Author: Rodrigo Gardin
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Spec-Driven Development: The Engineering Practice That Lets Teams Compress 18-Month Projects into Weeks
An AWS team completed an 18-month rearchitecture project in 76 days. Six engineers, where 30 had originally been scoped. The tool: Kiro IDE, built around a methodology called spec-driven development. That number isn’t a fluke — it’s showing up across EY, Amazon’s product lines, and the Kiro team itself. The question worth asking is why,…
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The Great Enterprise AI Chasm: Why 79% of Organizations Struggle to Move Beyond Pilots
Enterprise AI investment has never been higher. Yet according to Writer’s 2026 Enterprise AI Adoption Survey of 2,400 executives and employees across the US, UK, and Europe, 79% of executives acknowledge struggling with AI adoption — despite 59% of their companies spending over $1 million annually on AI. The gap between AI experimentation and production…
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Agentic AI in the Enterprise: Why 40% of Projects Will Fail by 2027—and What Separates Teams That Get It Right
In June 2025, Gartner polled more than 3,400 organizations and issued a stark prediction: over 40% of agentic AI projects will be canceled before the end of 2027. Not paused—canceled. The cause isn’t technology failure. It’s costs that spiral without a clear business case, governance structures built too late, and organizational behavior that was never…
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Agent-to-Agent (A2A) Protocol: How AI Systems Are Learning to Work Together in 2026
The Model Context Protocol solved half the problem: it gave AI agents a standard way to connect to tools. But what happens when agents need to talk to each other — across different frameworks, vendors, and organizational boundaries? That is the gap the Agent-to-Agent (A2A) Protocol was built to close, and one year in, it’s…
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Agent-to-Agent (A2A) Protocol: How AI Systems Are Learning to Work Together in 2026
The Model Context Protocol solved half the problem: it gave AI agents a standard way to connect to tools. But what happens when agents need to talk to each other — across different frameworks, vendors, and organizational boundaries? That is the gap the Agent-to-Agent (A2A) Protocol was built to close, and one year in, it’s…
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Explainable AI: Making Black-Box Models Transparent
On August 2, 2026, the EU AI Act’s high-risk provisions take full effect — and the clock is running. For any engineering team deploying AI in financial services, healthcare, or hiring, this isn’t a compliance checkbox. It’s a legal mandate requiring that your models be auditable, interpretable, and explainable on demand. The penalty for non-compliance:…
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Building Scalable MLOps Pipelines with MLflow and Kubeflow
The MLOps market hit $3.18 billion in 2025 and is growing at a 42% CAGR — yet Gartner estimates that nearly 70% of ML projects still never reach production. Teams are investing in machine learning at record pace, but most are discovering the hard truth: building a model is not the hard part. Keeping it…