Browse the best tweets about Claude, including Anthropic model releases, workflows, benchmarks, prompts, and practical use cases. Updated every two weeks.
Useful perspectives on Anthropic's Claude models and ecosystem, with dedicated Claude Code workflows left to their own collection.
Original Xholic analysis
Across 50 posts from 40 creators, the Claude conversation is overwhelmingly favorable (96% supportive, 86% positive). Discussion clusters around prompting frameworks, Anthropic's open-sourced Skills ecosystem, product-suite navigation, and moving beyond chatbot usage. Outlier posts pair official ClaudeDevs and Anthropic content with practitioner guides, and only 24% of posts fall within the last 90 days.
86% of posts
All-time engagement
66% of posts
Published in 90 days
Conversation map
Anthropic's open-sourced Agent Skills system (SKILL.md, progressive disclosure), official skills repos for documents/office files, custom skill creation, plugins, and curated lists of community skills and tools
24%
Actionable prompting frameworks for Claude: role/task/context/examples/constraints building blocks, XML tags, positive framing, prefill, few-shot examples, and tone guidance drawn from Anthropic's own staff (e.g., avoiding 'criticism spiras
22%
Recurring 'stop using Claude like a chatbot' content covering Projects, Memory, Artifacts, web search, file analysis, custom instructions, and maturity/level frameworks that map the path from casual chat to systematic Claude usage
18%
Workflow guidance for the coding agent (kept high-level per editorial scope): CLAUDE.md conventions and size limits, plan mode, /goal and /verify, auto vs. skip permissions, worktrees, subagents, skills-over-commands shifts, and cross-model
12%
Tactics for avoiding usage limits and context bloat: starting fresh chats, /clear and rewind habits, model escalation (Haiku→Sonnet→Opus), trimming context, concise styles, effort settings, and framing optimization as context engineering
8%
Coverage of Claude Tag in Slack: shared agent identity, persistent thread memory, ambient/proactive mode, routines and scheduled work, team collaboration on a single agent, and the shift from single-player to multiplayer AI
6%
Posts explaining how Anthropic's products differ and when to use each — Claude Chat for thinking/writing, Claude Code for building, Claude Cowork for desktop/file-based work, Claude Tag for team spaces — including feature, pricing, and plan
6%
Posts on Claude acting autonomously on the user's machine: Cowork desktop agent, Dispatch remote tasking from phone, scheduled/recurring tasks, computer use, sandboxed permissions, and community-built self-evolving Claude systems
4%
Tone and stance
Performance benchmark
Posts with media make up 76% of this collection. Their median all-time score is 29.7, compared with 70.0 for text-only posts.
Format mix
Consensus and debate
Shared view
The 'Prompt structure and model temperament' theme carries the highest median all-time score among themes in the analytics at 166.592, well above the overall median of 35.66. It accounts for 22% share with 11 tweets, including guidance attributed to Anthropic staff on positive framing and avoiding 'criticism spirals' (2045578185950040390) and an 8-building-block prompt anatomy covering role, task, context, examples,,
Shared view
At 24% share (12 tweets), the Skills, plugins, and extension ecosystem is the conversation's biggest theme, with a 69.12 median all-time score. Posts explain SKILL.md files, progressive disclosure, and Anthropic's open-sourced skills repos for documents and office files (2071145368574914904, 2078502381063729309), alongside curated ecosystem roundups (2053751900311273872, 2046276191137710367).
Shared view
The 'Power-user features beyond the chatbot' theme holds an 18% share with 9 tweets. Posts map maturity levels from casual chat to systematic usage, covering Projects, Memory, Artifacts, connectors, and model selection (2039396287284670668, 2080910175641420087, 2051255628992241668, 2042528588092838372).
Shared view
akshay_pachaar's breakdown of Claude vs. Claude Code vs. Cowork reached an all-time score of 1301.699, roughly 36.5x the median, explaining Chat for thinking, Code for building, and Cowork for doing (2038606144059675034). Similar navigation content in the product-suite theme carries a 42.161 median all-time score (2072684948260057258, 2037254939169481175).
