AI “loops” sound elegant until you have to debug one. Prompts calling models calling tools calling prompts, and no clear state. The real cost of autonomy is traceability. How is a human supposed to clean that up?
Waiting to ‘fix all the fundamentals’ before embracing AI is like refusing to use the internet until dial-up speeds improve. Progress never waits for perfection.
💡 @tlberglund and I talk every day about strategy, priorities, and growing people. But this one’s different. This time, we recorded it. Join us for a candid conversation on the project that turned out to be truly career-defining. 🎙️
In a startup world, you learn a lot and fast. One of the signals of healthy team culture is when the most experienced people say to everyone, "I have no idea how to do this. I'll have to figure this out."
Orchestrating agents feels new, but we’ve done this for years with microservices, workflows, and event streams. The difference is: agents are non-deterministic. this makes evel and validation loops critical for success.
Every major AI lab is hiring people who can: – ship eval pipelines – scale training infra – write interpretable logs MLE ≠ "fine-tune a llama" It’s how to make reasoning reliable at scale. Get in. It’s day 1.
The best time to start in ML was 5 years ago. The second best time is after reading that an LLM solved 5 IMO problems in natural language. The field just shifted from language generation to reasoning. Learn to build systems, not just prompts.
If you are a data engineer wondering what AI skills to master, read my latest article. And let’s talk! Now, number 1 trending story on TheNewStack 📰
Building AI agents? 🤖🤖🤖 You might actually be building microservices. @AdiPolak is back at the lightboard to explain what an AI agent is, what a modern AI system looks like, and how to architect that system for production using event-driven microservices! Watch the full…
This great presentation from @AdiPolak about data streaming includes the type of knowledge you want to have before prompting LLMs to build any complex systems. Ask better questions by first knowing these architectural concepts! infoq.com/presentations/…
If you are reading here ✨ You’re ahead of the curve. Most people are still trying to understand how AI and streaming work—you’re helping shape the future of both.
Precision in AI? In the last couple of years, @QCon has became a home where I come to learn from and connect with the best in the industry. This year, I was also able to contribute. Read here infoq.com/news/2025/04/a…
You Don’t Need a PhD to Win with AI. New blog alert: 🧠 Curious what is MCP? 🧠 How is MCP different from A2A? 🐝 What's BeeAI? 📚Read here to learn more! open.substack.com/pub/adipolak/p…
In 5 years, real-time AI pipelines will replace 80% of batch workloads, and enterprises that don’t adopt AI-driven streaming will become obsolete.
we just launched two things: o1, the smartest model in the world. smarter, faster, and more features (eg multimodality) than o1-preview. live in chatgpt now, coming to api soon. chatgpt pro. $200/month. unlimited usage and even-smarter mode for using o1. more benefits to come!
So, do you truly believe AI can build your data strategy.. ?
A decade ago AI slowed down due to lack of compute abilities. It was basically a supply chain and money issue. This time, deployment patterns, observability, and automated feedback loop has became the bottleneck. Some companies has solved that for a case-by-case basis. There's…
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