The article explores the dangers of relying on AI-generated outputs in software development, highlighting how AI can create a false sense of certainty. It emphasizes the importance of distinguishing between proof, evidence, and belief, urging developers to critically assess AI’s role in decision-making.

This article argues that human involvement often detracts from AI performance, especially in analytical tasks. While creative fields still benefit from human-AI collaboration, the author suggests that as AI improves, humans should limit their interference and focus on strategic decision-making instead.

This article argues that vertical software has already developed valuable context graphs that capture business logic and decision-making processes, unlike generic horizontal software. It highlights how these context graphs help agents move toward autonomy by providing essential reasoning and insights. The piece also discusses the potential for vertical platforms to absorb more functions and deepen their context graphs using AI.

The article reflects on the rapid changes in software development and strategy brought on by AI in 2025. It argues that as barriers to building collapse, the focus shifts from mere capability to judgment in design and execution. The author anticipates that 2026 will emphasize clarity and better decision-making over speed and volume.

This guide helps teams refine their prototyping strategies by focusing on decision-making speed and alignment. It includes tools for evaluating requirements, an overview of the AI prototyping landscape, and introduces Miro Prototypes for rapid iteration.

The article explores different meanings behind the phrase "I don’t know," using various personas to illustrate how people express uncertainty. It also discusses potential future trends in data and AI, emphasizing that innovations often arise from unexpected circumstances rather than careful planning.

This article explains how AI tools streamline the exploration phase in creative work, making it faster and cheaper to generate ideas. However, the responsibility for making informed decisions still lies with the human user, who must critically evaluate AI-generated options.

The article explores how AI tools are evolving beyond simple tasks to become better at problem-solving and decision-making than humans. It questions our reliance on AI and the implications of letting it guide our choices, suggesting that we may be ceding more control than we realize.

The article discusses the value of straightforward methods, like using text boxes, to capture organizational decision-making processes. It contrasts complex modeling efforts with the practicality of simply recording conversations and decisions, suggesting that a focus on clear documentation can lead to better outcomes in AI-driven environments.

This article discusses the difference between assistive and authoritative AI in organizations. While assistive AI helps with tasks, it doesn't change outcomes significantly. Allowing AI to take authoritative roles can reshape workflows and drive meaningful results.

Research is a crucial leadership skill that cannot be replaced by AI, as alignment and shared understanding among stakeholders are essential for effective decision-making. The article emphasizes that the process of transforming facts into knowledge requires collaboration and emotional connection, which AI cannot facilitate. Ultimately, relying on AI for problem framing can hinder genuine insight and ownership among team members.

Anthropic has introduced Claude, a series of AI models designed specifically for U.S. national security customers. These models aim to enhance decision-making and operational efficiency in government sectors, showcasing advancements in AI technology tailored for critical applications.

The article discusses the evolution of AI systems, particularly focusing on "systems of action" that integrate decision-making and autonomous operations. It explores how these advanced AI capabilities can enhance efficiency and effectiveness across various sectors by enabling proactive responses to complex situations. The roadmap for developing these systems highlights the importance of combining human expertise with machine intelligence.

The article introduces CEO GPT, an AI tool designed to assist business leaders with decision-making, strategy development, and operational efficiency. It highlights the potential benefits of using AI to enhance productivity and streamline processes within organizations. The tool aims to empower CEOs by providing data-driven insights and recommendations.

The article discusses the challenges and pitfalls of overthinking AI subscription services, emphasizing the importance of clarity and simplicity in decision-making. It encourages users to focus on their specific needs rather than getting bogged down by endless comparisons and options. The author suggests practical strategies to streamline the subscription process and make more informed choices.

Many people misunderstand AI, focusing on its flashy outputs like art and writing rather than its potential to enhance decision-making through effective information management. Businesses can leverage AI to optimize information flows, enabling better decisions and tackling unstructured data, thereby creating real value beyond superficial applications.

The article discusses the challenges posed by agentic artificial intelligences (AIs) in the context of the OODA loop—Observe, Orient, Decide, Act—framework. It highlights the complexities of integrating AI decision-making into human processes and the implications for security and governance. The author emphasizes the need for a deeper understanding of these interactions to ensure effective management of AI systems.

The Vaughn Tan Rule emphasizes that individuals should not outsource their subjective value judgments to AI unless there is a clear and justifiable reason to do so. This principle is grounded in the philosophical argument that AI currently lacks the ability to make meaning or subjective value assessments, highlighting the importance of human decision-making in contexts where personal values are at stake. Practical examples illustrate how sophisticated users of AI can navigate this rule effectively in their daily applications.