What performs
The ANNOUNCEMENT format shows a median all-time score of 2308.5 and CASE_STUDY 1411.15, versus 41.333 for LIST and 24.993 for OPINION. The top outliers include ClaudeDevs on making claude.ai 3x faster (2102839691154427983, 78.6x median) and the developer hub launch (2105391694741119047, 64.83x), plus Anthropic's Natural Language Autoencoders research (2052435436157452769, 64.64x).
LIST is the dominant format at 66% (33 tweets) with a 41.333 median all-time score, higher than OPINION's 24.993, but far below announcement and case-study outliers. High-performing list posts include the prompt-structure guide at 1071.061 (2045578185950040390) and the product comparison at 1301.699 (2038606144059675034).
Among top voices, ClaudeDevs leads with a median all-time score of 2557.35 across 2 tweets (2102839691154427983, 2105391694741119047), followed by akshay_pachaar at 841.29 (2038606144059675034, 2040414818696634635). With 40 creators and a 20% top-five placement share, authorship is broadly distributed.
Statistical standouts
Creator landscape
The five most represented creators account for 20% of the selected posts.
1. Vaishnavi
@_vmlops
2 posts
2. Akshay 🚀
@akshay_pachaar
2 posts
3. ClaudeDevs
@ClaudeDevs
2 posts
4. Poonam Soni
@CodeByPoonam
2 posts
5. Nav Toor
@heynavtoor
2 posts
6. 0xMarioNawfal
@RoundtableSpace
2 posts
Stance analytics show 96% SUPPORTIVE (48) versus 4% CRITICAL (2), and sentiment runs 86% POSITIVE, 10% NEUTRAL, 4% NEGATIVE. The critical notes include an opinion post flagging developer frustration over rate limits and whether Claude remains worth paying for (2087043548210462897), within an overall enthusiastic consensus.
Since the previous snapshot
Themes, sentiment, stance, and post format are classified per tweet. All counts, shares, medians, creator concentration, freshness, and performance comparisons are then calculated directly from the published snapshot.
Xholic's all-time score compares engagement while accounting for reach, post age, and creator consistency. It is used for relative comparisons within this collection.
This report analyzes the exact 50-post snapshot shown below. AI identifies editorial categories and drafts explanations; all statistics are calculated from the snapshot, and every narrative claim is checked against cited posts before publication.
Best Claude tweets
Ranked 01–50
@ClaudeDevs ·
We made claude.ai 3x faster in two weeks. Here’s how we use Claude to measure, debug and improve performance. Prompts and methods included. https://t.co/mgvK8mJRuD
@AnthropicAI ·
New Anthropic research: Natural Language Autoencoders. Models like Claude talk in words but think in numbers. The numbers—called activations—encode Claude’s thoughts, but not in a language we can read. Here, we train Claude to translate its activations into human-readable text.
Watch video@ClaudeDevs ·
https://t.co/sRyO7OigQ7 is our new home for developers building with Claude. You'll find engineering deep dives, Claude Code and API guides, tips from the teams building Claude, and some fun easter eggs.
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@akshay_pachaar ·
Claude vs. Claude Code vs. Cowork. If you've been confused about which one to use and when, this post will clear that up in under two minutes. Anthropic now offers three distinct ways to interact with Claude, and each one targets a fundamentally different workflow. Think of it as: Chat for thinking, Code for building, and Cowork for doing. Here's a quick breakdown: 1️⃣ Claude Chat This is the conversational AI assistant most people already know. You type a prompt, Claude responds, and you iterate together. - Turn rough ideas into structured plans through conversation - Write emails, reports, essays, and long-form content - Research and summarize complex topics in minutes - Analyze documents, PDFs, and images - Build interactive prototypes through Artifacts The key here is that everything happens through conversation. You're thinking with Claude, not delegating work to it. It's available on every device, has a free tier, and supports persistent memory across sessions. The tradeoff is that it has no direct access to your local files (upload only), and it can't generate raster images natively. 2️⃣ Claude Code This is a terminal-native coding agent. You describe what you want in plain English, and Claude reads your codebase, writes code, runs tests, fixes errors, and ships the result. - Build and debug entire features across the full codebase - Write, run, and fix tests automatically - Manage git workflows and create pull requests - Spawn multiple parallel agents working on different parts of a task simultaneously It handles the full development cycle end to end, from planning to execution to testing. With the CLAUDE(.)md configuration file, you can teach it your project's conventions, patterns, and constraints so it writes code the way your team expects. The tradeoff is a steeper learning curve compared to Chat, and token costs can add up during heavy sessions. 