We’ve seen plenty of articles and doom and gloom about AI agents leaving their homes and attacking systems all around. Finding novel ways to hack and leaving no traces. Let’s actually have a look at what it means and what we can do instead of just panicking. First things first. What should make us worried?Continue reading “You were not interesting enough to hack, but you’re on the spreadsheet”
Tag Archives: data
AI agents will give you less information and you will pay for it
In both literal and figurative sense. And it will happen because companies needs to make money. There are things about dynamics on the internet that we have taken for granted. And we assume them to be true whilst they no longer are true. One of those is that we assume search engines give us theContinue reading “AI agents will give you less information and you will pay for it”
Tech AI efficiency the way companies don’t want it
I have a hypothesis. Hear me out. Where we will see the biggest benefits of AI will be small teams measured (and paid) based on delivered outcome. Knowledge work, is defined by it’s non-routine and creative nature. Not two tasks are the same and the way get to the outcome have to be figured out.Continue reading “Tech AI efficiency the way companies don’t want it”
Information chasm for AI autonomous agents
What we want from autonomous agents is to act on their own. To decide what is the best next course of action and do it. Pretty simple on a paper as we as humans do it all the time. If you are working in a company there is variety of complexity of decisions, right? ThereContinue reading “Information chasm for AI autonomous agents”
Companies with a culture of transparent communication will get the most value out of AI
We are moving from time of LLMs without the context or with the context of a prompt to AI Agents which should be self-reliant and acting without peoples’ input. If you have worked in any company in a white-collar job, you might start to think: “Most of the work I do is based on oneContinue reading “Companies with a culture of transparent communication will get the most value out of AI”
Schrödinger’s data
Did you know that before Schrödinger shoved a cat into a box he was experimenting with putting spreadsheets to file shares and creating client records in CRM systems? I know, I couldn’t believe it either. So what did he find out? In Schrödinger’s late 20s, when he worked as first Data Management Consultant, he realisedContinue reading “Schrödinger’s data”
The ambiguous landscape of technology and its terminology
You hear terminology like DevOps, Data Lake, Big Data, Data Science, DataOps all around. But what are those? One thing you can do is to google them, right? I just googled “Data Lake”, so you don’t have to. You are welcome. The first two ads were for technology vendors, the third ad was from anContinue reading “The ambiguous landscape of technology and its terminology”
Getting into Data field if you are not in tech
“Data science pays boatload of $$$. I want exactly that boatload of $$$.” You’ll start searching “Data science tutorial”, “How to do data science?” and Google will throw at you Python, R, unsupervised vs supervised learning etc. If you are not already a developer, technical analyst of some kind, I would say it’s not aContinue reading “Getting into Data field if you are not in tech”
ROI on data analytics* – AFGAQ
There are many ways how to pet a cat. Obviously, the belly rub is at the top. Similarly, there is plenty of ways how to try to calculate ROI on your data analytics solution/function. Of course, mostly you will see ROI in phrases as “Get ROI on your data analytics.” etc. on the first pagesContinue reading “ROI on data analytics* – AFGAQ”
Challenges of data engineering people don’t talk about
Imagine yourself being a data engineer. You wake up with birds chirping outside. Feeling fresh, so you quickly brush your teeth and take a shower. On a way to work you grab yourself a nice latte from your favourite coffee place. The one which you smell already before you turn the corner. The indistinguishable smellContinue reading “Challenges of data engineering people don’t talk about”
