Episode Details

AI models love bullet points — but when you're generating client reports, board memos, or regulatory filings, that default style destroys credibility. In this episode, we break down why transformers favor structured output (it's not laziness, it's the attention mechanism) and compare three engineering approaches to fix it: system prompting (62% adherence), fine-tuning ($200+), and textual LoRAs (94% adherence for $20). Using DeepSeek v4 Pro as a case study, we explore how teams can deterministically steer AI toward flowing prose without losing base model capabilities.