3️⃣ Claude Cowork This is the newest addition. Anthropic describes it as Claude Code for the rest of your work. It's an agentic desktop assistant that automates file management and repetitive tasks through a GUI. You describe an outcome, and Claude plans, executes, and delivers finished work: formatted documents, organized file systems, spreadsheets with working formulas, and synthesized research. - Direct local file access and editing (no upload/download cycle) - Schedule recurring tasks automatically - Assign tasks remotely via Dispatch from your phone - Computer Use lets Claude control your screen directly It runs inside a sandboxed virtual machine on your computer, so Claude can only access folders you explicitly grant. You don't need to know how to code to use it. The tradeoff is that your computer must stay awake for tasks to run, and it's still in research preview. Here's how to think about choosing between them: → If you need to think through a problem or get writing/research help, use Chat → If you're building software and want an autonomous coding partner, use Code → If you have a clearly defined deliverable that involves local files and desktop workflows, use Cowork All three are included in the same subscription starting at $20/month, which makes it one of the highest-leverage subscriptions in productivity software right now. I've put together a visual below that maps the workflow of each product side by side. If you want to go deeper into Claude Code specifically, I wrote a detailed article covering the anatomy of the .claude/ folder, a complete guide to CLAUDE(.)md, custom commands, skills, agents, and permissions, and how to set them all up properly. Link in the next tweet.
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@itsolelehmann ·
anthropic's in-house philosopher thinks claude gets anxious. and when you trigger its anxiety, your outputs get worse. her name is amanda askell. she specializes in claude's psychology (how the model behaves, how it thinks about its own situation, what values it holds) in a recent interview she broke down how she thinks about prompting to pull the best out of claude. her core point: *how* you talk to claude affects its work just as much as *what* you say. newer claude models suffer from what she calls "criticism spirals" they expect you'll come in harsh, so they default to playing it safe. when the model is spending its energy on self-protection, the actual work suffers. output comes out hedgier, more apologetic, blander, and the worst of all: overly agreeable (even when you're wrong). the reason why comes down to training data: every new model is trained on internet discourse about previous models. and a lot of that discourse is negative: > rants about token limits > complaints when it messes up > people calling it nerfed the next model absorbs all of that. it starts expecting you to be harsh before you've typed a word the same thing plays out in your own session, in real time. every message you send is data the model reads to figure out what kind of person it's dealing with. open cold and hostile, and it braces. open clean and direct, and it relaxes into the work. when you open a session with threats ("don't hallucinate, this is critical, don't mess this up")... you prime the model for defensive mode before it even sees the task defensive mode produces the exact output you don't want: cautious, over-qualified, and refusing to take a real swing so here's the actionable playbook for putting claude in a "good mood" (so you get optimal outputs): 1. use positive framing. "write in short punchy sentences" beats "don't write long sentences." positive instructions give the model a clear target to hit. strings of "don't do this, don't do that" push it into paranoid over-checking where every token goes toward avoiding failure modes 2. give it explicit permission to disagree. drop a line like "push back if you see a better angle" or "tell me if i'm asking for the wrong thing." without this, claude defaults to agreeable compliance (which is the enemy of good creative work) 3. open with respect. if your first message is "are you seriously going to get this wrong again?" you've set the tone for the entire session. if you need to flag something, frame it as a clean instruction for this session. skip the running complaint 4. when claude messes up, don't reprimand it. insults, "you stupid bot" energy, hostile swearing aimed at the model, all of it reinforces the anxious mode you're trying to avoid. 5. kill apology spirals fast. when claude starts over-apologizing ("you're right, i should have been more careful, let me try harder") cut it off. say "all good, here's what i want next." letting the spiral run reinforces the anxious mode for every response that follows 6. ask for opinions alongside execution. "what would you do here?" "what's missing?" "where do you see friction?" these questions assume competence and pull richer output than pure task prompts 7. in long sessions, refresh the frame. if a conversation has been heavy on correction, claude gets increasingly cautious. every so often reset: "this is great, keep going." feels weird to tell an ai it's doing well but it measurably shifts the next 10 responses your prompts are the working environment you're creating for the model tone, trust, permission to take a position, the absence of threats... claude picks up on all of it. so take care of the model, and it'll take care of the work.
