Duality

We’re thrilled to unveil?Nigel, Duality’s revolutionary AI-agentic platform that is transforming the way software is developed. Powered by Model Context Protocol (MCP) and introduced today by his HeyGen avatar, Nigel takes agent-based development from concept to reality, streamlining workflows, accelerating productivity, and enabling teams to build smarter, faster, and more creatively than ever before. Nigel integrates seamlessly with tools like GitHub, Slack, Jira (Atlassian), and your codebase to unify disconnected processes into a single, cohesive experience. It captures requirements in real time, generates tasks instantly, and turns natural language into production-ready code. Nigel does not just solve problems; it transforms how teams approach product development. With the ability to solve integrations once and reuse them across projects, Nigel is scalable for any challenge, including building itself. Want to see it in action? Check out the video in the comments to explore how Nigel is already reshaping product development, streamlining everything from code changes to issue tracking and more. Where do you see the biggest opportunity for AI-agentic technology in your work? #AI #Innovation #SoftwareDevelopment #Duality #Nigel cc: Demis Hassabis Arthur Mensch Alexandr Wang Brett Adcock Steve Gu Ilya Sutskever Andrew Ng Amjad Masad

Most PMs know documentation is important, but few enjoy spending their extra time on it. Yesterday I discussed how creating a foundational documentation hub was the critical first step to building a successful AI-driven product management workflow. We've all experienced how inadequate documentation can lead to challenges down the road. I've long observed that the most passionate, customer-focused product managers often struggle the most with documentation. They'd rather be talking to users, refining the product, or working with developers than updating PRDs and status reports. This is exactly where AI tools create their most immediate value for product teams. Here's a framework for intelligently automating your documentation burden: ?? Core Documentation Types ? Requirements and specifications ? Project plans and status reports ? Meeting notes and action items ? Decision logs and knowledge bases For each type, there's a consistent workflow that yields better results: ?? Step 1: Template Creation Define standardized templates for each document type with clear sections, formatting standards, and quality criteria. AI works best when it has consistent structure to follow. ?? Step 2: Update Triggers Identify what events should automatically trigger documentation updates: meetings, requirement changes, code commits, stakeholder feedback. This creates a continuous documentation system rather than periodic, manual efforts. ??? Step 3: Review Process Establish appropriate human oversight (humans-in-the-loop) based on risk level: high-stakes documents need full review, routine updates might only need spot-checking. The key is matching the right level of oversight to each document type. What's transformative isn't just the time saved (though that's substantial) - it's the comprehensive coverage. When documentation updates automatically, nothing (or at least much less) falls through the cracks. Your team always has current, complete information to work from. By focusing on improving documentation with AI tools, teams can drastically reduce the time they spend on documentation while still dramatically improving quality and completeness. Even better, when PMs aren't buried in documentation tasks, they can focus on strategic work and customer engagement. What documentation tasks consume most of your time? Which would you most like to automate? Check out our AI-Driven Product Management Playbook (link in comments) for specific templates and automation workflows you can implement today. #ProductManagement #AI #DocumentationAutomation #ProductOps #AIProductivity #ProductDevelopment #AgileDocumentation

The most common question I get after sharing ideas about AI-driven product management is: "This all sounds great, but where do I actually start?" It's a fair question. Transforming your product development process doesn't happen overnight, and trying to change everything at once usually leads to frustration. After implementing AI-driven approaches across multiple projects, I've found that successful adoption follows a predictable sequence: ??? Phase 1: Foundation Setup ? Create a central documentation hub that serves as your single source of truth ? Systematically collect and organize context about your product, users, and objectives ? Configure initial AI tools with appropriate access to your knowledge base This foundation is critical. Without a centralized, accessible knowledge repository, your AI tools lack the context needed to produce valuable outputs. ?? Phase 2: Blueprint and Discovery ? Use AI-enhanced sessions to define your product vision and strategy ? Leverage AI tooling to help you analyze available user feedback and competitive data ? Leverage AI tooling to cross reference and combine insights across multiple sources. Also have it highlight discrepancies and open questions. What's powerful here is the comprehensiveness. Instead of analyzing samples of data, AI can process everything, finding patterns human analysis might miss. ?? Phase 3: Requirements and Planning ? Transform high-level objectives into detailed requirements using AI orchestration ? Establish automated synchronization between documentation, engineering workflows, and project management tooling ? Implement verification workflows and feedback loops to ensure quality and consistency This is where many teams see their first significant productivity gains. Requirements that once took days to document can be generated in hours, with greater consistency and fewer gaps. The key insight I've had is that this sequence matters. Teams that try to jump straight to automated requirements without establishing a solid foundation typically create more problems than they solve. Start small, measure the impact, and expand gradually as you build confidence in your approach. Where are you in this implementation journey? And what's been your biggest challenge in adopting AI-driven product management? Check out our AI-Driven Product Management Playbook (link in comments) for detailed guidance on implementing each phase of this framework. #ProductManagement #AI #ImplementationFramework #AIProductManagement #ProductOps #DigitalTransformation #AIAdoption

