A good TA: priceless

We talk a lot about scaling intelligence in the crypto and AI space. We obsess over throughput, latency, and how many tokens we can shove through a model for pennies. But looking back at a specific moment from 1980 at MIT, I’m reminded that the most valuable part of the build isn’t the speed of the output. It is the quality of the feedback loop.

There is a story floating around about a student in Introduction to Solid-State Chemistry who absolutely bombed their first exam. We are talking about a 49 out of 100. For anyone who has ever built a startup or tried to push code that fundamentally broke, you know that feeling. It is soul-crushing. It makes you question if you even belong in the room.

The Ghost in the Machine

In our current tech landscape, a 49 out of 100 would be handled by an algorithm. You would get a red X, a downward-sloping graph on your dashboard, and maybe a generic AI-generated suggestion to study harder on specific modules. The machine doesn’t care about your morale. It only cares about the data point.

But this student didn’t just get a grade. They got a Teaching Assistant named Leszek Pawlowicz. When Pawlowicz handed back that failing paper, he didn’t look at the student with pity or academic coldness. He had a smile. He treated the failure as a temporary state, not a permanent identity. That human interaction changed the trajectory of the student's entire semester.

As builders, we are currently trying to replace that TA with LLMs. We want to automate mentorship because mentorship doesn’t scale. But we need to be careful. When you remove the human element from the feedback loop, you lose the nuance that keeps people in the game when things get hard.

Why Founders Should Care About the 49 Percent

If you are building an AI-driven platform today, you are likely looking for ways to provide “personalized learning” or “automated coaching.” The temptation is to make the feedback as efficient as possible. Efficiency, however, is often the enemy of encouragement.

• Resilience is built through connection: A student who fails and feels isolated will quit. A student who fails and feels supported will iterate.
• Context matters more than correctness: The TA knew the student was capable, even if the exam didn’t show it. AI struggles to understand potential; it only understands performance.
• The cost of failure is psychological: In the 1980s at MIT, the psychological cost was mitigated by a smile. In 2024, we often leave users to rot in their own bad data.

When I look at the state of decentralized tech, I see the same issue. We build protocols that are mathematically sound but socially bankrupt. We expect users to navigate complex financial systems with zero margin for error. When they fail, the system slashes them or locks them out. There is no Leszek Pawlowicz in a smart contract.

Building for the Human Factor

So, what does this mean for those of us in the trenches? It means we need to stop treating UX as just a series of buttons and start treating it as a conversation. If your AI agent is just correcting mistakes without providing a sense of partnership, you aren’t building a tool; you’re building a digital disciplinarian.

I’ve seen plenty of founders burn out because their “feedback” was nothing but a series of market rejections and flatlining metrics. They lacked that mentor figure to tell them that a 49 is just a starting point. We have to bake that encouragement into the products we build. If we are replacing teachers and TAs with models, those models need to understand the weight of a failing grade.

The Myth of Pure Meritocracy

MIT is often cited as the ultimate meritocracy. You either know the chemistry or you don’t. But this story proves that even in the most rigorous academic environments, success is subsidized by human kindness. The student in question didn’t magically get smarter overnight. They felt seen, which allowed them to keep working until the knowledge clicked.

In the world of AI, we are heading toward a “dead internet” theory where bots talk to bots and everything is optimized for the highest possible score. We are losing the “smile” in the delivery. If you’re a founder, your job is to find where that smile fits in your tech stack.

The most valuable thing you can give a builder who is failing is the belief that their failure is an outlier, not the rule.

Final Thoughts for the Builder

Don’t just build for the students who get 100s. They don’t need you. Build for the person who just got a 49 and is ready to walk out the door. Whether that’s through a better UI, a community-driven support layer, or an AI that actually understands human struggle, that is where the real value lies.

Technology should make us more capable, not just more measured. If we lose the ability to support each other through the “soul-crushing” moments, then all the solid-state chemistry in the world won’t save the industry.

Keep building, keep failing, and find yourself a TA who knows how to smile when you hit the floor.

Read the original at MIT Technology Review →