More The AI Report Live episodes
Published 7 May 2026
Duration: 01:06:06
Strategies for viral content include reverse-engineering successful formats, platform-specific tactics (like LinkedIn lists, Instagram B-roll), leveraging AI tools for research and automation while prioritizing human creativity, and balancing consistency, personal branding, and iterative refinement to overcome challenges like content theft and maintain authenticity.
22,000 LinkedIn followers to over 210,000 in just over a year. Charlie Hills did not get there by luck. He got there by reverse engineering what alrea...
The podcast explores strategies for creating viral content by emphasizing reverse engineering proven formats and topics across platforms like LinkedIn and Instagram. It highlights the importance of combining pre-validated frameworks with original ideas, using platform-specific formats (e.g., lists, comparisons) to enhance virality, and addressing challenges like declining organic reach on LinkedIn. AI is presented as a tool for research and trend analysis but not a replacement for human creativity, with a focus on balancing AI-generated drafts with human curation to maintain authenticity and unique branding. Key principles include prioritizing clarity and simplicity in content, iterative refinement of scripts, and leveraging tools like Appify and Claude for automation, scheduling, and data analysis. The discussion also addresses challenges in the creator economy, such as content theft and lack of originality, while advocating for "stealing like an artist" to remix content creatively.
Workflows for content creation involve a hybrid AI-human approach, with tools like Claude and Gemini automating tasks such as script generation, infographic design, and social media scheduling, while human input ensures quality and personalization. The podcast details strategies for LinkedIn growth, such as high-quality daily posting and structured content creation using tools like Notebook LM, and Instagram-specific tactics like B-roll visuals and clear, concise scripting. It also covers the development of a SaaS tool (VSLO) for generating branded infographics, emphasizing the need for platform diversification beyond LinkedIn to YouTube and TikTok due to algorithmic challenges. Themes of work-life balance, passion-driven content creation, and the importance of personal branding are woven throughout, alongside reflections on transitioning from traditional employment to entrepreneurial ventures and the role of self-reliance in career growth.
11 Jun 2026 The Future of Work Is Less AI and More Human Than You Think | Aaron Mitchell Finegold, Adobe
The intersection of AI and finance is analyzed through funding's influence on AI/crypto trends, agentic content workflows, risks of unregulated AI, the need for human-AI balance in creativity, brand compliance systems, and strategies for trustworthy AI implementation in evolving work dynamics.
28 May 2026 AI Traffic to Retail Is Up 393%. Here Is What That Means for Your Business | Vivek Pandya, Adobe
Generative AI is reshaping e-commerce with a 393% rise in retail traffic and 40% of U.S. consumers using AI in purchasing, urging brands to optimize content for machine readability via GEO strategies, improve conversion rates, and adapt to demand for personalized, seamless shopping experiences.
21 May 2026 Inside the Rise of AI Employees and Autonomous Workforces | Swati Trehan
A centralized AI-driven platform streamlines enterprise workflows through autonomous multi-step task agents, modular integration, governance features, and scalable solutions tailored for HR, finance, and IT, emphasizing efficiency, user experience, and differentiation from competitors via non-reliance on single AI models.
19 May 2026 Anthropic vs OpenAI Just Got Serious + xAI Faces Environmental Backlash | AI News in 5
Recent AI advancements include Anthropic's B2B focus on behavioral reliability, OpenAI's enterprise integration, and Daybreak's GPT-5.5 cybersecurity platform, alongside rising environmental and regulatory challenges in AI development.
14 May 2026 Why Data (Not Code) Is Your Only Real AI Moat | Jason Li, Laurel
Data-driven workflow optimization in knowledge-intensive fields like law and accounting is highlighted through AI-powered time-tracking solutions that automate logging, enhance performance measurement with actionable insights, and address challenges like ROI demonstration, legacy system integration, and balancing automation with human-centric tasks, while emphasizing core data as a strategic competitive advantage.