When most people start working with AI tools, they make a fundamental mistake: treating each interaction as an isolated task. This is similar to the issue I mentioned yesterday: we've been programmed to provide concise search phrases to Google for quick results. "Generate a competitive analysis between company A and B." "Summarize this user feedback." "Draft a product spec for user login." "What car should I buy?" The results might be... fine. They definitely won't be great and you probably won't see the transformative impact you may have been expecting. That's because this approach to AI uses the wrong mental model. You'll only start to produce the transformative results you may have been hoping for when you shift from task thinking to system thinking. Instead of viewing AI as a tool to complete individual tasks, you need to begin seeing it as a component in interconnected workflows. Here's how this shift transforms product management: ?? Task Thinking: ? Focuses on isolated, disconnected activities ? Requires manual handoffs between steps ? Optimizes for individual execution speed ? Creates bottlenecks (you) between processes ?? System Thinking: ? Designs end-to-end connected workflows ? Creates automated handoffs between components ? Optimizes for overall system effectiveness ? Eliminates bottlenecks through orchestration Consider a monthly user feedback process. With task thinking, you might use AI to categorize feedback (one task) and then manually take that output to generate insights (another task). With system thinking, you design a workflow where feedback collection automatically flows to categorization, to analysis, to insight generation, to distribution - with you orchestrating the flow rather than serving as the integration point between each step. The key to effective system thinking is workflow mapping - visualizing the complete process from inputs to outputs and designing clear interfaces between components. This means defining exactly how information moves between steps, what triggers each action, and where human judgment adds the most value. This mindset shift doesn't happen overnight, but it's where the true power of agentic product management emerges. It's the difference between getting incremental productivity gains and completely transforming how you work. Where in your product process could you benefit from shifting from task thinking to system thinking? Check out our Agentic Product Management Playbook (link in comments) for frameworks to help you map your own agentic workflows. #ProductManagement #AI #SystemThinking #AgenticSystems #Workflows #ProductOps #AIOrchestration

As AI capabilities begin to transform product development, I'm seeing a fundamental shift in how successful PMs can better allocate their time and energy. A Human-Agentic Pyramid can help to illustrate this transformation: ?? At the top of the pyramid are high-value strategic activities: ? Setting vision and identifying market opportunities ? Building relationships and securing stakeholder alignment ? Creative problem-solving and innovation ? Critical analysis of complex data patterns ?? At the base are routine execution tasks: ? Creating and maintaining documentation ? Gathering and organizing information ? Coordinating follow-ups and status updates ? Processing basic feedback and metrics The agentic PM can focus at the top of the pyramid while thoughtfully delegating tasks at the bottom to AI systems they orchestrate. Their core product management responsibilities remain the same—it's how PMs allocate their time and energy that transforms, with more focus on the activities that create the greatest value. What makes this evolution powerful is that it strengthens the PM role by allowing more time for strategic impact. By spending less time on routine execution and more on strategy, PMs can have greater influence across more initiatives while experiencing less burnout. PMs can transform their effectiveness by climbing this pyramid, shifting from overwhelmed individual contributors to strategic orchestrators who leverage AI capabilities. Where do you currently spend most of your energy on this pyramid? What would change if you could reallocate your time toward the top? Check out our Agentic Product Management Playbook (link in comments) for frameworks to implement this approach in your organization. #ProductManagement #AI #AgenticSystems #ProductStrategy #Leadership #FutureOfWork #AITools

