Do you know what the biggest value of any company is? Nice try, but no, it isn't the budget. I'm talking about the expertise of its employees. Therefore, I'm glad that now Techstack Ltd has its internal knowledge base with useful materials recommended by company members.

If you've already answered why you need to build your own #AI model, then the next logical question should be how to actually do it. There are myriad potential places for bruises, so I've come to you with a step-by-step guide on how to soften the blow. cutt.ly/WeLe5j6k

Is our company's #data ready? This is the first question you should ask yourself before adopting AI. No one will answer it but you. The only thing I can help you with at this stage is to share five key steps to data readiness that you can take right now. cutt.ly/NeNa4BPj

Artificial intelligence promises transformation, but without #data preparation, it can't deliver. AI models are worth nothing on their own. And it's better for you to take this for granted at the start than after an unsuccessful implementation attempt. cutt.ly/ye9kWuKT

Writing software, especially prototypes, is becoming cheaper. This means the demand for good #AI product managers, i.e., people who can decide what to build, will only grow. I wouldn't be surprised if some engineers will end up doing more product management work as well.

Anthropic CEO predicts #AGI in the next 2-3 years. Meanwhile, only 8% of the C-suite confirmed that #GenAI is already transforming their companies. The delta between #AI advancement and human readiness is growing too fast, and no one seems incentivized enough to fix it.

How will #data and #artificialintelligence change in 2025? From more pipelines and AI use cases to the birth of the unstructured MDS, the data estate is becoming more complex than ever before. cutt.ly/Ke5x4TXR

The unpleasant truth is that developers soon turn into managers who spend more time reviewing code written by #AI than writing it themselves. It looks like the second wave of coding has begun, and whether we like it or not, it's coming right at us. cutt.ly/6rrnwmvi

Now more than ever, companies need to focus on the non-technical aspects of #AI, like governance, risk ownership, safety, and mitigation of technical debt. After all, end users don't care what's under the hood—what really matters is getting to their destination safe and sound.

#artificialintelligence isn’t just a privilege for big tech companies, as it may seem at first glance. It’s a practical tool businesses of different sizes can use to solve their day-to-day problems. You just need to know how to do it right. cutt.ly/nrpy94A2

I suggest we all finally take off our rose-colored glasses and face the truth 🔽 Companies that don't recognize the critical differences between AI-ready and traditional #data are doomed to fail. And they have no one to blame for this but themselves. cutt.ly/Gra9g4JK

Lately, photos like these have flooded my feed. And apparently, that’s one of the biggest uses of #artificialintelligence right now. Is that where we are? Not better data. Not faster workflows. Just cartoon versions of ourselves.

Sometimes, the most significant results come from minor, intentional adjustments. This is where true #transformation lives: in the quiet, often overlooked corners of our operations, not in implementing as many newfangled tools as possible. Agree?

It was the third year of the “temporary” AI hype… ...and its funding hits a record high! So I'm still expecting this bubble to burst, as #AI skeptics predicted. Based on the screenshots below, “not much” time is left to wait 😉

11 years of experience in #software development. Do you want to know what I've learned during this time? Most people think that programming is about code, but it is not. It's about people. The best engineers understand their users rather than just implementing tickets ☝🏻

How can companies prepare their data for #AI? What is the future of enterprise analytics? Why is the growth of AI operations becoming a critical business function? These are questions that we will all face at some point, whether we like it or not ⏳ cutt.ly/3rWHaKA3

Currently, most information about how #AI systems perform post-deployment is held by private companies. Closing that gap requires building public infrastructure for learning. And adverse event reporting, to me, is one of the key tools for doing that ➡ cutt.ly/FrUitpom

Global industrial robot market contracted 5.8% last year, reports Interact Analysis - The Robot Report therobotreport.com/industrial-rob… #IndustrialRobots #IndustrialRobotics #IndustrialIoT

I want to share this New Yorker article as a shining example of a thoughtful, coherent, and realistic view of the future of #AI based on a human-centric approach. No panic. No rose-colored glasses. No easy solutions to complex problems. cutt.ly/qrA7dm6x

According to OpenAI, the new product works faster, hallucinates less, and makes fewer mistakes. Yet, the thing is that GPT-5 was not expected to be a percentage improvement or cosmetic tweaks, but a qualitative leap. And in the end, we just got a faster and more accurate GPT-4.