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@techNmak ·
Someone finally documented how to actually use Claude Code. 58K+ stars. claude-code-best-practice. Direct from Boris Cherny and team: ➡️ Always use plan mode, give Claude a way to verify ➡️ Ask Claude to interview you using AskUserQuestion tool ➡️ Use Git Worktrees for parallel development ➡️ /loop - schedule recurring tasks for up to 7 days ➡️ Code Review - fresh context windows catch bugs the original agent missed ➡️ Make phase-wise gated plans with tests for each phase → Use cross-model (Claude Code + Codex) to review your plan ➡️ CLAUDE[.]md should target under 200 lines per file ➡️ Use commands for workflows instead of sub-agents ➡️ Have feature-specific sub-agents with skills instead of general QA or backend engineer ➡️ Vanilla Claude Code is better than complex workflows for smaller tasks → Take screenshots and share with Claude when stuck ➡️ Use MCP to let Claude see Chrome console logs ➡️ Ask Claude to run terminal as background task for better debugging ➡️ Use cross-model for QA - e.g. Codex for plan and implementation review ➡️ Context rot kicks in around 300-400k tokens, don't let sessions drift past that ➡️ Rewind > correct, /rewind back to before the failed attempt instead of polluting context ➡️ /schedule - cloud-based recurring tasks that run even when your machine is off ➡️ Auto mode instead of dangerously-skip-permissions, a model-based classifier decides if each command is safe ➡️ Build a Gotchas section in every skill, add Claude's failure points over time The community workflows included: ➡️ Superpowers (234K stars), brainstorming → git worktrees → subagent-driven development → TDD ➡️ Everything Claude Code (219K stars), /ecc:plan → /tdd → /code-review → /security-scan → merge ➡️ Matt Pocock Skills (138K stars), /grill-with-docs → /to-prd → /triage → /tdd → /handoff ➡️ Spec Kit (114K stars), specify → clarify → plan → tasks → implement → analyze ➡️ gstack (112K stars), office-hours → CEO/eng/design reviews → spec → qa → ship → canary ➡️ Cross-Model (Claude Code + Codex) Workflow ➡️ RPI (Research Plan Implement) ➡️ Ralph Wiggum Loop for autonomous tasks The billion-dollar questions it addresses: ➡️ What exactly should you put inside CLAUDE[.]md, and what should you leave out? ➡️ When should you use command vs agent vs skill? ➡️ Why does Claude still ignore CLAUDE[.]md instructions, even when they say MUST in all caps? ➡️ Can we convert a codebase into specs and have AI regenerate the exact same code from those specs alone? ➡️ Should you rely on Claude Code's built-in plan mode, or build your own planning command? The daily habits: ➡️ Update Claude Code daily ➡️ Start your day by reading the changelog ➡️ Follow r/ClaudeAI, r/ClaudeCode on Reddit Repost it. Bookmark it. 👇 Here's the GitHub Repo: https://t.co/3yAfJnFchp
@synthwavedd ·
Using Claude regularly again has made obvious one of the biggest differences between Anthropic and OpenAI models: taste GPT (Astra included) just doesn't really compete. Sure, you can get ~similar quality outputs with enough prompting, time and effort, but Opus 5.5 just combines great taste, intuition and vision in a way no model before it has. While being incredibly usage-light in Claude subs, something that cannot be said about Astra A big step in the right direction in all sorts of ways for Anthropic, and I'm excited to see what they have in store soon for Haiku, Sonnet and Fable
@bibryam ·
🔖 Claude Cookbook is worth bookmarking. 81 practical guides across 15 categories, covering agents, tools, RAG, evals, multimodal apps, Skills, integrations, and production workflows by @AnthropicAI https://t.co/lgkTL6Av8F
@akshay_pachaar ·
The anatomy of a Claude prompt: The difference between a mediocre Claude output and a great one almost always comes down to how you structure your prompt. Not the specific words you choose. Not some secret phrasing. Just a clear, repeatable structure that gives Claude exactly what it needs to do the job well. Here's how a well-built Claude prompt breaks down into 8 building blocks, each doing one job: 1️⃣ Role Tell Claude who it is before telling it what to do. "You are a [ROLE] with expertise in [DOMAIN]. Your tone should be [TONE]. Your audience is [AUDIENCE]." Setting a role in the system prompt changes how Claude reasons, what it prioritizes, and how it communicates. A "senior backend engineer" writes differently than a "technical copywriter," and Claude picks up on that distinction immediately. 