I'm excited to share Duality's playbook for Agentic Product Development! As we've been building Nigel (trynigel.ai), we've developed a comprehensive framework for how product teams can leverage AI agents to transform their development process. Rather than keeping these insights to ourselves, we've compiled them into a practical guide for product leaders navigating this rapidly evolving landscape. Our playbook explores how PMs can evolve from doers to orchestrators—focusing on strategic thinking and creative problem-solving while delegating routine tasks to AI partners. It includes frameworks, checklists, and real-world examples to help you implement these concepts immediately. The playbook itself is a product of the agentic workflows it describes—I orchestrated AI tools to help research, organize, and craft the content while maintaining strategic direction and quality oversight. This approach allowed me to create a more comprehensive and useful guide than would have been possible through traditional methods alone. The best part? This is a living document, and we genuinely want your feedback so we can improve it. What resonates? What doesn't? What sounds like it was written by a robot? What did I get wrong? Your insights will help make this resource more valuable for everyone. Link to the book in comments below. A big thanks to Scott Silvi, John Thorstad, and entire Duality team in helping to create the framework that allowed us to put this playbook together. #ProductManagement #AI #AgenticSystems #Productivity #Leadership #ProductDevelopment #AITools #ChatGPT #MCP #Anthropic #Claude

Scott Silvi and the team at Duality have been working hard to build, refine, and push Nigel to its limits, solving the real problems product and engineering teams face. Messy handoffs, lost context, and decisions that disappear into the void. No more. Nigel captures critical details, asks the right questions at the right time, and keeps teams fully aligned from idea to execution. We’ve been talking about it. Now it’s time to get Nigel into the real world. The waitlist is open. If you’re ready to get your hands on it, sign up now. Check the link in the comments. #AI #Automation #Nigel #AgenticDevelopment #ProductManagement #SoftwareEngineering #FutureOfWork #ScottSilvi

Work as we've known it isn't broken. It's just... well... becoming a bit unnecessary. At least, that’s where things are headed. Over the past couple weeks, Scott Silvi and David Scott have been talking about something we’ve all felt coming. AI isn’t just speeding up work, it’s making a lot of it disappear. Nigel isn’t another AI assistant. It’s the interface to intelligence itself. No more bouncing between dashboards, formatting decks, or searching for tools. Just ask. It thinks, plans, acts, and when needed, checks in for approval. What’s happening right now?? -AI agents that clear mental overhead – Nigel handles the repetitive stuff so you can focus on real work? -Bidirectional workflows – Agents spin up, map out their plan, check in via Slack, text, or email, then execute? -Software development without the grind – Engineers aren’t just writing code. They’re orchestrating AI agents to build and ship faster? -Busywork is fading away – No more searching, formatting, or waiting. Just ask Nigel for a report, an update, or a presentation. Done in seconds. Every issue that gets accepted now follows the same flow:? -AI agent spins up in a secure container? -Runs a plan stage and checks in? -Toggles from “Plan” to “Act” once approved? -Submits a PR. Hands-free, but always human-approved People are seeing this for the first time and realizing there’s no going back. The work that used to take a week is happening in a day, maybe less, and the pace is only picking up. We’re shipping another leap forward in early February. If you’re already building with AI agents, let’s compare notes. If you’re not, now’s the time. Duality can help. #ScottSilvi #Duality #AIAgents #FutureOfWork #AutomationRevolution #AgenticAI #AIProductivity cc: Dario Amodei?Demis Hassabis Emad Mostaque Jensen Huang Noam Shazeer Nathan Benaich

Making business decisions at the speed of light? Yeah, Nigel does that. We’ve shown how Nigel helps build software, but it’s just as powerful for running a business. Executives, product managers, and decision-makers can get instant insights. No bouncing between windows and windows of dashboards, no context switching, no interrupting the team. Just natural language queries that pull real-time data across systems. Need a report? A board-ready presentation? Done in seconds. No blank canvas, no scrambling, just AI-powered execution. Watch Scott Silvi walk through how Nigel makes decision-making frictionless. The future isn’t coming... it’s already here, courtesy of Duality.

Check it out!! David Scott and Scott Silvi (or at least their HeyGen avatars ??) break down the buzz around AI agents: what they are, what they’re not, and why they’re game-changers for 2025 and beyond. From dynamic decision-making to next-level adaptability, agents are reshaping the AI landscape. Got questions or want to share your thoughts? Leave a comment! #AI #Agents #Innovation #Duality #HeyGen