Jason Haensly
Software Engineering Program Lead

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[Watch] Making Best Practices the Default with GitLab

 


We pride ourselves on our adaptability to each client’s unique needs and constraints — and no two projects are the same. This is typically most evident in a project’s infrastructure, the tools, and utilities a team uses during development to track work items, streamline communication, and estimate schedules. Customizing infrastructure takes time and effort, and when timelines are tight or the engagement short, it can be hard to justify that investment. Shouldn’t we be focusing on the critical path?

Recognizing this, and in the spirit of continual self improvement, we have been investing in tools and “templates” that reduce that up-front cost so that every project can be our best, most efficient effort, no matter the constraints. GitLab has emerged as a keystone technology for us thanks to a licensing and security model that allows us to invite clients in to collaborate with us directly, and an extensible design that has enabled us to use Git in applications that it wasn’t ever intended to support.

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June 15, 2020

[Download] Do Better. Sustainable Product Design Ebook

As a product development consulting company, we are in a unique position to drive sustainable design across industries—and we don’t intend to stop there. Instead, we are sharing our work to help others design more sustainable products and systems. This ebook abstracts our sustainable design process into easy-to-use tools, which can be applied to any hardware product development.

June 29, 2020

Sidewalk Detection on the Edge and Shared Micromobility: A Solution Analysis

As the only form of public transit that is readily capable of supporting social distancing, shared bikes and scooters will be an essential component of an effective urban economic recovery strategy in the coming months. Prior to COVID-19, the city of San Francisco announced that future shared scooter platforms will be required to have deterrents to riding on sidewalks. Naturally, being both SF residents who will be affected by this decision, and curious engineers with micromobility industry experience, we decided to leverage our expertise in machine learning to explore the specifics involved in implementing a system which can determine if a scooter is riding on a street or a sidewalk.

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