#reasoning-models
13 articles
Limits and failure modes: overthinking, underthinking, and when reasoning breaks
The empirically-documented ways reasoning models fail in production — overthinking, underthinking, sycophantic traces, benchmark gap — and how to detect and route around them.
Reasoning Distillation: Teaching Small Models to Think
How DeepSeek-R1 distillation lets a 7B model out-reason a 32B baseline — the mechanics, the learnability gap, and what breaks in production.
How reasoning models are trained: RLVR, GRPO, and the post-training stack
The post-training recipe behind o1 and DeepSeek-R1: how RLVR and GRPO replaced RLHF for reasoning, with real training mechanics and failure modes.
Reasoning models plus tools: agentic workflows and function calling
How o3, o4-mini, and Claude extended thinking combine reasoning with tool calls to make harder agent tasks tractable — and the failure modes they introduce.
Preference Optimization: DPO, SimPO, ORPO, and the Post-RLHF Stack
How DPO, SimPO, ORPO, and GRPO replaced the classic RLHF pipeline — what each method removes, when to use which, and the 2025 reasoning-alignment frontier.
Cost, latency, and the model-selection decision tree for reasoning
A practical framework for choosing between reasoning and standard models, with real cost and latency numbers from 2025-2026 deployments.
Test-Time Compute Scaling: Sequential, Parallel, and Tree-Based Strategies
How reasoning models spend more compute at inference time via longer chains, Best-of-N sampling, and tree search — and the cost, latency, and accuracy tradeoffs of each.
Few-shot prompting, chain-of-thought, and reasoning models
Master few-shot prompting and chain-of-thought, then learn why both techniques must be rethought entirely for o3, Claude extended thinking, and Gemini 2.x.
The model landscape in 2025-2026: closed frontier, open-weight, and reasoning
GPT-5, Claude Opus 4, Gemini 3.1, Llama 4, DeepSeek-R1: what the three competitive tiers actually mean for engineers picking models in production.
Prompting reasoning models: what changes and what breaks
The counter-intuitive rules for prompting o3, DeepSeek-R1, and Claude extended thinking — simpler prompts often outperform elaborate ones, and common techniques backfire.
ReAct, Reflexion, and Planning Patterns
How ReAct, Reflexion, Plan-and-Execute, and LATS differ as agent planning strategies — with honest benchmarks, failure modes, and a decision framework for production.
What Are Reasoning Models? Chain-of-Thought, o1, and the Inference-Time Shift
How o1-style models differ from standard LLMs: internal chain-of-thought via RL, not prompted CoT, and why that changes your prompting, cost model, and architecture.
Reasoning Models: When and How to Use Them
Reasoning models spend inference tokens thinking before they answer. Learn when that's worth it, when it's a waste, how prompting changes, and how to control cost.