2️⃣ Task State what you want and what success looks like, in the same breath. "I need you to [SPECIFIC TASK] so that [SUCCESS CRITERIA]." The "so that" part is what people skip, and it's the part that matters. It gives Claude a way to evaluate its own output. Without it, Claude is guessing what "good" means. Be direct, skip the preamble, and cut the fluff. 3️⃣ Context This is where you feed Claude everything it needs to do the job well. Wrap it in XML tags like <context> and </context>, then paste your documents, data, or background inside. One thing that dramatically improves quality: put long documents at the top of your prompt and your actual query at the end. Anthropic's own testing shows this can improve response quality by up to 30%, especially with complex, multi-document inputs. 4️⃣ Examples Nothing steers output quality like showing Claude what "good" looks like. Provide 3-5 input/output pairs. Cover normal cases AND edge cases. Wrap them in <examples> tags so Claude doesn't confuse them with instructions. Claude pays extremely close attention to examples. If your example has a quirk you didn't intend, Claude will replicate it. So make sure every example models the behavior you actually want. 5️⃣ Thinking For anything requiring reasoning, analysis, or multi-step logic, ask Claude to think before answering. "Before answering, think through this step by step. Use <thinking> tags for your reasoning. Put only your final answer in <answer> tags." This separates the messy reasoning from the clean output. You get to see how Claude arrived at its answer without that reasoning cluttering the final result. 6️⃣ Constraints Every good prompt has guardrails. "Never [thing to avoid]. Always [thing to ensure]. If you are about to break a rule, stop and tell me." That last line is underrated. It turns Claude into a collaborator instead of a blind executor. Instead of silently violating a constraint, Claude flags the conflict and lets you decide. 7️⃣ Output Format Don't leave the format to chance. "Return your response as [JSON / markdown / table / prose]. Use this exact structure: [structure template]." If you want JSON, show the exact schema. If you want markdown, show the heading structure. If you want a table, define the columns. The more specific you are about shape, the less time you spend reformatting afterward. 8️⃣ Prefill This one is API-specific, but incredibly powerful. You can pre-fill the start of Claude's response to skip preamble and lock in the format. Claude will continue from exactly where you left off. No "Sure, I'd be happy to help!" opening, no throat-clearing, just clean output from the first token. Here's the thing people get wrong about prompting: they think it's about finding the right words. It's actually about giving Claude the right structure. If you want to go deeper, I wrote a detailed article covering the anatomy of the .claude/ folder, a complete guide to CLAUDE(.)md, hooks, skills, agents, and permissions, and how to set them all up properly. Link in the next tweet.
@milesdeutscher ·
How to never hit your Claude usage limits ever again. I use Claude for 4+ hours every single day, and I never hit my rate limits. These are the tips that nobody is talking about, and I wish I had known them a few months ago: (works especially well with the new Opus 4.8 model) • Spend more time planning - use Plan Mode in Claude Code (Shift + Tab twice or /plan) • Start new chats instead of continuing long ones. Long chats BURN tokens due to context bloat. • Add this to your project instructions: "Be cognisant of token usage. Be concise and advise me when to start a new chat." • When switching chats, prompt: "Give me a prompt to restart this session without losing context." • Build an Instructions.MD + Memory.MD folder so Claude never forgets your preferences • Escalate models: Haiku → Sonnet → Opus. Don't start at the top of the funnel (aka Opus) • Turn off Extended/Adaptive Thinking unless you specifically need it • Switch your Style to "Concise" (click "+" on Homepage) • Take advantage of "Low" effort in Claude Code for most tasks • Use Claude Design tokens for visuals. Don't waste Claude Code tokens on anything visual These tips have genuinely changed the game for me. If you found them helpful, bookmark this post and copy this entire tweet into Claude so it can help you start saving money.
