If you have a team of software engineers and want to move them to Mac, you will need to consider a number of things before you do so.
Here’s what’s new in our January 2023 Release Notes:
* Tables Columns Sorting Improved
* Reconcile Commits Count Between KPI Card and the Table
* Efficiency Tab Improvements and Efficiency KPI Cards Align
Imagine all the people, Livin’ life in peace
You may say I’m a dreamer, But I’m not the only one
I hope someday you’ll join us, And the world will be as one
Imagine, John Lennon
depicting a futuristic 2021, features an 80 Gb drive inside Keanu Reeves’ head. Using a doubler he was able to make it 160 Gb… just enough to hold 320 Gb!
What is an an AI Digital Assistant? You can call ‘em by a number of different names – virtual assistants, intelligent assistants, smart chatbots, or the increasingly ubiquitous smart home assistants like Siri and Alexa. Technically speaking, they are software agents able to answer questions and do “stuff” for you based on your commands.
It’s helpful to not overthink what AI Digital Assistants are – but they involve some combination of software, hardware, typically with some form of Machine Learning or AI capability. Beyond that, we start getting into the differences between Alexa and HAL 9000, Robot B-9, R2D2, C3PO, Elon Musk’s Neurolink, and Borg.
This line of logic will eventually drive you insane, asking (like the EU Parliament) whether digital assistants are robots and whether we should give robots rights as electronic persons (See 59 – e)? And while that sounds absurd, recall that corporations are legal persons.
“Alexa, order me a large Extravaganza Pizza with extra jalapenos!” In 30 minutes or less, a pizza will be at your door. That’s pretty simple.
But, Intelligent Digital Assistants are rapidly getting more sophisticated and capable of at least answering some radically complex questions. Oh, some can easily beat fighter pilots, too.
Revenue.AI has an AI digital assistant (named RAI) “who” specializes in Revenue Management – a big thing in the travel and hospitality industry (before COVID), but even bigger in consumer packaged goods.
RAI can answer questions like, “What is the best price for a 2-liter bottle of ‘Beastie Beer’ to increase market share” in Japan’s supermarkets?”
It’ll cross-reference all competitor products in the same bracket, factoring a wide range of data points like brand popularity, transportation overhead, and many others to provide an optimized price to minimize cannibalization while attracting new beer drinkers.
Beastie Beer’s the Beer That Bites Back. Totally fictional product, an absolutely real scenario.
Artificial Intelligence – and by extension, Intelligent Digital Assistants are already awesome when it comes to handling not just Big Data – but Exponential Data.
It remembers everything, spots patterns, and performs complex calculations exponentially faster than humans. Data is concerned with a Virtual Vendetta of V-words like Volume, Velocity, Variety, Variability, Veracity, Value, and Visibility.
It’s hard to get a handle on just Data Volume and Velocity. Data Centers like Walmart’s Area 71 often handle Terrabytes of data daily. A single product might have 100 or more data points associated with it – be sold by dozens of different store alongside scores of competing products, in up to almost 200 different countries/regions.
It can take a traditional Revenue Management team 6 months to set up their 5-year pricing strategy on a per-country basis. A digital assistant like RAI makes it almost a real-time exercise with the added granular capability of optimizing on a per channel and store basis.
We thought the following “Big Data” snapshots might be fun and helpful to appreciate how much data we all have to work with – to sort through, analyze, and reach profitable decisions upon:
18,000 pages, 14x longer than “War and Peace.” It’d take a developer 4 months to read.
Walmart’s 11,600 m2 data center capable of holding a whopping 460TB of data.
In software development, the #1 expense is usually wages for software developers, driven in part by a global shortage of sufficiently skilled developers. A digital assistant offers engineering managers dramatically enhanced capabilities for optimizing their team’s performance.
Per the US Bureau of Labor Statistics, the average wage of software developers in the United States is $110k. Fully loaded costs (taxes, benefits, insurance, overhead), add 25-40% pushing the in-house cost to about $145k. The average Agile team has seven developers. That puts us over $1 million a year, for one “average” in-house team.
Though a bit dated (2018), Stripe’s The Developer Coefficient presents that the “average” team is just 68.4% efficient in their work. Inefficiency burns about $310k or 4,601 developer hours – per team per year. We see developer hours as the key bottleneck. Hiring more developers increases organizational complexity and feeds inefficiency.
The “smart money” maximizes existing resources and adds complexity only as truly needed.
In How to Make a Difference with 1-on-1 Meetings, we made the case that your real “mission” is to “engineer your team to perfection as relates to your company mission and product objectives.” It’s (usually) not your responsibility to code, but to help your team be the best coders they can be. One-on-One meetings provide you a feedback loop in learning from your developers how you can do that better.
Intelligent Assistants provide you with an additional feedback loop. This equates to real-time access to data-driven insights enabling you to measure how you are doing – as reflected in your team’s improvement over time. But, IAs are also able to identify and inform you of issues that you need to tackle to help your team write higher quality code, faster and more efficiently.
Software engineer managers might also share some of the benefits that an Intelligent Assistant provides your HR or hiring managers, like:
It’s all just a matter of asking questions and getting answers. But, an Intelligent Assistant can also act as a warning system:
Why Software Developers Leave identifies numerous “triggers” and just as many indicators that one of your developers is thinking about quitting – may be to find another job. Some of these indicators may be shared with developer burnout. Where burnout tends to lead to a gradual decline in developer performance, a developer can suddenly opt to quit.
An Intelligent Assistant can provide you with the kind of real-time awareness allowing to check in with your at-risk developers to see how they’re doing. That never hurts and it helps often enough. The thing is that if you’re paying attention to your developers they’re likely to stay longer and less likely to burn out. The effort to find a replacement and the time it will take the new developer to get up to speed is not something you can completely – but an IA can make it a lot easier to mitigate.
Professional posers and slackers have good reason to be concerned about performance metrics and intelligent assistants. If you can code and honestly want to be a better coder, an intelligent assistant could be your best friend. Please, don’t interpret that as a reflection on your social life.
Professionally speaking, an intelligent assistant promotes awareness not just about how you are performing, but how you can be a better coder. For one, you’ll be able to see how you are faring relative to other developers. The real benchmark is to simply strive to be a better coder today than you were yesterday.
Here’s what should be happening…
A senior developer can often do in an hour or two what might take a junior developer all day. As a junior developer, that might be disheartening, “How’s that even possible?” But, between standups, code reviews, pull request reviews and interaction, retrospectives, one-on-one meetings, walkthroughs, and a lot of day-to-day experience, you can see the grass grow.
An intelligent assistant is like an “assistant coach” providing you insights that you can use to be a better coder – like working on reducing your code complexity or prompt you to ask another developer how their code churn is consistently lower than everyone else’s.
Junior developers make, what? $80k? If you apply yourself, within 18 months you could potentially qualify as a mid-level developer to make ~$100-110k. After that, it may take several years before you can be a senior developer. Even so, you still have your choice to work remotely for companies in exotic destinations like Silicon Valley. Bad example, but that could be good for a $10-30k yearly boost.
Article updated: April 14, 2022
