标签：#Feedback

Introduction Tennis players often find themselves in a feedback vacuum. Without a coach physically present, pinpointing what’s wrong with a stroke becomes a guessing game. This gap in immediate, stroke-specific guidance is a silent killer of progress, leaving players to rely on sporadic coaching sessions or self-diagnosis, which often misses the mark. The problem isn’t just about lack of access to coaches—it’s about the inability to see and correct subtle technique flaws in real time. Enter Rallylens , a web app born out of personal frustration. As a student and tennis player, I built this tool to address the disconnect between practice and feedback. It uses video analysis powered by AI to break down uploaded tennis videos frame by frame, identify stroke types (forehand, backhand, serve), and compare them against ideal technique benchmarks. The system doesn’t just flag errors—it explains them. For instance, if a backhand stroke shows an inconsistent racket angle, the feedback highlights this deviation and suggests adjustments, focusing on mechanics like wrist rotation or body alignment. The Mechanism Behind the Feedback Rallylens operates through a multi-step process that mimics a coach’s eye but with the precision of machine learning: Video Segmentation: Uploaded videos are split into frames, allowing the AI to analyze micro-movements that might be invisible to the naked eye. Stroke Classification: Using computer vision techniques , the model identifies the stroke type with an accuracy rate currently at 85%, though unusual playing styles can still cause misclassification. Pattern Analysis: The algorithm compares detected patterns against biomechanical benchmarks , flagging deviations like improper weight transfer or late racket contact. Feedback Generation: Instead of generic advice, the system generates actionable insights , such as “Adjust your shoulder tilt by 10 degrees to optimize power transfer.” Edge Cases and Limitations While Rallylens bridges a critical g

August 3, 2026Lockhead Taking feedback - so essential for AWS every other tech company or startups #culture #aws #devops #aws #building #oss #build-in-public Taking feedback - so essential for AWS every other tech company or startups There’s a reason for this post: Last week I gave feedback to a good friend. It was something around “this thing doesn’t work for me, can you fix this?” Within hours, Ran had taken my feedback and incorporated it into his website. This little story motivated me to write this blog as in our industry we start to forget the importance of human interactions and the power of feedback. Feedback: A gift and a curse Feedback is a gift. Every content creator and startup developer will agree: Any piece of feedback you can get helps to shape your future as a creator or builder. It’s a gift that too many of us have stopped giving in 2026 - either because we’re busy building our own SaaS or because we’re too distracted by AI in our day to day job. The gift of feedback has made AWS one of the biggest cloud vendors and has helped Google Cloud to quickly win shares of the cloud market: by making things simpler that AWS made too complicated in the past years. The gift of feedback can be a rant or a viral post where you expressed your problems or concerns that you faced when you were building something. Feedback is a gift if it is clear enough to help you change something. Feedback can be a curse if it is given in the wrong format or tone. It can be a curse if it becomes or is taken personal and when it negatively impacts the work. Feedback is a curse when it is given with wrong intentions. It is a curse when it is being ignored. Feedback makes a difference This week, a bunch of AWS Heroes meet and the whole week is about exactly this: giving feedback . It’s a week where we get to talk and discuss in person with the teams we work with (mainly behind the scenes) through the whole year. We share - and openly fight with each other - on current and future AWS

How we decide is at the core of architecture, and the architecture advice process is a way to decentralize architectural decisions. It needs to be supported by Architecture Decision Records because of the speed at which technology and systems move, and can be complemented by a weekly architecture advice forum. By Ben Linders