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duncan.bandojo

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About Duncan Bandojo

Duncan F. Bandojo is a undergraduate of Computer Science at Polytechnic University of the Philippines, with an interest in backeend development and geospatial data analysis, and is currently diving into frontend development. He is passionate about building applications that leverage visual data (geospatial) to provide visual insights that genuinely helps people.

Agent Skills: On-the-fly capabilities for your AI Agents

2026-01-17T18:06:31+00:00

Agent Skills are the new boom. If you’ve been following the agentic AI space since late 2025, you’ve likely noticed a shift. Previously, we spent most of 2024 and 2025 obsessing over tools—giving LLMs calculators, database access, and API keys. But giving a new employee a laptop and a login doesn’t make them productive. You still have to train them. For example, you have to show them how your organization works. That is exactly what Claude Agent Skills are. Released by Anthropic in October 2025, Agent Skills have quietly become one of the most powerful features in the Claude ecosystem, [...]

Agent Skills: On-the-fly capabilities for your AI Agents2026-01-17T18:06:31+00:00

The Year of the Agent: Anthropic’s Claude AI Models and Agents

2025-12-26T17:20:34+00:00

  Looking back on the past year of 2025 coding with the help of artificial intelligence, we can safely say that it was the year of agents, especially pioneered by Anthropic with Claude Code. AI products have matured to offer highly reliable agents that can understand, navigate, and work seamlessly on large codebases. It is the end of the old ways: of manually copying and pasting code into web AI applications. Agents are now actually part of the codebase, navigating around like a real developer. And they can now be left with long-running tasks on their own,opening and working on [...]

The Year of the Agent: Anthropic’s Claude AI Models and Agents2025-12-26T17:20:34+00:00

Neural Networks and Images with Convolution

2025-11-29T08:07:33+00:00

In the age of artificial intelligence, it is common to meet the term neural network, seeing diagrams of neurons connecting to other neurons, programmers training models, and so on. Here, we will discuss how neural networks are similar to plain mathematical functions (models), how they build upon traditional linear regression, and their application to visualize images with convolutional neural networks. The usual pedagogy for learning neural networks begins with the iconic diagram: columns of circles ("neurons") connecting to other circles across multiple layers, passing information from input to output. But what is this diagram trying to capture? And what really [...]

Neural Networks and Images with Convolution2025-11-29T08:07:33+00:00

Crowd Detection: How AI Predicts Busy Areas

2025-10-26T15:10:10+00:00

You might use Google Maps in your daily commute, but have you ever wondered how it provides real-time traffic data? Or how it highlights the busiest areas and even the popular times for a business? To achieve this, Google powers these features with large-scale analysis and crowdsourcing from our smartphone location data. Subsequently, an artificial intelligence (AI) application is used to also predict crowd levels in the coming hours and days, instead of being limited to real-time situations. Google Maps' features for live busyness, popular times, and traffic are a suite of AI-powered systems. Specifically, they are built on crowdsourcing [...]

Crowd Detection: How AI Predicts Busy Areas2025-10-26T15:10:10+00:00

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