May 12, 2025 | AI
Given the insane adoption curve of GenAI tools like ChatGPT, Perplexity, and Claude, chances are youโve already already experimented with these single-use AI assistants. But the real breakthrough isnโt just about using one smart tool-itโs about orchestrating multiple AI agents to work together in real time. Welcome to the era of agentic AI.
Most people still experience these tools as black boxes: you type in a prompt, you get an answer, and you rarely see how the sausage is made. But beneath the surface, a radical shift is happening. Some of these platforms are quietly evolving into sophisticated, multi-agent systems-if youโre not watching closely, you might miss the transformation.
To make this tangible, Iโve created a ๐๐ถ๐บ๐ฝ๐น๐ถ๐ณ๐ถ๐ฒ๐ฑ ๐ถ๐น๐น๐๐๐๐ฟ๐ฎ๐๐ถ๐ผ๐ป ๐ผ๐ณ ๐ฎ๐ด๐ฒ๐ป๐๐ถ๐ฐ ๐๐ ๐ฎ๐ฟ๐ฐ๐ต๐ถ๐๐ฒ๐ฐ๐๐๐ฟ๐ฒ, (this architecture is based on the MAESTRO framework, designed with security in mind).
Unlike traditional automation, where every step is rigidly defined, agentic AI enables dynamic collaboration. In its most intelligent configuration, the AI is context-aware, with multiple AI agents coordinated across tools, workflows, and even departments-each acting semi-autonomously, and adapting in real time.
Hereโs a practical executive scenario: Letโs say youโre a Chief Product Officer preparing for a board meeting. Instead of manually gathering data, agentic AI agents automatically pull the latest product metrics, summarize customer feedback from multiple channels, highlight emerging trends, track competitor activities, and flag any risks-delivering a tailored briefing to your inbox before your morning coffee.
Understanding this architecture is key to unlocking next-level productivity and innovation. The only real limit? Your imagination, and the ability to connect the right systems and data sources.
Agentic AI is transforming the way we work. What will your team of agents do for your business?
Feb 25, 2025 | AI, Innovation
AI is transforming ๐ฐ๐๐๐๐ผ๐บ๐ฒ๐ฟ ๐ฒ๐
๐ฝ๐ฒ๐ฟ๐ถ๐ฒ๐ป๐ฐ๐ฒ๐, ๐ผ๐ฝ๐ฒ๐ฟ๐ฎ๐๐ถ๐ผ๐ป๐, ๐ฎ๐ป๐ฑ ๐ฑ๐ฒ๐ฐ๐ถ๐๐ถ๐ผ๐ป-๐บ๐ฎ๐ธ๐ถ๐ป๐ดโbut are we thinking about its full potential holistically?
I’ve been mapping out AIโs capabilities across front-end (customer-facing) and back-end (operations & intelligence) use cases. Itโs not meant to be exhaustiveโbut rather a starting point to spark discussion among senior business leaders about AIโs role in driving value.
From GPT-powered conversational agents to cybersecurity automation, from personalized recommendations to AI-driven forecasting, this framework lays out where AI is making an impact todayโand where opportunities might still be untapped.
๐’๐ฑ ๐น๐ผ๐๐ฒ ๐๐ผ๐๐ฟ ๐ถ๐ป๐๐ถ๐ด๐ต๐๐!
โข Am I missing key categories or use cases?
โข How are you leveraging AI in ways that arenโt widely discussed yet?
This is a ๐๐ผ๐ฟ๐ธ ๐ถ๐ป ๐ฝ๐ฟ๐ผ๐ด๐ฟ๐ฒ๐๐, and your input will help refine a more comprehensive view of AIโs evolving role in business.
ย
#AIย #ArtificialIntelligenceย #BusinessStrategyย #Leadershipย #DigitalTransformationย #AIUseCasesย ย #Innovation
Jan 20, 2025 | AI, Innovation, Strategy
๐ง๐ต๐ฒ ๐ณ๐ถ๐ฟ๐๐ ๐ฟ๐ถ๐ฝ๐ฝ๐น๐ฒ๐ ๐ผ๐ณ ๐๐ต๐ฒ ๐๐ด๐ฒ๐ป๐๐ถ๐ฐ ๐๐ ๐ฎ๐ฟ๐ฒ ๐ฏ๐ฒ๐ด๐ถ๐ป๐ป๐ถ๐ป๐ด ๐๐ผ ๐ฟ๐ฒ๐ฎ๐ฐ๐ต ๐๐ต๐ผ๐ฟ๐ฒ, bringing transformative changes to how we interact online. There are impressive examples of AI-powered assistants helping job seekers craft resumes and fill applications,ย to intelligent travel planners curating personalized itineraries via natural voice interaction. Youโd be forgiven to think youโre already experiencing these capabilities with the latest LLMs, but this next evolution of AI is a significant leap forward of the technology. These autonomous agents can analyze data, set goals, and take action to achieve them.
