Your AI Pilot Didn't Fail. It Was Never Built to Ship.
88% of enterprise AI pilots never reach production. The reason is almost never the model — it is the data, integration, ownership and measurement nobody scoped.
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Notes on shipping AI agents, ML and full-stack engineering
Practical write-ups from the Geeks Invention team — production lessons from AI agent fleets, machine learning, IoT and software delivery.
The EU AI Act Deadline That Wasn't Delayed
The Digital Omnibus deferred the high-risk obligations to 2027. It did not touch Article 50 transparency, which applied from 2 August 2026 to almost everyone.
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What Breaks When You Put AI Agents in Production
86% of teams run coding agents against production code; only 8.6% have other agents live. The gap is verification, permissions, memory and observability.
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The 20× Inference Bill Nobody Is Watching
Routing routine steps to a small model instead of a frontier one can cut inference spend by 20× or more. How to find out what it would save you.
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MCP for Teams Who Don't Build AI Products
28% of the Fortune 500 have deployed Model Context Protocol. What it takes to expose an internal system to an AI assistant without regretting it later.
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Context Engineering, Minus the Hype
Roughly 80% of AI output quality comes from what is in the context window, not how the prompt is worded. What that changes about the way you build.
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500 Hours of Engineering, Done in 10
We handed a product team's entire bug lifecycle to a fleet of AI agents: 150 issues imported straight out of a messy spreadsheet, and 50 of them fixed, reviewed and sitting in merge-ready pull requests ten hours later.
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AI and Creativity: Unlocking the Potential of AI in Artistic Innovation
Generative tools made iteration cheap and moved the scarce skill to judgement. What that changed about creative work, and the rights and disclosure questions still open.
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Machine Learning's Influence on E-commerce Trends
Search and fraud detection reliably pay in e-commerce. Personalisation often doesn't, and the difference is usually trustworthy event data rather than model sophistication.
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The Future of AI and ML in Custom Software: What to Expect
Some development work collapsed, some barely moved, and a new engineering discipline appeared. Two years of evidence on what AI actually absorbed.
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The Future of AI in Healthcare: Custom Software Solutions
Ambient documentation and imaging triage reached the bedside; sepsis prediction largely did not. What separated them was integration and safety design, not model quality.
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The Intersection of IoT and Custom Software
Connected-device projects rarely fail on hardware. They fail on device management, OTA updates and data pipelines — the four systems every fleet needs before it scales.
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Predictive Analytics & Data Science: Growth Catalyst for Businesses
A prediction is only worth the decision it changes. The three questions that kill most predictive projects before modelling starts, and where the discipline reliably pays.
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