https://engineering-leadership.hinshelwood.com/tags/agentic-engineering/ Recent content in Agentic Engineering on Engineering Leadership in AI & Software Hugo en Tue, 16 Jun 2026 17:40:35 +0000 https://engineering-leadership.hinshelwood.com/articles/telling-people-what-to-do-is-not-leadership-it-s-a-failure-of-system-design/ Mon, 04 Aug 2025 09:00:00 +0000 https://engineering-leadership.hinshelwood.com/articles/telling-people-what-to-do-is-not-leadership-it-s-a-failure-of-system-design/ Telling people what to do is not leadership, it is a sign of poor system design that stifles autonomy and slows delivery. Effective leadership means creating systems where teams have clear goals, constraints, and feedback loops so they can self-manage, deliver value, and adapt without micromanagement. Focus on improving your delivery system, set meaningful goals, enable autonomy with clear boundaries, use evidence-based metrics, and empower teams to own outcomes, so you can step back and let professionals do their best work. https://engineering-leadership.hinshelwood.com/articles/are-we-still-pretending-coding-was-the-bottleneck/ Mon, 01 Sep 2025 09:00:00 +0000 https://engineering-leadership.hinshelwood.com/articles/are-we-still-pretending-coding-was-the-bottleneck/ AI writing code is not the real game-changer; coding was never the main bottleneck in software delivery. The real constraints are in poor system design, handoffs, unclear requirements, and lack of built-in quality, which AI will only make more visible. To benefit from AI, focus on improving flow, building quality in from the start, and making teams accountable for outcomes rather than output. https://engineering-leadership.hinshelwood.com/signals/rethinking-dev-test-staging-production-pipelines-for-safety/ Fri, 21 Feb 2025 16:30:30 +0000 https://engineering-leadership.hinshelwood.com/signals/rethinking-dev-test-staging-production-pipelines-for-safety/ Traditional Dev-Test-Staging-Production pipelines give a false sense of security because staging environments do not truly reflect production, leading to missed issues and wasted resources. Modern teams should focus on releasing to small user groups in production and using real feedback to guide rollouts. Consider shifting from heavy pre-release testing to faster, data-driven feedback in production to improve safety and efficiency. https://engineering-leadership.hinshelwood.com/articles/how-lack-of-agency-is-killing-your-devops-initiatives/ Mon, 16 Jun 2025 09:00:00 +0000 https://engineering-leadership.hinshelwood.com/articles/how-lack-of-agency-is-killing-your-devops-initiatives/ DevOps only works when developers have real control over production environments, deployments, and telemetry; without this operational agency, automation just creates fragile systems and blocks learning from real user feedback. Most DevOps efforts fail because they focus on tools instead of empowering developers to deploy, monitor, and adapt in production. To succeed, give your teams full operational ownership so they can deliver value continuously and respond quickly to real-world issues. https://engineering-leadership.hinshelwood.com/articles/the-missing-lever-in-agile-transformations/ Mon, 02 Jun 2025 09:00:00 +0000 https://engineering-leadership.hinshelwood.com/articles/the-missing-lever-in-agile-transformations/ Agile transformations often fail because they focus on following ceremonies instead of building real agency in people and systems. True agility comes from empowering individuals and teams to make decisions and adapt, supported by evidence-based management to measure outcomes and guide change. To succeed, shift your transformation efforts from compliance to fostering agency and use data to drive continuous improvement. https://engineering-leadership.hinshelwood.com/signals/you-want-speed-adaptability-resilience/ Sun, 11 May 2025 15:30:29 +0100 https://engineering-leadership.hinshelwood.com/signals/you-want-speed-adaptability-resilience/ Investing in Agile, Scrum, Kanban, and DevOps will not deliver real speed, adaptability, or resilience unless your teams have the agency to truly own their work and outcomes. Without empowering people to take responsibility, you risk superficial processes and disengaged teams. To achieve genuine agility, ensure your system supports team and individual ownership, not just frameworks. https://engineering-leadership.hinshelwood.com/engineering-notes/how-i-used-generative-ai-to-transform-site-tagging-and-categories/ Thu, 15 May 2025 09:00:00 +0000 https://engineering-leadership.hinshelwood.com/engineering-notes/how-i-used-generative-ai-to-transform-site-tagging-and-categories/ Migrating a large, legacy blog to Hugo enabled the use of generative AI for automated tagging and categorisation, significantly improving content discoverability and editorial consistency while reducing manual effort. The system combines AI-driven suggestions with human oversight, using multi-factor scoring, penalty logic, and transparent reasoning to ensure quality and accountability. Development managers considering similar automation