Beneath the surface, these AI agents will catalyze a seismic shift in how businesses operate. We’re entering the “agentic era” of digital connectivity. This new paradigm is not just about enhancing user interfaces; it has major implications on backend operations, data integration, analytics, customer service, privacy considerations, and much more. It is likely to be a messy landscape behind the scenes as established SAAS platforms seek to maintain their value with added AI features, while business leaders seek to break down data silos for greater insights by implementing Agents that can work across those platforms.
For CPOs, CTOs, and startup founders, this isn’t just a technological shiftโit’s a strategic revolution. Agentic AI will:
โ Break down data silos
โ Optimize operational workflows
โ Provide unprecedented analytical insights
โ Revolutionize customer experiences
As professionals, we must ask ourselves: How will these AI agents redefine our roles? What new skills will we need to thrive in this AI-augmented landscape? And most importantly, how can we harness this technology to create more value for our organizations and customers?
The future is here, and it’s powered by AI. Are you ready to ride this wave?
#GenerativeAIย #FutureOfWorkย ย #DigitalTransformation
Jul 15, 2024 | AI, Innovation
Over the past few days, I’ve been working on a side project that left me questioning the very core of prompt engineering.
A friend pitched an idea for a game: players need to find food-related anagrams within a recipe title. Heโd need hundreds of recipes and their associated anagrams. Seemed like a perfect use case for AI, right? My goal was to generate a few hundred recipe titles with their corresponding anagrams. I tried using increasingly complex, multi-step prompts, which brought me to the limitations of my prompt engineering skills. The results were disappointing, full of inaccuracies and undesirable results.
Out of frustration, I took a different approach. I asked the LLM (Large Language Model) itself for the prompts necessary to produce the results I wanted. The LLM provided an 8-step prompt sequence which showed me a few steps I had missed. Out of curiosity, I responded, “OK, do those steps,” and the results were astounding. Within seconds, I had 100 accurate recipe titles with their food-related anagrams.
This experience leads me to ponder: Is the skill of prompt engineering dead? If an AI can provide the optimal prompts itself, why would we need to invest the time to become good prompt engineers? I realize that this is provocational. Obviously I had to employ an intermediate level of prompt engineering to receive the correct steps, but itโs clear that the ability to formulate good questions remains an essential skill no matter if we are working with people or AI.
As we stand on the frontier of AI, it’s essential to continuously question and redefine our approaches. This experiment has shown me that sometimes, the best results coming from asking a simple question.
#AI ย #Innovation ย #ProductLeadership ย #PromptEngineering ย #FutureOfAI
Apr 15, 2024 | AI, Design, Innovation, Strategy
Today, Scott Belsky‘s latest insights in the Implications newsletter resonated deeply with me. He discusses a future of brands increasingly deploying AI agents as the primary interface, potentially leading to a landscape of disparate self-serving experiences, each thirsty for your data. This raises an important question about the emergence of platform-level agents, personalized to negotiate on behalf of individuals based on their unique data and preferences.
Several years ago at Spring Studio, we explored a similar concept for the banking sector, envisioning a future where a chatbot evolves into an AI-enabled โcompanionโ. Dubbed the โself-driving bank accountโ, this tool could autonomously manage funds to prevent overdrafts, optimize bill payments, and even advise on optimal timing for major purchases.
This evolution in digital interfaces could profoundly impact consumers, brands, and developers. As we navigate this shift, itโs crucial to consider how such innovations could redefine the customer journey, focusing on privacy, trust, loyalty, transparency, and interoperability.
What do you think the future holds for customer-brand interactions in an AI-mediated landscape?
https://lnkd.in/g9-S-TUJ
#AIBranding #CustomerExperience ย #DigitalBanking ย #FutureOfAI ย #BrandInnovation ย #TechTrends ย #AICompanions
