The peak of hype isn’t the best moment to reflect on AI. Will it take your job, or is it the next fad like NFTs? Are AI startups ridiculously overvalued, or are the companies that sleep on AI doomed?
Time will tell. LLMs are far from perfect, but I’m excited they’re here anyway. Not because of a silly promise to make me 10x more productive, but because they can solve some problems that were previously unsolvable.

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A detailed account of building and deploying an AI Mentor feature for a coding education platform. The team implemented an event-driven system using Go, Pub/Sub, and Server-Sent Events to help students debug their code. Key challenges included handling LLM hallucinations in production, implementing proper testing (evals), managing costs and rate limits, and building reliable agent systems. The project revealed that AI development is 80% traditional software engineering and 20% AI-specific work, with most complexity lying in orchestration rather than the LLM calls themselves.

Shipping an AI Agent that Lies to Production: Lessons Learned