Tutorials Gemini 3.5 Pro: Feed a 2M-Token Codebase in One Call
Load a whole repo into Gemini 3.5 Pro's 2M context, query it without RAG, and cache to cut cost.
How-to content for builders, indie hackers, and AI engineers. Less theory, more shipped code.
Tutorials Load a whole repo into Gemini 3.5 Pro's 2M context, query it without RAG, and cache to cut cost.
Tutorials Hands-on Python guide to Sonnet 5's adaptive thinking, effort levels, and the 30% tokenizer trap.
Tutorials Build a semantic cache that reuses answers for similar prompts and slashes LLM API costs.
Tutorials A runnable Python governor that caps LLM spend per user and auto-downgrades models.
Tutorials Stream Gemini's thought summaries live, control reasoning effort, and track thinking-token cost.
Tutorials Surface, stream, and log Gemini 2.5 Pro Deep Think's reasoning chain with thought summaries.
Tutorials Build a skill-manifest registry so an AI agent wields dozens of skills without context bloat.
Tutorials Build a frugal tool-calling coding agent on NVIDIA's open Nemotron 3 Nano via OpenRouter in Python.
Tutorials Build agents with typed deps, validated output, and offline tests using Pydantic AI.
Tutorials Wire NVIDIA's open 550B MoE into a Python tool-calling loop for long-running agents.
Tutorials Let a cheap executor model consult a stronger advisor mid-task in one Messages API call.
Tutorials Build a provider-agnostic LLM failover client in Python that survives outages and model removals.