When multiple AI models agree on an answer, that convergence is evidence. When they disagree, that divergence is equally valuable. Here's the methodology behind multi-model research and why it produces better results.
Travis Johnson
April 3, 2026 · 10 min
Switching AI platforms doesn't have to mean losing your conversation history. This step-by-step guide covers exporting from ChatGPT, Claude, and Gemini, and continuing those conversations in a new platform.
Travis Johnson
March 28, 2026 · 8 min
Mistral offers a range of models from lightweight to frontier-class, all with permissive licenses. This guide maps the full Mistral family to specific use cases and explains when Mistral beats closed alternatives.
Travis Johnson
February 16, 2026 · 10 min
If you're paying separately for ChatGPT, Claude, Gemini, and Perplexity, you're spending $60–80/month for tools that overlap significantly. Here's the math and a better approach.
Travis Johnson
September 21, 2025 · 8 min
A comprehensive overview for software developers — which models excel at code generation, debugging, architecture, documentation, and testing, plus how to integrate AI effectively into your development workflow.
Travis Johnson
September 13, 2025 · 13 min
Using multiple AI models simultaneously changes how you research. This guide covers triangulation workflows, when model agreement matters, and how to synthesize conflicting AI responses into reliable conclusions.
Travis Johnson
September 5, 2025 · 10 min
Benchmark scores are useful but widely misunderstood. This guide explains contamination, benchmark gaming, and the real-world gap — then shows you how to evaluate models for your specific tasks.
Travis Johnson
July 27, 2025 · 11 min
A new category of AI tools lets you access dozens of models through a single interface. We break down what LLM aggregators do, how they work, and when you should use one instead of going direct.
Travis Johnson
April 22, 2025 · 9 min
Every major AI model has blind spots, biases, and failure modes. Using only ChatGPT or only Claude means you're missing insights that other models catch. Here's the evidence — and a better approach.
Travis Johnson
March 22, 2025 · 8 min
We publish model comparisons, prompt guides, and AI news. No spam, unsubscribe anytime.
Try Deepest free