TL;DR You can integrate Azure DevOps with GitHub to get the best of both worlds in Power Platform development. ADO stays as the backbone: work items, sprint planning, test plans, and deploy pipelines all remain on Azure DevOps. Code moves to GitHub: Power App Code Apps or Power Pages SPA live in GitHub repos, unlocking native GitHub Copilot integration and the Copilot Cloud Agent. The two platfo
GitHub Copilot just got a lot more complicated — and not in a good way. If you tried to sign up for Copilot Pro recently and hit a wall, that's not a bug. GitHub quietly paused new sign-ups for Copilot Pro, Pro+, and Student plans starting in late April 2026. No end date announced. No workaround offered. Just a message and a door that won't open. That alone would be worth covering. But they made t
Microsoft's 'Co-Authored-by Copilot' Tag: Unpacking the Strategic Play for AI Dominance in VS Code The persistent insertion of 'Co-Authored-by: Copilot' into commit messages within VS Code—often irrespective of GitHub Copilot's active contribution to specific changes—is far from a benign engineering detail. It represents a calculated, multi-faceted strategic maneuver by Microsoft, signaling a pr
What if your code editor could do keyword research, audit your SEO, and optimize your content for AI search engines — without leaving VS Code? I built a set of open-source agent skills that turn GitHub Copilot into a hands-on marketing strategist. Here's what I learned, how they work, and how you can use (or build) your own. The problem Open Ahrefs/Semrush → research keywords What if I could encod
選定理由 Paper: https://arxiv.org/abs/2512.01020 【社会課題】 【データの設計と従来技術の限界】 Issue Tree（法的論点ツリー）に変換し、葉ノードに対しルーブリック基準を適用可能にした。原告・被告・裁判所の主張をツリー構造で整理した約24,000インスタンスのデータセットを構築。評価軸は「論点カバレッジ」と「正確さ」の2次元。以下がサンプルである： 【原告の主張】被告は540万円を支払え └─【原告】保険金の支払い義務がある ├─【原告】死亡は突発的・偶発的な事故だった │ └─【原告】餅を食べて窒息死＝外因による傷害 │ └─【被告】死因は既往症の可能性が高い └─【裁判所の結論】突発的事故と認定 ただし窒息死は証明不十分 この
The grey enemy and the friend to save me from it If you're a software developer and you are on GitHub, you already know what I'm talking about: the contribution graph. That public heatmap on your profile that tracks your every commit, PR, and review you've ever made. That grid of gray and green squares that (in some cases looks like a well maintained patch of grass) tells a story about your codi
Introduction To understand knowledge graphs, you first need to grasp three core concepts: entities, relations, and triples. Imagine a knowledge graph as a network that models the real world using nodes and connections. In this network, an entity is any distinct thing or object such as a person, city, or company. For example, “Sreeni”, “Plano”, and “Caterpillar” are all entities. A relation descr
This is my Day 2 of learning AI fundamentals where I will be covering the following concepts: Vector Embeddings How Tokenisation and Vector Embeddings relate to each other Vector embeddings is the process of turning each token id(generated during tokenisation) into high dimensional vector where semantic similarity results into geometric closeness. Think of it like this: dog is closer to puppy, al