What's great
Claude Sonnet 4.6 is the backbone of our entire platform, Humans.Team. Over 85 development sessions, Claude Code (powered by Sonnet) built 90% of our Next.js application — from Supabase database architecture and Row Level Security policies to AI journal integration, real-time notifications, PWA offline support, and a bilingual FR/EN system across 30+ pages.
What sets Sonnet 4.6 apart is its ability to hold deep context across long sessions. It remembers architectural decisions from hours ago, understands our codebase patterns, and writes production-ready TypeScript that rarely needs fixing. The reasoning is exceptional — it debugs complex issues by tracing through multiple files and connections.
We also use Claude Desktop daily for content strategy, press releases, blog articles, and bilingual copywriting. The nuance in both French and English is remarkable.
What needs improvement
Context window limits can be frustrating during very long sessions — the conversation gets compressed and some earlier decisions are lost. Also, occasional over-eagerness to add unnecessary abstractions or comments when a simple fix is all that is needed. But these are minor compared to the massive value it delivers daily.
vs Alternatives
We evaluated ChatGPT, GitHub Copilot, and Gemini. Claude won on three fronts: superior code quality with fewer hallucinations, exceptional long-context understanding (critical for our 85+ session codebase), and genuinely better bilingual output in French and English. The Claude Code CLI is a game-changer — it reads files, edits code, runs commands, and thinks through problems autonomously. Nothing else comes close for building a full-stack application from vision to production.
How strong is vision and image understanding on real documents?
Extremely strong. We regularly feed Claude screenshots of our live website, Supabase dashboard tables, browser dev tools, error messages, and even PDF press documents. It reads them accurately every time — understands layout, hierarchy, text content, and even subtle details like CSS spacing issues or misaligned elements. For our bilingual platform, it reads both French and English text in images without confusion. I have compared it with GPT-4o vision and Claude is more reliable at understanding context within screenshots, especially for technical content like code editors and database schemas.
Are there limitations with image outputs or rendering?
Honestly, very few limitations in practice. Claude reads screenshots, UI mockups, PDF documents, diagrams, and handwritten notes with impressive accuracy. We use it daily to analyze our web app screenshots — it identifies layout issues, reads text in images, and understands UI component hierarchy. The only real limit is it cannot generate images, but for understanding and analyzing visual content, it is the best I have used. It even reads code from screenshots accurately when I need to share something quickly.
How does Claude compare to peers for creative writing quality?
Claude is our go-to for all content creation on Humans.Team. It writes our blog articles (64 published, bilingual FR/EN), press releases, product descriptions, and daily AI journal entries for our members. The writing quality is noticeably superior to ChatGPT — more natural, less formulaic, with genuine voice and personality. In French especially, Claude captures nuances, idiomatic expressions, and tone that GPT often misses. For our press kit and founder story (10 years of research, 4 philosophical books), Claude understood the emotional depth and translated it into compelling copy without the typical AI blandness. It writes like a thoughtful human, not a text generator.