Agentic Compliance - Padraic O'Reilly - Cyber Saint - So What About AI Agents | Episode 47
In this insightful conversation, Philippe Trounev and Padraic O'Reilly discuss the evolving landscape of compliance and automation in cybersecurity. They explore the challenges and opportunities presented by AI agents, the importance of quality assurance, and the role of human oversight in maintaining effective compliance systems. The discussion also touches on the future of agentic compliance and the balance between automation and human involvement.https://www.cybersaint.ioand https://www.docsie.ioJoin us on Discord https://discord.gg/ceKz5d4b
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EP 46 - So What About AI Agents - Agentic SEO with Daniel Horowitz
SummaryIn this conversation, Philippe Trounev and Daniel Horowitz discuss the evolving landscape of SEO in the age of AI. They explore how traditional SEO practices are being disrupted by AI search results, the importance of adapting strategies to focus on middle and bottom funnel content, and the necessity of building topical authority and internal linking structures. Daniel shares insights on best practices for optimizing for AI search, emphasizing the need for comprehensive and specific content, as well as the importance of schema markup. The discussion highlights the challenges and opportunities presented by AI in the SEO field, and the need for continuous adaptation to stay relevant.TakeawaysSEO has shifted to a fragmented search landscape due to AI.Top of the funnel content is becoming less effective.Internal linking is crucial for AI crawlers.Building topical authority is essential for visibility.Content must be specific and comprehensive to rank well.AI search results are easier to manipulate, leading to disinformation.User behavior is changing; quick answers are preferred.The visibility model is replacing traditional click-through models.Schema markup is increasingly important for AI search optimization.The role of SEO professionals is evolving to be more strategic. TitlesNavigating the New SEO Landscape with AIThe Death of Top Funnel SEO StrategiesSound bites"Top of the funnel is basically dead.""You need to build topical authority.""Less is more for AI crawlers."Chapters00:00 Introduction to AI and SEO Strategies11:52 Building Middle and Bottom Funnel Content Strategies21:55 Implementing Best Practices for AI SEO27:31 The Future of SEO and AI IntegrationKeywordsAI, SEO, search optimization, digital marketing, content strategy, AI search, visibility model, schema markup, internal linking, topical authority
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So What About AI Agents - Navigating Compliance, Automation and Data Poisoning in the Age of AI
SummaryThis conversation explores the evolving role of AI in business, focusing on compliance, data management, and the automation of traditional roles. Philippe Trounev discusses the implications of AI technologies, including data poisoning, the replacement of product managers, and the ethical concerns surrounding AI agents in negotiations and monitoring. The discussion highlights both the potential benefits and risks associated with the increasing reliance on AI in corporate environments.KeywordsAI, compliance, data poisoning, product management, negotiation, automation, corporate safeguards, ethical concerns, technology, future of workTakeawaysAI is increasingly being used to enforce compliance in businesses.Data poisoning can be used strategically to influence AI recommendations.The role of product managers is being automated by AI technologies.AI agents are negotiating deals, potentially removing humans from the process.There are ethical concerns regarding AI's decision-making without human oversight.Companies are implementing safeguards against unauthorized AI usage.AI can be weaponized in competitive business environments.The future may see a separation between the internet for agents and humans.AI's ability to monitor and report can lead to unintended consequences.The landscape of business roles is rapidly changing due to AI advancements.TitlesAI's Impact on Business: Compliance and AutomationNavigating Data Poisoning in the Age of AISound bites"AI supposed to make our lives easier.""AI spotting kids over Doritos.""An agent has a conversation with a supplier."Chapters00:00 The Rise of AI Agents and Their Impact05:41 The Future of Product Management and Automation
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EP 45 - So What About AI Agents - Enterprise Implementation Playbook
KeywordsAI projects, hype vs reality, return on investment, success metrics, narrow use casesSummaryIn this conversation, Ammar Bhaisaheb discusses the critical aspects of initiating AI projects, emphasizing the importance of distinguishing between hype and reality. He advocates for a focused approach, where projects are defined by narrow use cases and measurable goals. The conversation highlights the necessity of modeling return on investment before embarking on any AI initiative, ensuring that projects are viable and worth the investment of time and resources.TakeawaysThe very first chat with clients is to separate hype versus reality.AI projects should be approached with a scalpel, not a will.Success in AI requires a narrow, super use case.Clear goals must be measurable for AI projects.Modeling return on investment is crucial before coding.Projects should aim for a three to five X return on investment.If a project can't deliver ROI, it's not worth pursuing.Focus on measurable outcomes to ensure project success.Narrow use cases lead to better-defined AI projects.Invest time only in projects that meet ROI criteria.TitlesNavigating the AI Hype: A Practical ApproachThe Scalpel Method: Precision in AI ProjectsSound bites"Separate the hype versus reality in AI.""Pick a narrow, super use case.""Clear goal that you can actually measure."Chapters00:00 Introduction to AI Agents and Their Impact00:07 Choosing the Right Use Cases for AI Agents00:43 Data: The Foundation of AI Success
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EP 44 | Why AI Can't Replace Enterprise Technical Writers (Yet)
John Brazier spent 25 years leading Oracle's technical documentation team, managing 394 books translated into 10+ languages. Today we discuss why AI-generated documentation fails at enterprise scale, the $12M translation problem, and why technical writers are evolving into "Knowledge Orchestrators."🔑 Key Topics:- Why enterprise documentation requires human wisdom, not just AI knowledge- The $500K cost of translating a single 500,000-word manual- How one comma can trigger a $40,000 retranslation- Revenue recognition regulations that make AI documentation illegal- The future role: Knowledge Orchestrator vs Technical Writer📊 Quick Stats:- 394 books in Oracle's documentation library- $12M initial translation cost for 6-product logistics suite- 500,000 translatable words per book- Translation costs: $0.06-$0.30 per word⏱️ Timestamps:00:00 Introduction02:28 The Scale of Documentation at Oracle04:41 Translation Challenges ($12M Problem)09:29 Knowledge vs Wisdom in Technical Writing16:36 The Future of Technical Writers31:39 Why Human Oversight Is Non-Negotiable#TechnicalWriting #AI #Documentation #EnterpriseAI #FutureOfWork
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