3 Simple Mistakes That Kill 80% of AI Projects

AI projects keep failing for reasons no one wants to admit. The surprising part is how easily they can move ten times faster when the setup is done right. 

Most companies never reach that point. They get blinded by the early sparkle and miss the traps hiding underneath.

Non-tech teams can build real AI when they pick the right quick wins, use simple building blocks and stitch human judgment to machine output.

The approach is simple, repeatable and almost nobody is using it the right way.

Common mistakes that kill projects:

• Believing the “magic effect” and expecting instant results

• Ignoring the final 20 percent where projects actually break

• Never teaching people how to think and work with AI

In this episode we cover how non-tech companies can ship working AI, why the messy final 20 percent matters more than your demo, and one simple prompt trick that helps builders go deeper. Curiosity still beats every tool on the table.

You’ll replay this part: a strange trick that turns into the top advice for young builders.

AI agents are starting to run long enough to build something close to real memory.

For the first time, agents are starting to run long enough to build memories, form plans, and carry entire experiences forward. 

The window is opening to something closer to a digital lifespan. The moment they stop resetting, everything changes.

The science behind this shift is even stranger. Wearable brain computer interfaces are reading thought patterns from outside the skull. Sensory tools are letting people see through their tongues. Neural implants are pulling language directly from the brain. 

We uncover how long-running agents learn differently from short running ones, why Meta’s BCI experiments matter more than the headlines, and how continuous experience turns an agent into something that feels alive. 

The interview goes far deeper than any prediction. It shows how close we are to machines that remember every moment.

You’ll replay this part: the digital experience becomes something you can hand over like a memory.

Data is not the bottleneck anymore. This conversation begins with a truth that feels almost too obvious once you hear it. 

Every new model demands more power than the one before, and the hunt for energy has started to reshape how the entire stack gets built.

The strange part is how invisible this trend has been to everyone who is not designing the systems themselves.

A new way of thinking is spreading across the infrastructure world. Local generation instead of distant grids. Electricity measured like currency. Even waste streams turning into power sources. 

It sounds unbelievable until you see the numbers and the experiments happening in places nobody would expect.

Microgrids built from local power. Solar on every rooftop. Even dairy farms turning their manure into electricity strong enough to feed a megawatt system. Two thousand cows can power an entire data center.

The conversation in this episode peels back the physics behind the AI boom and reveals why so many of our assumptions about sustainability fall apart the moment you count joules instead of dollars.

This is the plot twist of the entire energy conversation, the kind of detail that changes how you look at every device you own.

You’ll replay this part: A single accounting move that makes sustainability cheaper and practical now.