Artificial Analysis benchmark write-up of Anthropic's Claude Sonnet 5.5: scores 56 on the Intelligence Index, two points behind Opus 5.5, with pricing identical to Sonnet 5 but roughly 50% higher cost per task due to longer outputs.
Anthropic's developers share tips, playbooks and opinions on building with Claude and Claude Code, including agents, skills, context engineering and prompt caching.
Why I recommend it: Written by the company that makes Claude, so it's practical but not neutral. Best read by people who already use Claude for coding.
The first volume of Tech:NYC's Decoded Futures prompt cookbook: ready-to-copy AI prompt recipes for nonprofit work, sorted by task, each offered at three levels of detail — a quick one-paragraph version, a structured version with steps, and a full version specifying role, steps and output.
Why I recommend it: Free, no account, nothing to install — you copy a prompt and paste it into whichever assistant you already use. Start at the Low level if you are new; it works with no setup. Swap the bracketed placeholders for your real organization details, because a prompt left generic gives you a generic answer. Volume 2 is also in this library; V.1 is still worth keeping for the tasks it covers that V.2 dropped. Written for nonprofit teams, but the recipes for writing, summarising and planning transfer to any job.
Anthropic's own announcement of Claude Opus 5.5, published 22 September 2026 — the first model in the Claude 5.5 family. The company's claims, in its own words: it performs at the level of Claude Fable 5.1 on most work and costs 40% less to run than Opus 5 on typical workloads; on Anthropic's automated behavioural audit, its most comprehensive internal alignment test, it scores the highest of any model the company has tested. The page also cites early-tester anecdotes, including one completing a 680,000-line code migration in under a day, and a result of succeeding 39 times out of 40 on a page-load optimisation task. It is Anthropic's first release since the company publicly called for pacing the frontier, and it was tested before release by external evaluators including METR and Frontier Design.
Why I recommend it: Read this as a primary source, not as a review. Every performance and cost figure on the page was produced by the company selling the model, on tests it designed — that does not make them false, it makes them unchecked by anyone with a reason to doubt them. The checkable part is the external pre-release testing by METR and Frontier Design, so that is the part to weigh. Note too that '40% less to run than Opus 5' compares Anthropic with its own older model and says nothing about a rival's price, and that the standout numbers come from hand-picked early testers rather than a measured success rate you can plan around. The announcement is free to read; using the model itself is not free beyond whatever the current Claude free tier allows.
AI detector for ChatGPT, Gemini and Claude. Claims third-party verified accuracy for essays, articles and documents.
From the site: AI Detector for ChatGPT, Gemini & Claude — Remarkably Accurate. Detect AI-generated text in essays, articles & documents. Third-party verified results.
A technical design paper by Alice Poteat (Anthropic, August 2026) setting out how function hooks let plugins extend Claude Code — the event model, composition order, rendering and enterprise controls.
Why I recommend it: Advanced and unapologetically technical. Read it as an example of a clear design document as much as for the AI tooling itself.
The public GitHub discussion where Anthropic and the community designed function hooks — a way for plugins to extend Claude Code — including the shipped design decisions and community feedback.
Why I recommend it: A rare look at how an AI product feature gets designed in public. Useful if you want to see how technical feedback is actually written.
XDA Developers had Claude Code (Opus 5), Codex (GPT-5.6) and Google Antigravity (Gemini 3.8) rebuild the same website from the same brief. The comparison shows which agent handles detail, polish and real-world edge cases best.
Why I recommend it: Useful if you are choosing an AI coding assistant for side projects or learning to prompt more effectively. The winner is not necessarily the one you would expect.
Anthropic's free learning hub for Claude: structured courses with video lessons and quizzes covering Claude.ai, Claude Code, Cowork, the API, and MCP, with completion badges.
Why I recommend it: A free, name-brand AI credential path. The Claude 101 course alone gives you something concrete to put under "skills" instead of vaguely claiming AI experience.
A downloadable guide to using Claude for LinkedIn content: audience research prompts, voice calibration, and reusable prompt frameworks for turning an hour into a week of posts.
Why I recommend it: The prompt frameworks in here are the useful part - especially the audience pain-point mining prompt. It is a lead magnet for a paid program, so take the system and ignore the sales pitch.
A research report based on roughly 95,000 search result records across 3,000 prompts in Claude, laying out seven patterns behind which sites AI assistants cite - useful if you want your business or personal site to surface in AI answers.
Why I recommend it: AI answers are becoming a discovery channel whether we like it or not. If you run a business or a personal site, this is a practical read on being findable there.
Prompting framework and twelve worked prompts for using a top-ranked model on finance and analysis tasks.
Why I recommend it: Steal the prompt structure, not the finance specifics. The same framing works for market research or competitor scans in your own business.
Five-step walkthrough from Innovating with AI on creating a reusable Claude Skill so an assistant writes and works in your voice.
Why I recommend it: Details: build one skill around a task you repeat weekly — cover letters, client recaps, outreach — and you will feel the payoff immediately.
Free, self-paced hands-on lab using ChatGPT, Claude, Gemini, NotebookLM, and Perplexity for real work tasks.
Why I recommend it: A recognizable university name on a free AI literacy course. Finish it with one work problem you solved using the tools so you have a story to tell.
Entrepreneur White Paper: AI Tools, Prompts & Strategies for Founders
Jacqueline Tangorra's Entrepreneur white paper with 30 startup ideas, a 12-tool AI stack, four business prompts, and 12 deep strategy prompts for market sizing, competitor analysis, pricing, go-to-market, unit economics, and expansion.
Why I recommend it: The prompt library alone is worth the download. Paste the TAM, pricing, and unit-economics prompts into your AI assistant and you have a consultant-grade first draft.
Anthropic's free course teaching a practical framework for working with AI: delegation, description, discernment, and diligence. Good grounding before you use AI in job search, school, or client work.
In plain terms: This free online course teaches a practical framework for using artificial intelligence tools effectively and responsibly. You can practice prompting techniques, learn how to evaluate AI results, and earn a certificate of completion.
From the site: A free course from Anthropic on the 4D framework for working effectively and responsibly with AI: Delegation, Description, Discernment, and Diligence.
Why I recommend it: This is the fastest way to sound credible about AI in an interview. Take the course, then describe one task you redesigned with AI and what you checked before trusting the output.