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Key Takeaways AI often fails outside of demos because it can’t learn from real-world mistakes or adapt to unpredictable users and systems.
Founders who focus on AI that improves over time — not just executes commands — are the ones turning automation into real business results.
According to the internet, startups are running entire companies on AI. Founders have AI sales teams closing deals while they sleep. AI agents are supposedly replacing full departments overnight.
Meanwhile, your agents stall out. They make questionable tool calls, get stuck in loops and fail to complete tasks reliably.
That doesn’t mean you’re behind. It means you’re operating in the real world.
Your AI agents interact with real customers, real enterprise systems and real constraints. When they make mistakes, those mistakes don’t disappear into a demo — they cost time, money, and credibility.
You’re not alone
Research from MIT helps explain why this gap exists.
Tools like ChatGPT are now ubiquitous. MIT found that roughly 90% of employees in surveyed companies use large language models regularly at work. Coding agents such as Claude Code, Cursor and Codex have become standard in many developer workflows.
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