Blog
Practical articles about building with Anthropic's Claude — from API integration and prompt engineering to workflow automation, tool use, and agentic patterns. Real code, real benchmarks, honest takes.
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.
Claude Workflow Automation Recipes
Production-tested recipes for chained prompts, tool use, hooks, no-code integrations, and GitHub Actions with Claude's API.
Frequently asked
About this blog
Quick answers to the questions readers ask most often about how Claudinhos approaches Claude tutorials, comparisons, and production patterns.
What kind of articles do you publish?
Hands-on Claude tutorials, model benchmarks (SWE-Bench Verified, HumanEval, Terminal-Bench), head-to-head comparisons against GPT, Gemini, and GitHub Copilot, prompt engineering recipes, MCP integration guides, and production patterns for agentic workflows. Each post ships with code you can adapt to your own stack.
How are the benchmarks and comparisons run?
We test on real codebases using identical prompts and identical task definitions across models. When we cite a number, we name the source, the date, and the methodology. When numbers come from third parties, we say so explicitly and link the original report so you can verify or update it yourself.
Who is this blog for?
Software engineers integrating Claude into products, startup founders evaluating AI infrastructure, and tech leads standardizing AI tooling across a team. The articles are written for people who need decisions backed by signal — benchmarks, methodology, and operational data — not vibes or marketing.
How often are new articles published?
New posts ship regularly across the same themes: model evaluation, prompt engineering, agentic systems, MCP and tool use, workflow automation, and engineering management decisions around AI tooling. Bookmark the page or follow tsunode on social to catch them as they go live.
Can I trust the numbers in your comparisons?
We cite SWE-Bench Verified, HumanEval, and other public benchmarks by source with dates and known limitations. When our own session data informs a claim, we say so and disclose sample size — it is our experience, not a controlled study. We never present third-party numbers as if we ran them ourselves.