claude_opus_4.8_max_thinking_5k_v2

## Overview This dataset captures Opus 4.8’s signature strengths: - Deep, structured, high-effort reasoning - Honest communication about trade-offs and uncertainties - Excellent production software engineering judgment - Strong agentic workflow design - Clear, actionable technical strategy It is intended for fine-tuning open models to behave more like Opus 4.8 in professional software engineering and complex reasoning tasks. --- ## Dataset Details - **File**: `opus_4_8_max_thinking_5k_v2.jsonl` - **Size**: 5,000 examples - **Format**: Chat messages with visible `<think>` reasoning - **Difficulty**: Expert / Professional level --- ## Format ```json { "messages": [ { "role": "system", "content": "You are Claude Opus 4.8 at maximum thinking depth..." }, { "role": "user", "content": "Real-world professional engineering or strategy prompt..." }, { "role": "assistant", "content": "<think>\nVisible high-quality chain-of-thought...\n</think>\n\n**Structured professional response...**" } ], "metadata": { "model_focus": "claude_opus_4_8_max_thinking", "category": "Production Software Engineering" | "Agentic Systems" | "Technical Strategy" | ..., "difficulty": "expert", "example_id": "...", "generated_at": "..." } } ``` --- ## Categories - **Production Software Engineering & Refactoring** - **Agentic Workflow Design & Automation** - **Complex Technical Strategy & Decision Making** - **Code Quality, Testing & Observability** - **Enterprise Systems & Scalability** --- ## Key Features - **True `<think>` tags** on every response — visible, high-quality reasoning process - Highly varied, realistic professional prompts - Concrete, actionable responses with clear structure - Honest handling of trade-offs and uncertainties - Strong focus on developer experience and production realities - No repetitive placeholders or low-quality filler --- ## Intended Use This dataset is designed for: - Supervised fine-tuning (SFT) to improve reasoning depth and software engineering capability - Distilling Opus 4.8-style structured thinking into open-weight models - Research on capability transfer from frontier models - Building models strong in complex technical decision-making and agentic workflows **Recommended for** teams and researchers who want models that think carefully, communicate honestly, and perform well on real engineering and strategy tasks. --- ## How to Load ```python from datasets import load_dataset dataset = load_dataset("json", data_files="opus_4_8_max_thinking_5k_v2.jsonl") ``` Works well with Axolotl, TRL, Unsloth, and Llama-Factory. --- ## Quality Notes This is a **synthetic** dataset created to emulate the professional output style and reasoning depth of Claude Opus 4.8. It is real model outputs. Every example was generated with care to ensure: - High diversity - Professional tone and depth - Visible, non-trivial reasoning - Practical usefulness for training --- ## License & Responsibility This dataset is provided for research and educational purposes. Users are responsible for ensuring their fine-tuned models comply with applicable laws and ethical guidelines. --- *Generated June 2026 — Focused on maximum thinking depth and professional software engineering excellence.*