should maintain human control over final decisions and leverage AI to streamline, not replace, editorial processes. https://engineering-leadership.hinshelwood.com/articles/human-and-ai-agency-in-adaptive-systems-strategy-before-optimisation/ Mon, 30 Jun 2025 09:00:00 +0000 https://engineering-leadership.hinshelwood.com/articles/human-and-ai-agency-in-adaptive-systems-strategy-before-optimisation/ Human decision-making is essential for setting strategy, purpose, and adapting to change, while AI should be used for tactical optimisation within clear human-defined boundaries. Over-relying on AI for adaptation leads to fragile systems, loss of accountability, and strategic obsolescence. Development managers should ensure humans remain responsible for strategic direction and adaptation, using AI only to optimise within those parameters. https://engineering-leadership.hinshelwood.com/tags/agentic-engineering/ Tue, 22 Jul 2025 15:58:00 +0000 https://engineering-leadership.hinshelwood.com/tags/agentic-engineering/ Agentic Engineering is the deliberate design and practice of software development that maximises the agency of both humans and intelligent systems. It integrates engineering excellence, DevOps ethos, and ethical autonomy to create environments where decisions are decentralised, feedback is fast, and value delivery is continuous. It’s characterised by Developer Agency, Systemic Observability, DevOps-Infused Craft, Ethical AI Integration, and Feedback-Driven Adaptation. Agentic Engineering is not a job title, role, or method, it’s a philosophy of engineering in which the ability to act with clarity, intent, and impact is engineered into the way we build, learn, and evolve. https://engineering-leadership.hinshelwood.com/tags/agentic-agility/ Mon, 07 Apr 2025 12:39:49 +0000 https://engineering-leadership.hinshelwood.com/tags/agentic-agility/ Agentic Agility is the capacity, human or AI, to take intentional, adaptive action within socio-technical environments to improve outcomes and align with evolving goals. It is grounded in agency: the power to act with autonomy, accountability, and purpose. Without agency, Agile devolves into hollow rituals; with it, people and systems can deliberately shape value delivery. Agentic Agility manifests through human judgement and learning or AI-driven optimisation within constraints, enabling continuous evolution of both what is delivered and how it is delivered. It is the critical lever that sustains agility as a living, resilient capability rather than a hollow label. https://engineering-leadership.hinshelwood.com/tags/collective-intelligence/ Thu, 23 Jan 2025 10:17:24 +0000 https://engineering-leadership.hinshelwood.com/tags/collective-intelligence/ Collective Intelligence represents the enhanced problem-solving and innovation capabilities that emerge when humans with agency effectively collaborate with AI agents as team members. This concept goes beyond traditional human collaboration to encompass human-AI partnerships where both parties contribute complementary strengths, human creativity, judgment, and contextual understanding combined with AI processing power, pattern recognition, and consistent execution. Unlike passive tool usage, Collective Intelligence requires humans to have genuine agency and AI systems to operate with designed autonomy within appropriate constraints. The resulting synergy enables teams to navigate complex socio-technical environments, make more informed decisions, and deliver superior outcomes that neither humans nor AI could achieve independently. This form of agentic agility is essential for modern product development, where the volume and complexity of information, rapid change cycles, and need for continuous adaptation exceed purely human cognitive capabilities. By cultivating Collective Intelligence, organisations can harness the full potential of human-AI collaboration, transforming how value is created and delivered in digital product development. https://engineering-leadership.hinshelwood.com/tags/agentic-software-delivery/ Tue, 21 Jan 2025 10:00:00 +0000 https://engineering-leadership.hinshelwood.com/tags/agentic-software-delivery/ Agentic Software Delivery is a strategy for continuously achieving business outcomes through the deliberate integration of autonomous AI agents, human expertise, and organisational context. It is not about automation for automation’s sake, but about enabling teams to move faster and smarter by embedding proactive, context-aware intelligence into their systems of work. The term ‘agentic’ implies more than assistance, it implies agency. These agents operate autonomously within defined boundaries, learning from data, adapting to patterns, and making context-informed decisions. They contribute meaningfully to outcomes across discovery, development, delivery, and operations. This approach relies on the synergy between domain experts and AI agents, requiring lean, empirical systems of work, strong product strategy, and modern engineering practices such as CI/CD, observability, infrastructure as code, and automated testing.