Empirique.io is a boutique consulting firm that partners with executives to align strategy, delivery, and product at scale.
We deliver short, high-impact engagements to help organisations accelerate outcomes, redesign delivery operating models, and instill lasting Agile capability from the top down.

Strategic Agility for Complex Organisations

Empirique Services

  • The Agile Operating Model Diagnostic is a premium, short-term consulting engagement that helps executive leaders assess, understand, and improve how their organisation delivers value through Agile practices at scale.

    It is designed to uncover systemic issues in structure, governance, decision-making, and team dynamics — and to provide clear, actionable insights to improve speed, alignment, and adaptability.

  • The Product Delivery Playbook is a tailored consulting engagement designed to help organisations codify how they deliver value from idea to customer — in a way that’s scalable, repeatable, and aligned with business strategy.

    It's ideal for scale-ups or enterprises that have multiple product teams but no consistent way of working, leading to misalignment, delivery delays, and diluted accountability.

  • The Executive Agile Advisory service is a high-trust, strategic coaching engagement for senior leaders — typically CTOs, Heads of Product, CDOs, and Delivery Directors — who are navigating Agile at scale and want targeted, experienced counsel to accelerate outcomes, align teams, and lead with clarity.

    This is not team coaching — it’s leadership-level advisory to address organisational complexity, decision bottlenecks, and delivery drag from the top down.

  • The Agile Team Accelerator is a rapid enablement program designed to quickly boost the performance of Agile teams — whether newly formed, underperforming, or under pressure to deliver.

    Unlike generic team coaching, this is a short, focused intervention that diagnoses friction, reboots ways of working, and helps teams gain clarity, confidence, and momentum — fast.

  • Our services are designed for executive leaders and delivery teams navigating complexity at scale. Whether you're a CTO, Head of Product, or VP of Engineering, we provide targeted advisory and enablement to help you align strategy with execution, unlock team performance, and scale delivery without chaos. From C-suite leaders seeking clarity on delivery operating models, to product organisations in need of a unified playbook, to under-pressure teams needing a performance reset — Empirique.io delivers high-impact outcomes that turn Agile from a process into a competitive advantage.

New Articles

Application of Generative AI Technology in Scrum

  • What is Inside the "AI Technology in Scrum" Document?

    The "AI Technology in Scrum" document explores how Generative AI is transforming Agile and Scrum frameworks by automating tasks, optimizing backlog management, and enhancing decision-making. The document is structured into several key sections:

    1. AI in Scrum Artefacts

      • AI tools analyze sprint backlog trends, suggest prioritization, and track progress using predictive analytics.

      • AI enhances backlog creation and validation by automating user story generation, detecting duplicates, and refining requirements.

      • AI-driven backlog risk analysis helps teams identify dependencies, workload issues, and bottlenecks.

    2. AI-Driven Scrum Roles Enhancement

      • Product Owners use AI for backlog prioritization, customer insights, and strategic planning with tools like Jira AI and Azure DevOps AI.

      • Scrum Masters leverage AI for sprint forecasting, risk detection, and automated reporting, using tools like Retrium AI and Atlassian Advanced Roadmaps AI.

      • Development Teams benefit from AI-powered coding assistants like GitHub Copilot and automated testing platforms such as Testim.io and Mabl.

    3. Enhancing Scrum Events with AI

      • AI improves Sprint Planning through intelligent backlog prioritization, workload forecasting, and risk assessment.

      • AI-driven Daily Scrums automate status updates, highlight blockers, and transcribe key discussions.

      • Sprint Reviews leverage AI-generated reports and stakeholder sentiment analysis.

      • Sprint Retrospectives benefit from AI-driven feedback analysis and improvement recommendations.

    4. Examples of AI in Scrum at Leading Companies

      • Amazon utilizes AI in backlog management, sprint planning, and anomaly detection with AWS DevOps Guru.

      • Google integrates AI for backlog optimization, code suggestions, and automated sprint reporting with Google Cloud AI.

      • Microsoft employs AI-driven backlog prioritization, sprint forecasting, and team productivity analysis with Azure DevOps AI.

      • IBM applies AI for coding assistance, backlog refinement, and predictive analytics using IBM Watson.

      • Tesla enhances sprint execution with AI-driven automation, predictive maintenance, and real-time backlog adjustments.

    5. AI Tools in Scrum: Pros and Cons

      • AI-powered backlog management tools like airfocus AI, Jira AI Dashboards, and Azure DevOps AIstreamline prioritization.

      • AI-driven standup bots such as Standuply AI and Geekbot improve daily team communication.

      • AI-powered testing and debugging tools like Testim.io and DeepCode automate quality control.

      • Challenges include AI biases, team resistance, and data privacy concerns, requiring organizations to balance AI automation with human oversight.

    6. Challenges and Ethical Considerations

      • AI insights can introduce bias, requiring human validation of automated recommendations.

