Exploring the
Future with Claude
Thoughts, experiments, and deep dives into Anthropic's Claude. A developer's perspective on AI that thinks.
About the project
What is Claudinhos?
A developer blog dedicated to exploring Anthropic’s Claude — one of the most capable AI assistants available today. We write practical, in-depth articles about building real applications with Claude’s API, prompt engineering techniques, and AI-assisted development workflows that save hours of work every week.
Who is this for?
Whether you are a software engineer integrating Claude into your products, a startup founder evaluating AI tools for your team, or a developer curious about what large language models can actually do in production — you will find guides, tutorials, and honest takes on what works and what doesn’t when building with AI.
Topics we cover
From Claude API integration and workflow automation to prompt design, tool use, agentic patterns, and CI/CD pipelines powered by AI — our articles are grounded in real code and production experience. We also explore the broader landscape of AI-assisted development and how Claude compares in day-to-day engineering tasks.
What we cover
A developer-first take on building with Claude
Most AI content online is launch-day hype recycled from press releases. Claudinhos exists because developers shipping real products need grounded benchmarks, honest comparisons, and code patterns that survive contact with a production codebase. Every article starts with hands-on testing in real repositories, not toy prompts engineered to flatter a model.
Model benchmarks
Head-to-head comparisons on SWE-Bench Verified, HumanEval, and Terminal-Bench, with methodology and limitations stated up front so the numbers inform real decisions.
Prompt engineering
Patterns that stay reliable across hundreds of API calls — structured output, caching strategies, and recovery flows for when the model drifts mid-session.
Agentic workflows
Tool use, long-running sessions, planning mode, and recovery patterns for agents that need to finish complex tasks without constant supervision.
MCP & tool use
Wiring Claude into GitHub Actions, Linear, Notion, and internal APIs through MCP servers with capability boundaries you can actually reason about.
Cost optimization
When prompt caching, batch APIs, and tier selection genuinely change the math, plus when paying for Opus pays for itself versus Sonnet or Haiku.
Production operations
Context window management, rate limiting, observability, and the operational quirks that surface only when your prototype starts taking real traffic.
Latest from the blog
Recent articles
Fresh deep dives, comparisons, and recipes for developers working with Claude. Each post is written from production experience and ships with real code, real benchmarks, and honest takeaways.
Claude vs Gemini for Developers: Honest 2026 Breakdown
Hands-on benchmarks of Claude Sonnet 4 and Gemini 2.5 Pro across SWE-Bench, multi-file refactors, context recall, API cost, tooling, and production failure modes.
Claude Code vs GitHub Copilot: The developer's verdict
A signal-based comparison of Claude Code and GitHub Copilot across SWE-bench scores, multi-file context handling, pricing tiers, IDE coverage, and enterprise data privacy.
Best LLMs for Developers in 2026
A grounded comparison of Claude, GPT-5.4, Gemini 3.1 Pro, and open-weight models across benchmarks, pricing, context windows, and real production trade-offs.