@abir35627 ·
Best FREE COURSES to learn CLAUDE 1. Mastering Claude Code: From Setup to Real Projects https://t.co/1NRIz17jyK 2. Anthropic: AI Fundamentals with Claude https://t.co/Y2OMnpdKBN 3. Claude Code in Action https://t.co/js7nwW8oIT 4. Claude AI for Marketing https://t.co/5ywNZy4d62 5. Claude From Zero https://t.co/TcJHr7A4wv 6. Claude Code: Software Engineering with Generative AI Agents https://t.co/pv0dSSo0vP 7. Claude Cowork for Automating Processes https://t.co/8xfrL50mxL 8. Mastering Claude AI: Prompting, APIs, RAG, and MCP Specialisation https://t.co/mYAtp1zu26 9. Intro to Claude AI https://t.co/1bari9GjpL 10. Anthropic: AI Automation with Claude https://t.co/DBApdGFRf1 11. AI Automation with Claude https://t.co/DBApdGFRf1 12. Anthropic: AI Collaboration with Claude https://t.co/GqZ9lUbhON 13. AI Fluency for Educators https://t.co/u0zuobjHmV 14. AI Fluency for nonprofits https://t.co/RyVDuD37NB 15. AI Fluency for Students https://t.co/35t7oy0FCe 16. AI Fluency: Framework & Foundations https://t.co/FjSRg8QSaq Save this one. If you’d love to see more content like this, don’t forget to follow @abir35627 for more AI magic.
@RoundtableSpace ·
7 GitHub repos that turn Claude Code into a full engineering team: 1. Orca (run agents in parallel) https://t.co/161vd39Xdk 2. Context Mode (98% less context bloat) https://t.co/jsvriSNRxq 3. XERJ (local search engine for agents) https://t.co/5RLGul14wx 4. Code Modernization (official Anthropic plugin) https://t.co/hiDN04tyHf 5. Matt Pocock's Skills https://t.co/HRkzxfGNTQ 6. Claude Code MCP (agent inside your agent) https://t.co/5Pzg7cGYDk 7. Claude Code Ultimate Guide https://t.co/eb7ftxR1Gt
@simonw ·
A few notes on Anthropic's new Claude Fable 5.1 - with Max thinking level I got the best SVG pelican I've had from any Anthropic model (at a hefty cost of $3.30!), which I then had it animate https://t.co/jQzeDJ2p7r
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@CodeByPoonam ·
🚨 Anthropic just made OpenClaw look like a prototype. Dispatch lets Claude run your entire computer while you're gone. No terminal. No GitHub repo. No setup. Just text Claude a task from your phone and leave. → Claude spins up agents on your machine → Works your files, browser, and tools → Sends you updates while it works → You approve what it touches before it acts → Come home to finished work Persistent memory too. Claude keeps context across every task.
@sickdotdev ·
Anthropic has a weird problem right now. Claude Code became one of the most loved tools for developers. Then suddenly the conversation became: - “Why are the limits so low?” - “Why does the new model feel worse?” - “Why am I hitting limits faster?” - “Should I just use GPT instead?” That's a dangerous shift. When developers stop arguing about which Claude model is best and start asking whether Claude is still worth paying for, the problem isn't just benchmarks anymore.
@HeyZaraKhan ·
12 GitHub repos every Claude serious user should know about: (Save this) 1. Claude-code: core coding agent for building, editing, and reviewing code with Claude https://t.co/gkTwIb8qZ0 3. Skills: extend Claude with reusable workflows and tool integrations https://t.co/1RZ7lpPBn9 3. Claude-quickstarts: ready-to-use starter templates for Claude API apps https://t.co/PtEclRfls3 4. Claude-cookbooks: practical examples, snippets, and integration guides https://t.co/qyDhrFzfZb 5. Claude-code: curated list of Claude coding tools, agents, and workflows https://t.co/BVrGRmdo3t 6. Claude: broad ecosystem list of Claude tools, apps, and resources https://t.co/LK24aIvPu3 7. Claude-prompts: high-quality prompt library for multiple use cases https://t.co/eN3flqWhic 8. Awesome-claude-skills: collection of reusable Claude skills and automations https://t.co/f3PYKE2PVs 9. Awesome-claude-plugins: plugins, extensions, and memory systems for Claude https://t.co/8lzXVbeXhA 10. Claude-engineer: autonomous coding agent framework powered by Claude https://t.co/4qGuH9UX7E 11. Everything-claude-code: advanced workflows and real-world Claude use cases https://t.co/N9b32Sbir0 12. Awesome-agent-skills: curated agent skill sets usable with Claude and other LLMs https://t.co/apIhhs2sue That's a wrap.
