Yousuf Idris’ Post

How to build an AI Product: We don't totally know. We're all still learning. ⬇️ ----------------------------------------------------------------------- So why don't we know? Processes follow in the wake of tech waves. Seizing a market share is often the priority. So, product processes take time to develop. Then folks need time to train on ops and workflows. But it comes with three difficulties I keep seeing: 𝐃𝐚𝐭𝐚.  You'll see this keep popping up. Data needs to be the focus before you build any AI product. Products keep getting built without understanding it. Failed LLMs keep showing up because business didn't understand the data or context. Sourcing, cleaning, and managing data are critical challenges even for analytics. Its 10x more important for AI. 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰.  We're still trying to figure out the order of AI product development tasks. It is also vital to ensure smooth handoffs and problem discovery. Problem discovery as part of the workflow often get overlooked - especially if we think data is enough. 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦.  This is tricky. You find out scaling is part of the battle. Picking and scaling the right AI infrastructure and platform. You can have a great model. But latency can hurt customer experience. Or you can't scale it to meet user requests. So can the wrong platform - mobile is different than desktop. Logistics and ops is the difficulty here. Building the AI product will require support. It also will need people trained in these processes. Those that can? Will be able to pivot quickly. They'll be able to roll out AI products faster from curated data sets. We may not know right now. but we're sitting on a blue ocean for AI Products. #ai #datascience #ml #product #productmanagment

According to Bloomberg Intelligence, the GenAI market is on track to hit $1.3 trillion over the next decade, skyrocketing from its $40 billion value in 2022. This growth presents a golden opportunity for leaders eager to weave AI into their product offerings. To help you get started, this article from Forbes offers some practical steps and key things to keep in mind. - Kickstarting an AI-friendly environment means assembling a diverse AI team ready to address everything from data privacy to legal matters. - When it comes to putting AI into action, think small to win big. Focus on crafting solutions that meet your customers' needs head-on, ensuring they see direct benefits. - When rolling out GenAI applications, use a strategy that allows for careful tuning and adjustments, ensuring your offerings meet and exceed customer expectations. - Embracing GenAI to oversee the quality of GenAI-driven content offers an intelligent way to ensure your content remains top-notch and authentic to your brand's values. How do you envision GenAI revolutionizing your field or business? https://lnkd.in/eR63Xs4z #GenAI #Technology #ProductDevelopment

Product Management Framework that will help you build your Gen AI Product Responsibly. Attended an insightful webinar 'Responsible Product Design with Generative AI' by Shyvee Shi on Data Science Dojo Here are my Key Takeaways from the session: 💡 Gen AI trend is here to stay. 💡 Most Gen AI startups are in the foundation state. 💡 How to design a delightful and responsible Gen AI product. 💡 Identifying the best suitable use case for Gen AI - How important is it for the generated content to be read manually? - How critical is the accuracy of the information in your use case? - How often does the use case occur? - Can we measure process efficiency gain between pre vs post AI workflows? - Can we measure the tangible money $$$ impact of the AI outputs? - How confident the AI outputs will be useful to users? What is the risk of hallucination? - Do we have the data sets to draw from to do something that others can't? - Is this use case unique enough to prevent it from becoming a commodity? 💡 Humans still have agency, the ability to give feedback, and key decision-making powers in their hands. 💡 Book Recommendations: 📖 The Coming Wave: Technology, Power, and the Twenty-first Century's Greatest Dilemma 📖 Reimagined: Building Products with Gen AI 📒 Sharing my webinar notes. #responsibleAI #productManagement #GenAI #Notes #Webinar

According to Bloomberg Intelligence, the GenAI market is on track to hit $1.3 trillion over the next decade, skyrocketing from its $40 billion value in 2022. This growth presents a golden opportunity for leaders eager to weave AI into their product offerings. To help you get started, this article from Forbes offers some practical steps and key things to keep in mind. - Kickstarting an AI-friendly environment means assembling a diverse AI team ready to address everything from data privacy to legal matters. - When it comes to putting AI into action, think small to win big. Focus on crafting solutions that meet your customers' needs head-on, ensuring they see direct benefits. - When rolling out GenAI applications, use a strategy that allows for careful tuning and adjustments, ensuring your offerings meet and exceed customer expectations. - Embracing GenAI to oversee the quality of GenAI-driven content offers an intelligent way to ensure your content remains top-notch and authentic to your brand's values. How do you envision GenAI revolutionizing your field or business? https://lnkd.in/gQbCmTsG #GenAI #Technology #ProductDevelopment

I’ve been blown away by the insights shared at INBOUND24 around AI and its growing role in business. Here are some of the top points I’m taking away: 👉 AI is a powerful accelerator: It’s not just about adding cool new features; it can fundamentally transform how businesses operate. 👉 Data quality is everything: AI is only as effective as the data it’s given. Ensuring both structured and unstructured data is accurate is key to unlocking AI’s full potential. 👉 HubSpot’s focus: There’s a big push toward enabling businesses to manage their data better, powering AI tools for smarter customer insights. 👉 Customer success starts with data: The biggest opportunity lies in helping customers improve the clarity and quality of their data, setting them up for long-term success. Can’t wait to share these insights with the team! #AI #DataQuality #INBOUND2024 #HubSpot #SeekEvolution

