Introduction

As I discussed in my article on my reporting automation workflow, I don't get a lot of IT resources to lean on, so I've relied a lot on local code execution to accomplish process automation.

My best (worst) example is the process for the associate call-off voicemail. We have a voicemail that associates are required to call when they miss, or will miss, any part of a scheduled shift. Call the number, leave a voicemail with your information: chat notifications go out and the voicemail gets logged. My automation flow for this depends on no fewer than four independent points of failure and brittle steps that need to be babysat.

This year I decided to re-implement the whole thing on a cloud communications platform to improve error handling, operate consistently with no or minimal manual intervention, and be easily handed off to another person or team. I ended up going with Twilio due to their in-platform serverless function support (Twilio Functions). This post covers my learning process in assembling the new flow and walks through the final result.

Note: This is firmly in the Learning In Public category, so don't depend on any of the following to represent correctness or best practices. Feedback welcome, though.

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Introduction

Light is underappreciated as a way to improve the quality of an indoor environment. The technology has only gotten to the point relatively recently where the energy cost and technology make it feasible to implement adaptive lighting setups with the output to sufficiently light an interior space.

I'm in front of the computer a lot and spend too much time indoors, so indoor light quality has a disproportionate impact on my mood. Good incentive to understand how it impacts mood, energy levels, and sleep quality.

Based on my experience, the areas of opportunity are in matching color temperature to time of day, improving the Color Rendering Index, increasing lumen output during the day, and automation.

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Introduction

A recent technology change at work resulted in switching our contact center agents from phones to WebRTC. This was a good opportunity to upgrade headsets, as many of the analog headsets they're using are difficult to adapt consistently reliably and motherboards on mid-range business machines often have fairly terrible analog audio inputs. I tested a range of USB headsets for suitability for use by work-at-home contact center agents during an 8-hour shift.

Note: When I initially wrote up this article, it was at the beginning of March before the COVID-19 situation had really hit. Availability of anything related to remote work is extremely limited at this time, so the prices outlined below are no longer inline with reality. Availability has improved a bit compared to in March and April.

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Introduction

The Model F keyboard by Model F Labs is a new reproduction of some models of IBM's classic Model F range that aims to be as good as or better than the originals.

I have a bit of a fixation on buckling spring keyboards, having several modern Unicomp models, and the Model F is the best of the buckling spring boards. When the project first came to my attention in 2016, I was extremely excited and I pre-ordered a keyboard in 2017.

I am reviewing an F77 (ID # 739) that I received in June 2020. My impression after a couple weeks of use is extremely positive. The keyboard is both a high-quality reproduction and an excellent keyboard in general.

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