Navigate the crowded AI model market with confidence. Understand the real tradeoffs between Claude, GPT, Gemini, and open-source models — and make smarter choices for your use case.
Model selection depends on your task type, cost constraints, context requirements, and whether you need multimodal capabilities. This pathway gives you the frameworks to compare: benchmark performance on tasks similar to yours, pricing at your expected volume, context window requirements, and whether you need API access or a consumer product. It also covers open-source alternatives for privacy-sensitive or cost-sensitive applications.
The specific model comparisons (GPT-5.6 vs Claude Fable 5) reflect the 2026 landscape and will evolve. The evaluation frameworks — how to read benchmarks, how to think about fine-tuning vs prompting, how to assess quantization tradeoffs — are durable skills that apply regardless of which specific model versions are current.
10 articles, approximately 6 hours. This is an intermediate pathway that pairs well with AI Foundations for a complete picture of both the architecture and the market landscape.
Understand what AI actually is — tokens, transformers, agents, and the landscape. Start here if you're new.
11 articles · ~4h →Go from vague requests to precise, reproducible AI outputs. The skill that underpins everything.
13 articles · ~5h →Go from zero to productive with Claude Code — the terminal AI coding agent that ships real projects.
15 articles · ~7h →Claude Fable 5 and Mythos 5: SOTA Autonomy and Safeguards
What Anthropic shipped and what it means for agentic work.
Understand and build the loops, harnesses, and protocols that make AI agents reliable and autonomous.
16 articles · ~6h →
