https://gaberger.github.io/tags/mcp/Recent content in Mcp on A Field CTO PerspectiveHugoen-usTue, 13 Oct 2026 00:00:00 +0000https://gaberger.github.io/2026/10/inside-the-ai-harness/Tue, 13 Oct 2026 00:00:00 +0000https://gaberger.github.io/2026/10/inside-the-ai-harness/<p><em>Written by a practitioner who has spent three years building AI apps, harnesses and code development tools. See</em> About the author <em>at the end.</em></p> <h2 id="why-the-harness-matters">Why the harness matters</h2> <p>In 2026, what an AI agent can actually do depends less on the model and more on the software wrapped around it. That wrapper is the harness.</p> <p>A language model on its own is a function: text in, text out. It cannot read a file, run a test, remember yesterday, or check its own work. Everything that lets it do those things lives outside the weights.</p>https://gaberger.github.io/2026/07/delivering-apis-for-ai/Thu, 09 Jul 2026 00:00:00 +0000https://gaberger.github.io/2026/07/delivering-apis-for-ai/<p>The rise of AI agents and autonomous systems is fundamentally changing how we design and deliver APIs, shifting from human-centric interfaces to AI-native integration patterns that require new architectural thinking.</p> <h3 id="the-inflection-point">The Inflection Point</h3> <p>Technology innovation has repeatedly transformed how we build systems. From the fourth-generation programming languages (4GL) of the 1990s that abstracted database operations to today&rsquo;s AI-powered code generation, each wave has forced us to rethink fundamental assumptions. We now stand at another such inflection point: the transition from human-interface (HI) APIs to agent-interface (AI) APIs.</p>