Ideas Weave Every Narrative with AI.
Most AI-generated documents are unreadable because the model is designed for reasoning, not for natural language. The fix isn’t better prompts—it’s choosing the right model and ruthlessly pruning the context you feed it. A product manager’s hard‑won lesson from testing Grok, Claude, and GPT on real project docs.
Stanford’s CS329A course reveals the hidden frontier of AI: not bigger models, but smarter inference-time compute and reliable verifiers. Small models, given 10,000 attempts, can outperform GPT-4. The real bottleneck isn’t parameters—it’s building verifiers that can judge complex outputs. The next AI revolution won’t be about scale; it will be about trust and self-correction.
Kimi K3’s 2.8-trillion parameter model didn’t just top the coding leaderboard; it shattered the illusion that open-source AI equals cheap alternatives. By demanding massive deployment costs and flagship-level API pricing, Moonshot AI has rewritten the rules. Open source is no longer for the poor—it’s a high-value luxury. The gap between model capability and productization is your next big opportunity.