Elisha Terada
AI Agent Development, AI Strategy, AI/Machine Learning, AI/ML, Digital Transformation, Generative AI
Why Most Enterprise AI Initiatives Stall Before They Start
Most organizations are trying to build the AI interface first while the operational and data layers underneath it still aren’t ready. The chat interface is often the easiest part of enterprise AI. Making the organization understandable to machines is the hard part. The AI demos looked straightforward. Connect the data. Add a copilot. Ask questions.
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AI Agent Development, AI Strategy, AI/Machine Learning, AI/ML, Generative AI, Software, Technology Architecture, Web App Development
Why Spec-Driven Development Breaks Down in Real Projects
Spec Driven Development is gaining momentum in the AI era as tools like Cursor, Claude Code, and Codex turn specifications into executable inputs for software generation. But while detailed specs can accelerate development, many real-world projects operate in unstable environments where requirements shift constantly. This article explores why Spec Driven Development works well in mature product teams, where it breaks down in fast-moving project environments, and how AI is changing the economics of prototyping, iteration, and requirements discovery.
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AI Strategy, AI/ML, Generative AI, Software, Systems Design, Technology Architecture, Web App Development, Website Development
Turning Your Codebase Into Stakeholder-Ready Documentation with AI
Treat your codebase, PRs, commit history, and AI conversations as a structured work diary so AI can synthesize accurate, stakeholder-ready documentation on demand. AI can parse repositories and reasoning trails to produce drafts (security controls, data flows, architecture) and, critically, surface gaps that indicate product or clarity issues. Implement this by structuring the codebase, generating periodic AI-driven reports, and using discrepancies as a forcing function for improvements. The result is reduced reactive overhead, preserved institutional memory, and tighter alignment between engineering work and stakeholder visibility.
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AI Agent Development, AI Strategy, AI/ML, Generative AI, Software, Web App Development, Website Development
Using Cursor as Your AI-Assisted IDE
This guide shares practical best practices for using Cursor as a productivity amplifier—not an autopilot—by planning before prompting, breaking work into small, specific tasks, and always providing rich context. It stresses disciplined engineering: test and review AI changes like PRs, commit frequently, and keep a clean, well-structured codebase. Teams should leverage Notepads, Rules, and shared workflows to align output and reduce risk, while exercising extra caution for production-critical systems. Used intentionally, Cursor accelerates learning, debugging, and refactoring without compromising quality.
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AI Agent Development, AI Strategy, AI/ML, Customer Experience, Software, UX/UI Design, Web App Development, Website Development
Agents Are Getting More Expressive. That Changes Customer Support.
Expressive voice AI marks a shift from purely logical accuracy to emotionally calibrated interactions where tone, pacing, and delivery shape outcomes. This evolution moves agents from merely answering questions to handling situations, improving de-escalation, CSAT, and operational metrics. While imperfect today, recognizing that tone is part of the product signals an ecosystem-wide change that will redefine how service systems are built and measured.
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AI Strategy, AI/ML, Generative AI, Website Development
From SEO to GEO: What Changed in the Age of Generative Search
Search used to mean ranking on Google. Now it often means being summarized by AI. This shift from Search Engine Optimization (SEO) to Generative Engine Optimization (GEO) isn’t cosmetic. It changes how discovery works, how authority is built, and how value is captured. Below is a structured breakdown with supporting research. Executive Summary 1. The
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