Enterprise Software
6 posts on this topic — practical guidance from Shawn Livermore on fractional CTO, AI, and technology leadership.
Your Vibe Coding Starter Template Is an Architecture Decision
When you pick a starter template for a vibe coding project, you are making the first architectural commitment of the entire codebase. Everything the AI generates afterward works within those assumptions.
Read post →The Strategic Shifts in Enterprise Software Creation That AI Is Actually Forcing
AI tools produce more code, faster. The harder question is what that means for architecture governance, build-vs-buy decisions, and team structure — the decisions that were already difficult.
Read post →The Enterprise Software Specification Is Broken. AI Is Making That Visible.
AI coding tools fill specification gaps with defaults from their training data. In enterprise software, those defaults are rarely correct. The specification problem that always existed is now impossible to ignore.
Read post →Build vs. Buy Software in the AI Era: When the Economics Shift
AI has moved the cost curve for custom software development. That changes which software is worth building. Here is how to re-evaluate the build vs. buy decision when your development cost assumptions no longer hold.
Read post →What Anthropic's Parallel Subagents Mean for Enterprise Modernization Programs
Claude Opus 4.8's Dynamic Workflows can run hundreds of parallel subagents across a codebase. The bottleneck in enterprise modernization has never been coding speed — it's architecture and sequencing. Understanding the difference changes how you use the capability.
Read post →Before Your Team Vibe Codes, Define the Code Footprint
AI coding tools generate code faster than teams can review it. Quality is set before the first prompt, by your starter template, context file, and defined target.
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