AI enablement

The Handoff Problem: Why Most AI Rollouts Fail Before the Model Does

Most AI adoption failures do not stem from weak models, but from broken workflows at the human-AI handoff. This article explores how unclear briefs, missing governance, and unprepared teams cause high-potential AI systems to fail—and how redesigning workflows, prompts, and operating models can turn AI into a reliable operational partner.

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Designing an AI-Assisted Content System That Scales With the Practice

A case study on building an AI-assisted content system for a professional services firm to scale thought leadership without overloading partners. By introducing structured templates, AI-assisted drafting, and streamlined review workflows, the system enabled faster publishing cycles, consistent quality, and a repeatable content engine aligned with high-trust expertise.

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Diagram showing a central automation tool connecting developers, product, ops and systems like Git, CI, logs, tickets, data and messaging.

Claude Code Is Not Winning Developers With Better Chat. It Is Rewriting the Interface Between Code, Tools and Control.

Claude Code is not trying to win on prettier autocomplete. It is quietly turning the dev environment into a network of supervised agents, opinionated tools and tight permissions – a move that matters far more to real teams than another benchmark chart.

Claude Code Is Not Winning Developers With Better Chat. It Is Rewriting the Interface Between Code, Tools and Control. Read More »