top of page

The 'Technology' We Use Most in the Age of AI: Reminders

  • Writer: souladvance
    souladvance
  • May 13
  • 3 min read

Introduction

We are a technology company. Our focus? AI, machine learning, automation – basically, any fancy word that shapes the future is cooking in our kitchen. The vision we present to the outside world is clear: simplifying life, optimizing processes, minimizing the potential for human error. But what about our own kitchen? Ah, the kitchen... that's a whole different world.


While AI is Discussed, Reality Knocks...

Every day, in every corridor, in every virtual meeting, we talk about the power of artificial intelligence. "How can we automate this process with AI?", "How can we evaluate this data with learning algorithms?", "Where should AI be used to provide the best customer experience?"... These sentences fly through the air, presentations are dazzling, the future is bright!

But then we pause for a moment and look at our daily operations. And we face the harsh truth: Do you know the "process" we spend the most time on, that consumes the most energy within the company? Reminding people to do things.


The Manual Reminder Process: An Engineering Marvel (!)

While selling automation outside, internally we've practically become experts in "manual reminder optimization." This process is much more sophisticated than you might imagine:

  1. The Initial Trigger: A task needs to be done or information is needed.

  2. Goal Setting: Who was responsible for this task? Which team? (Here, human memory, our most primitive 'database', comes into play.)

  3. Channel Selection and First Attempt: Should we send an email? Write on Slack? Maybe just a ping will do? (Since AI can't predict the right channel and time, random shots are allowed.)

  4. Feedback Mechanism: Did a reply come? Or not? Was it read but not understood? (Here, AI's 'sentiment analysis' capability falls short, entirely dependent on human interpretation.)

  5. Escalation Matrix (Manual Version): If there's no reply or the task isn't done...

    • First Reminder (Gently): "Just wanted to remind about this..."

    • Second Reminder (A bit more insistent): "Waiting for an update on this..."

    • Third Reminder (Slightly reproachful): "It was urgent, what's the status?"

    • Fourth Reminder (Desperation): Calling on the phone, walking to their desk, shouting (kidding! Or maybe not...)

  6. Team Multiplier: Now, multiply this process by the number of teams in the company. Each team is a different planet, requiring a different reminder orbit. While reminding one, there's always the risk of forgetting the other. You'd think we're training a separate AI model for each team's brain; when one gets the reminder, the other gets formatted or something.

The Apex of Irony

While AI algorithms process billions of data points to make predictions, internally we're panicking, thinking, 'Did I remind our people about tomorrow's meeting?' We sell automation solutions, but we can't even fully automate the most basic "To-Do Tracking" process internally.


A reminder note on the fridge with a sad face magnet urging you not to forget an important task.
A reminder note on the fridge with a sad face magnet urging you not to forget an important task.

We are a tech giant, but for internal communication, it's as if pigeons are flying between us, and that too depends on the pigeon's performance for the day.

Perhaps there's a deep philosophy underlying this situation? Maybe the fine line that distinguishes humans from machines, that "natural intelligence," is that unique forgetfulness and the need for reminders that AI can never truly replicate? And maybe our company, no matter how much it exalts AI, proudly preserves this fundamental human "feature"(!)?

Conclusion (Until the Next Update)

In short, while the world discusses a brilliant AI vision from the outside, the unsung heroes (that is, all of us) who sustain that vision internally continue tirelessly, day after day, being a link in the reminder chain.

Whether AI will take over the world one day is unknown, but it seems it will take a little longer to take over the kingdom of forgetfulness within us.

Now, if you'll excuse me, I need to send out that team meeting reminder and complete the day's 'manual intelligence' shift. Wouldn't want to forget!


1 Comment


YeGoblynQueenne
May 15

Looking at early telegraphs doesn’t predict the iPhone, etc.

The problem with this line of argument is that LLMs are not new technology, rather they are the latest evolution of statistical language modelling, a technology that we've had at least since Shannon's time [1]. We are way, way past the telegraph era, and well into the age of large telephony switches handling millions of calls a second.

Does that mean we've reached the end of the curve? Personally, I have no idea, but if you're going to argue we're at the beginning of things, that's just not right.


https://news.ycombinator.com/vote?id=41680488&how=up&goto=item%3Fid%3D41667652

________________

[1] In "A Mathematical Theory of Communication", where he introduces what we today know as information theory, Shannon gives as…

Like
bottom of page