Most AI tooling today focuses on one problem: How do we give the model better context? That's an...
TokenCap v1.1.0 releases Execution Contract, shifting AI agent focus from repository context to disciplined execution—scope tracking, verification rules, confidence ratings. For tech managers, it solves AI adoption blockers: preventing scope drift, skipped verification, and silent failures that compromise production reliability.
Most AI tooling today focuses on one problem:
How do we give the model better context?
That's an important problem, and it's exactly what TokenCap has been solving through repository intelligence.
But after spending months using AI coding agents every day, I realized something.
Context isn't where most failures happen anymore.
One of the biggest challenges in AI-assisted development isn't choosing the right model. It's...
One thing I've realized while building with AI is that context isn't a prompt problem anymore. It's...
Every AI coding assistant promises the same thing: "Write code faster." Yet after months of using...
One of the strangest workflows in modern software development looks like this: Ask ChatGPT a...
Recent AI engineering signals point to a practical lesson: huge context windows help, but reliable AI apps still need context…
Two days ago, I released TokenCap v1.4.0 with support for Local MCP (Model Context Protocol). The...