      • Team resistance to AI automation necessitates a balance between AI-driven efficiency and Agile team autonomy.

      • Data privacy and security concerns arise when AI tools process sensitive sprint and backlog data.

    7. Conclusion

      • AI is revolutionizing Scrum, making Agile workflows more efficient, data-driven, and automated.

      • While AI enhances backlog management, sprint planning, and development efficiency, organizations must maintain human oversight to ensure transparency, accuracy, and ethical AI use.

      • Companies embracing AI in Scrum will gain a competitive edge by delivering software faster, improving team collaboration, and optimizing product development processes.

    The document provides real-world AI tool examples, company case studies, and references to industry research, making it a comprehensive guide for teams looking to integrate AI into their Scrum practices.

  • The "AI Technology in Scrum" paper is primarily intended for Agile practitioners, Scrum teams, and technology leaders who are exploring how AI can enhance Scrum methodologies. The target audience includes:

    1. Product Owners (POs)

      • Helps POs understand how AI tools can assist in backlog prioritization, refinement, and risk assessment.

      • Demonstrates how AI-driven insights can improve decision-making based on historical data and customer feedback.

    2. Scrum Masters (SMs)

      • Guides Scrum Masters in leveraging AI for sprint forecasting, risk detection, and team performance tracking.

      • Provides AI-powered solutions for facilitating retrospectives, stand-ups, and sprint reviews.

    3. Developers & Agile Team Members

      • Explains how AI-powered coding assistants like GitHub Copilot and Google Gemini Code Assist enhance productivity.

      • Showcases AI-driven automated testing, bug detection, and backlog refinement to streamline development workflows.

    4. Agile Coaches & Consultants

      • Provides insights into the latest AI trends in Agile methodologies and how AI can optimize Scrum workflows.

      • Offers real-world examples from companies like Amazon, Google, Microsoft, IBM, and Tesla to support AI adoption strategies.

    5. Technology & Engineering Leaders (CTOs, CIOs, VPs of Engineering)

      • Helps decision-makers assess the impact of AI on Agile project management and software development.

      • Demonstrates how AI can improve sprint efficiency, backlog management, and overall product delivery.

    6. Organizations & Enterprises Adopting AI in Agile

      • Serves as a reference for companies integrating AI into Scrum frameworks to enhance productivity and agility.

      • Highlights best practices, challenges, and ethical considerations when implementing AI in Scrum.

    Overall Purpose of the Paper

    This paper is designed for anyone looking to integrate AI into Scrum—whether to enhance productivity, automate repetitive tasks, improve decision-making, or streamline Agile processes. It provides a practical guide, tools, and examples to help Agile teams embrace AI without compromising agility and collaboration.

Innovation and the MVP - The Achilles Heel

  • Innovation is the driving force behind business success, but many startups and enterprises struggle with transforming an idea into a viable product. The Minimum Viable Product (MVP) serves as the foundation for testing a concept, gathering user feedback, and making informed decisions about whether to pivot or persist. However, emotional attachment, cognitive biases, and internal pressures can cloud judgment, leading to flawed decision-making. This is where an external objective viewpoint plays a crucial role. External advisors, mentors, consultants, or services like Empirique can provide unbiased insights, ensuring that MVP validation is data-driven rather than emotionally driven.

    The Pitfalls of Internal Bias in MVP Development

    How External Validation Ensures MVP Success

    Long-Term Impact on Innovation Success

  • This article is designed for startup founders, product managers, innovation leaders, investors, and Agile practitioners who are involved in developing Minimum Viable Products (MVPs) and scaling innovation projects. It is particularly beneficial for:

    • Entrepreneurs & Startup Founders – Understanding how to validate ideas without emotional bias and when to pivot or persist.

    • Product Managers & Innovation Teams – Learning best practices for data-driven decision-making in product development.

    • Investors & Venture Capitalists – Evaluating whether startups have solid validation processes before investing.

    • Agile Coaches & Business Consultants – Using external validation methodologies to guide teams towards successful MVP execution.

    • Corporate Innovation Departments – Ensuring large enterprises follow lean and validated innovation strategies to minimize failure risks.

    By providing insights into external validation, objectivity in MVP development, and structured decision-making frameworks, the article serves as a comprehensive guide for anyone looking to increase the success rate of their innovation projects.

At Empirique.io, we combine strategic clarity with system-level thinking. That’s why we built Agorik, the AI coach for Agile delivery. It’s powered by our own transformation playbooks and a structured, contributor-backed knowledge base.


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At Empirique, we believe Agile is a conversation—one shaped by clarity, curiosity, and courage.
We build systems that prioritize evidence over ego, contribution over control, and systems thinking over short-term wins.

Agorik is our community initiative: a community-built AI designed to democratise Agile expertise, credit real practitioners, and evolve with every contribution.

Our tools are open by design and guided by a singular mission—to help teams learn faster, deliver better, and transform together.
Because real agility isn’t about doing more—it’s about learning better, together.