🔧 Unlocking the Power of Tool-Calling in AI 🚀 Imagine an AI that doesn’t just answer questions but takes action—retrieves data, executes commands, and completes tasks autonomously. That’s the transformative power of Tool-Calling! 🤖 What is Tool-Calling? Tool-calling allows AI agents to interact with external resources like APIs, databases, and software systems. It bridges the gap between intelligence and action by enabling AI to: 📊 Fetch real-time data, such as stock prices or weather updates. 🛠 Run complex workflows, like code execution or multi-step tasks. 🔗 Connect and act: Access systems, analyze outputs, and adapt in real time. ✨ Why Tool-Calling is Revolutionizing AI Tool-calling is already reshaping industries: 🏥 Healthcare: Assisting in diagnoses by accessing patient data and research. 💼 Finance: Automating trades by analyzing real-time market conditions. 🛒 E-commerce: Smart assistants checking inventory, applying discounts, and finalizing purchases. It’s turning AI into a proactive problem-solver, helping businesses automate processes and enhance user experiences like never before. ⚠️ Challenges We’re Tackling Tool-calling comes with unique hurdles, such as: ⏱ Managing Latency: Ensuring rapid response times while interacting with multiple tools. 🧠 Maintaining Context: Integrating data from various sources without losing coherence. ⚖️ Balancing Autonomy: Designing AI that’s proactive but stays within safe boundaries. 🌟 What’s Next? As tool-calling evolves, AI will become an even greater enabler of automation, efficiency, and innovation. From real-time decision-making to seamless task execution, the possibilities are endless. 💡 Ready to explore how tool-calling can transform your business? Let’s connect! #ToolCalling #AIInnovation #Automation #ArtificialIntelligence #FutureOfWork #SmartAI #TechForBusiness #DigitalTransformation 🔧🤖🚀

🚀 Exciting News! OpenAI just released Swarm! The AI world is buzzing with the release of Swarm, a new framework for multi-agent systems that's reshaping what's possible. Imagine AI agents working together effortlessly to tackle complex tasks—what seemed impossible just yesterday is now within reach! These AI agents are like digital helpers designed to perform tasks for us. While we're still in the early stages, they're already making a difference in areas like managing schedules and automating routine business tasks. Here's a quick look at how Swarm, CrewAI, and LangGraph stack up: 🔍 A Quick Look at Swarm, CrewAI, and LangGraph: 1. Swarm by OpenAI Focus: Simple coordination among multiple agents, perfect for straightforward workflows. Strengths: Ideal for tasks like customer support or supply chain management—lightweight and easy to set up. Limitations: Not great for complex workflows; lacks built-in memory and advanced error handling. 2. CrewAI Focus: Highly customisable for business automation, allowing agents to perform specialised tasks. Strengths: Excels at automating business processes like HR, marketing, and data handling, with good error-handling capabilities. Limitations: Can struggle with tasks that change frequently or need heavy info sharing. 3. LangGraph Focus: Graph-based approach for structured, complex projects with many interdependencies. Strengths: Great for big projects like software development, where tasks are connected and need flexible error handling. Limitations: Overkill for simple, straightforward tasks. The potential is limitless! These AI advancements can transform industries by: Speeding up customer service with smarter problem-solving Optimising supply chains through seamless AI collaboration Making project management more efficient with AI understanding complex dependencies I'm excited to see how these tools will change the way we work. Are you ready for the collaborative AI revolution? Let's talk about how these innovations could impact your industry. Drop your thoughts below! 👇 #AI #OpenAI #Swarm #FutureOfWork #Automation #TechInnovation #ArtificialIntelligence

Learn how to craft a winning product vision that thrives amid rapid market changes and AI disruption. This guide shows you how to leverage AI's potential while staying aligned with your business goals.

Driving business growth leveraging AI mandates a dive-deep hands-on lifelong learning. It was so much fun getting hands-on with Agents to understand the state of Agents based innovation, and patterns to leverage them. Firstly, AI based Code generation has improved dramatically, even since the last 3 months. I had 8+ tools and technologies integrating together automomously, including Slack, Sheets, web, search, and LLM based Code generation was highly accurate, with 80% + productity gains. Here are the top take-aways from my experience: 1/ Fine-Grained Orchestration: Successful AI Agent deployment requires highly orchestrated, detailed instructions. Without careful design, agents will produce inconsistent results, especially when complex business processes are involved. 2/ Human-in-the-Middle: When decisions involve business-sensitive areas, it’s essential to keep a human in the loop. While agents offer significant capabilities, leaving them to make decisions autonomously can be risky, as they operate with a 'brain of their own.' 3/ Agent Frameworks are Not Production-Ready Yet: While AI software is maturing at an impressive pace, current agent frameworks remain in early development stages. They’re powerful but not yet robust enough for critical systems deployment. As the technology continues to evolve, careful planning, oversight, and human collaboration will be key to unlocking the potential of AI Agents in real-world settings. Great collaborating with 🟢 Amir Feizpour @Mykola #AI #AIAgents #CIO #CTO #FutureofWork

🚨Fueling the Flywheel Effect with 🤖Agentic AI! As AI assistants automate tasks and learn autonomously, they'll generate HUGE amounts of new 📊data. This "fuels" the flywheel effect! Each task an agent completes creates more training data, making it smarter with every experience 🧠. Agents also learn from each other through this shared data 🔄. Done right, this creates a continuous cycle of transformation within businesses!🔁 But simply having agents isn't enough - companies must strategically guide this flywheel effect. Only by taking an "enterprise AI" approach can organizations ensure their agent army is properly optimized to maximize results from all that valuable hidden data. 💪 How will YOUR business engage agentic AI to ignite its data flywheel and fuel non-stop innovation? The future is flywheel - are you ready to hit the gas? 🏎️ ➡️ https://dell.to/3TOIxfN #iwork4dell