doesn't come from collecting more tools. It comes from connecting the work, measuring what happens, and making the system smarter every time it runs. That's the operating model to build around. ------------------------------ Want all of my insights in one place, buy our book at www.agentized.com/book (Release Nov 2026)     

Host: Mark Fidelman Guest: Aksel Bedikyan, marketing research and analytics practitioner based in Montreal, Canada Episode description How is AI changing marketing analytics—and what remains valuable when AI can write code, analyze data, and automate reports? Mark Fidelman talks with Axel Benikian about AI agents, the changing role of data science, and practical ways marketers can get more insight from the data they already have. Axel explains how his team uses AI to automate recurring analysis and presentation work, while emphasizing that useful insights still depend on access to good data. His advice to businesses: map your existing data first, use AI to explore what it can tell you, and turn to custom research when important questions can't be answered with public or existing data. Key takeaways AI is broadening access to data science. Coding may become less central to some roles, while more people use AI to build apps, models, and tools for business questions. AI can automate repetitive analytics work. Aksel's team uses Claude to help generate analyses and recurring PowerPoint reports, including brand trackers. Start with the data you already have. Map your internal data and connect it to the questions you want to answer before investing in new data collection. AI has limits when it comes to proprietary information. LLMs can help analyze available data, but they don't automatically have access to a company's private customer or business data. Custom research still matters. Interviews, focus groups, ethnography, and surveys can fill gaps when existing data can't answer new questions. Learn by doing. Aksel recommends experimenting with AI tools and sharing what you learn with others. Episode timestamps 00:27 —Aksel's background in aerospace engineering, consulting, and market research 02:36 — Will AI replace data scientists? 05:25 — AI agents: risks to jobs and opportunities for innovation 07:05 — How Aksel's team applies AI to marketing analytics 09:54 — Automating recurring analyses and PowerPoint reports 11:46 — How marketers can make better use of existing data 15:13 — When AI needs to be supplemented with custom research 15:47 — Staying curious and learning through hands-on experimentation Links Mark Fidelman's book, Agent Shock: agentize.com/book Aksel Bedikyan: OG Insights · Find Axel on LinkedIn

Stop Chasing AI Tools: What Marketers Should Actually Do With AI AI marketing is moving fast and the constant stream of new tools can leave even experienced marketers feeling behind. In this episode, Mark Fidelman talks with marketing educator Will Francis about how to put AI to work without getting swept up in the hype. Will shares why he recommends starting with one primary AI assistant, how desktop apps can help marketers work directly with their files, and why he prefers practical workflows over complicated agent hierarchies. He also walks through his own AI-powered dashboard, explains how he uses voice dictation throughout the day, and discusses where human judgment still matters. The conversation also covers Will's AI for Marketing community, which he said was planned to launch in mid-October at the time of recording. Key takeaways Start with one main AI workspace instead of trying every new tool. Look for useful outcomes—like organizing documents or creating a daily briefing—before building a complex AI setup. Treat AI agents as assistants that need direction and review; left unchecked, they can produce "work slop." Connect AI to the systems and data you actually use if you want a more complete picture. Make room for human judgment, strategy, and leadership—and step away from AI during the day. In this episode 00:04:20 Will's background and his practical approach to AI education 00:07:29 How to avoid getting overwhelmed by AI tools 00:10:30 Will's tool recommendations for marketers 00:12:30 Why he's skeptical of complex, always-on agent systems 00:18:02 Practical ways CMOs can get started with AI 00:22:09 AI as a sounding board—and the continuing role of human judgment 00:25:15 Will's daily AI workflow and custom dashboard 00:30:30 The AI for Marketing community and workshops Sign up for my book AgentShock  About Will Francis Will Francis is a marketing educator and creator with 25 years of experience, including work at MySpace, advertising agencies, and his own agency. He creates practical, no-hype content to help people use AI for marketing. Learn more: willfrancis.com