The author argues that current AI products, from frontier labs to open-source tools like Ollama, fail to take their problem-solving role seriously, resembling a 'grift' rather than a reliable tool. The post calls for making error-checking and verification first-class features in LLM-based products, particularly those aimed at research or software development. The critique centers on the gap between the obsequious, disclaimer-laden UX of chatbots and what a genuinely trustworthy working tool would require.
Background
The AI product landscape in 2026 continues to grapple with trust and reliability issues, as LLM-based tools struggle to move beyond chatbot interactions into dependable professional workflows. Open-source inference runtimes like Ollama have lowered barriers to local model deployment but inherit the same verification gaps that affect commercial products.
- Source
- Lobsters
- Published
- Sep 29, 2026 at 01:01 AM
- Score
- 5.0 / 10