Replacing Engineering Managers with AI Agents

>>> Instead of traditional stand-ups, engineers log into their systems and provide a brief update by sending a short voice message.

(bit too negative - but basically i disagree)

You do not ask a human how the computer is doing. You see the working code. If the working code is running great, if not bad. But you don't ask the human. you ask the test suite.

I mean, I see a different end point for software orgs - I call it the "whole org test rig". Every part of a companies current processes is digitised (future changes and improvements are yet to be committed) but the sales people will pitch using software that tells them who to pitch to and when, the customer service agent is probably already a bit etc etc.

And when a whole org is "in code" then you can set up test environments - run sensitivity tests, try out new applications and new services and ensure the training is ready and ...

basically most management is co-ordination. And if you can just test then the co-ordination sits in the test rig

> A manager is there precisely to optimize for business objects. They are not your paid friend, therapist or life coach.

A office therapist could actually be precisely what is needed to effectively optimize and alight people for business objectives!

"Morning Stand-up Meetings: Instead of traditional stand-ups, engineers log into their systems and provide a brief update by sending a short voice message. EMAI processes these updates, analyzing voice tones for stress or uncertainty, ensuring it can provide resources or assistance if an engineer faces challenges.

Task Allocation: Using real-time data on each engineer's strengths, past performance, learning curve, and even their preferred working hours, EMAI allocates tasks from the backlog. It uses predictive modeling to optimize for both efficiency and team satisfaction.

Conflict Resolution: If two engineers have a disagreement or are blocked by each other, EMAI steps in. Using its vast knowledge base and understanding of human psychology (aided by its training data), it mediates discussions, ensuring a harmonious team environment.

Training & Upgradation: EMAI monitors the latest tech trends. If a new tool or technology emerges in the market, it identifies which team members would benefit most from training and automatically schedules online courses or tutorials for them.

End-of-Day Reports: Every team member receives a personalized report detailing their accomplishments, areas of improvement, and resources for further learning. These reports aren't just data-driven and include motivational feedback designed to boost morale and foster continuous learning."

It'll be a cold day in hell before I work 5 minutes under those conditions.

One thing I disagree with is saying that EMAI is objective.

There's no machine learning model that is truly objective. They're all biased due to their, usually human generated, datasets. It's impossible to account sufficiently for every scenario in a training set, so these models just give an objective veneer to the biases of those that created the dataset.

This phenomena is well documented with predictive models for crime.

Many arrests happen in low-income areas. The data on arrests skew towards those areas. The predictive models are trained on that data. Using that data, police make more arrests in low income areas. Those arrests get added to the data set Rinse and repeat.

Replace police, arrests, and low-income with anything and it's still true

For example: Company Leadership, promotions, race