I’m planning to return to pure coding for now, stepping away from AI-driven assistants like Cursor, Windsurf, and their peers. These tools often spit out convoluted solutions for trivial features, turning ten-minute jobs into hours of debugging. When you ask the AI to fix its own mistakes, hallucinations multiply, and you end up deeper in the weeds. Today’s AI coding assistants are temperamental and far from reliable. Before leaning on an AI, you must first understand the problem you’re solving and how you would solve it manually. Mainstream paid LLMs can generate solid code, if you steer them correctly, but they don’t innately grasp your unique vision. They excel at one-off, well-trod tasks (like scaffolding a basic to-do list) because countless examples exist in their training data. Custom ideas? They’ll guess at best and miss the mark at worst. Instead of chasing one-shot demos, invest a few days in structured planning: First, write a problem-statement document (Markdown or plain te...
Procurement professionals today operate within increasingly complex environments where decisions must be made promptly, often with limited information and significant financial implications. In such settings, heuristic methods, simple experience-based rules for judgement, play a vital role in enabling timely and pragmatic decision-making. Although these cognitive shortcuts offer operational advantages, they can also lead to inconsistent outcomes if applied without analytical validation. This article explores key heuristics applicable to procurement and sourcing activities. It draws from foundational behavioural research, journal literature and recent technological developments, including artificial intelligence, to provide a measured overview of how heuristics influence professional judgement and how their limitations may be addressed through structured approaches and intelligent systems. Common Heuristics in Procurement Practice Heuristics simplify decision-making by reducing complexi...