Reasoning Models and Deep Reasoning in LLMs: Chain-of-Thought, Tree of Thoughts, and Test-Time Compute
Language models don't reason. Not in the way humans do.
5 pages
Prompts
Reasoning Models and Deep Reasoning in LLMs: Chain-of-Thought, Tree of Thoughts, and Test-Time Compute
After reading Wei et al.’s work on Chain-of-Thought, the Tree of Thoughts paper from Princeton, and several recent studies on test-time compute scaling, I wanted to organize what I learned about …
AI as an Amplifier, Not a Replacement: Why Domain Expertise Matters More Than Ever
There’s a narrative floating around that AI will replace domain experts. That if the model can generate code, write architecture docs, and explain EMV flows, then maybe you don’t need the …
AI Sycophancy: Your Model Is Trained to Please You, Not to Be Right
There’s a quiet failure mode in AI-assisted engineering that most people don’t talk about: sycophancy. It’s the tendency of large language models to prioritize agreeing with you over …
Prompt Engineering for POS: Treating LLM Inputs as First-Class Architecture
When we talk about AI in payments, the conversation often jumps to chatbots and support agents. But the real leverage — especially in regulated environments like SmartPOS and SoftPOS — is how you …