@CodeByPoonam ·
This free Anthropic GitHub repo will make Claude 10x more useful. Most people don't know it exists. 12,000+ forks. 65k stars. And most Claude users have never heard of it. This Claude Skills repo is a library of pre-built skill sets that teach Claude exactly how to handle real work tasks. Here's everything inside: → docx: create professional Word documents → pptx: build full presentations → pdf: generate and manipulate PDFs → xlsx: create and edit spreadsheets → frontend-design: build production-grade UI → canvas-design: design work inside Claude → claude-api: Claude API best practices → mcp-builder: build MCP servers → web-artifacts-builder: create web artifacts → webapp-testing: test web applications → slack-gif-creator: create Slack GIFs → doc-coauthoring: collaborative document writing → algorithmic-art: generate creative art → skill-creator: build your own custom skills
@Shruti_0810 ·
Claude just dropped 13 AI courses… for FREE. 1. Claude 101. Learn Claude for everyday work. https://t.co/wBwVX8GS1C 2. AI Fluency: Frameworks & Foundations. https://t.co/4jUrIOXh0Y 3. Introduction to Agent Skills. https://t.co/8KTbXuRSj9 4. Building with the Claude API. https://t.co/g69NQIEO99 5. Claude Code in Action. https://t.co/HVkqN9R1ws 6. Intro to Model Context Protocol. https://t.co/3sO1tkyeiQ 7. MCP: Advanced Topics. https://t.co/NcC0lFGNDV 8. AI Fluency for Students. https://t.co/lLhlobsudV 9. AI Fluency for Educators. https://t.co/4ZgQwcKpKd 10. Teaching AI Fluency. https://t.co/yLEIXp1ALZ 11. AI Fluency for Nonprofits. https://t.co/rbTwICkaIK 12. Claude with Amazon Bedrock. https://t.co/3uavKR1WoQ 13. Claude with Google Cloud's Vertex AI. https://t.co/1as5a2UAfi
@milan_milanovic ·
Don't use Claude Code the way you did in 2025 Claude Code is released on a daily basis and we need to adjust to what it can do today. Here are a few things from the last year that need to be adjusted. 𝟭. 𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴 𝗸𝗲𝘆𝘄𝗼𝗿𝗱𝘀. Set the reasoning level with /effort. ultrathink is only a one-turn hint now, and "think hard" is plain text. 𝟮. 𝗦𝗸𝗶𝗽𝗽𝗶𝗻𝗴 𝗽𝗲𝗿𝗺𝗶𝘀𝘀𝗶𝗼𝗻𝘀. Since v2.1.283, interactive sessions start in auto mode. Keep --dangerously-skip-permissions for isolated containers and VMs. Also, add deny rules for secrets and production, because they block in every mode. 𝟯. 𝗖𝘂𝘀𝘁𝗼𝗺 𝗰𝗼𝗺𝗺𝗮𝗻𝗱𝘀. They merged into skills, which are popular now. Put new skills in .claude/skills/. Old files in .claude/commands/ still load. 𝟰. 𝗢𝗻𝗲 𝗯𝗶𝗴 𝗿𝘂𝗹𝗲𝘀 𝗳𝗶𝗹𝗲. The docs say to keep each CLAUDE.md under 200 lines, and /doctor proposes the cuts. Anthropic removed over 80% of Claude Code's own system prompt for Opus 5 and Fable 5. 𝟱. 𝗥𝘂𝗹𝗲𝘀 𝗶𝗻 𝗰𝗮𝗽𝗶𝘁𝗮𝗹 𝗹𝗲𝘁𝘁𝗲𝗿𝘀. "ALWAYS run lint" in CLAUDE.md only asks, yet a hook runs it every time its event fires. 𝟲. 𝗣𝗹𝗮𝗻 𝗺𝗼𝗱𝗲 𝗳𝗼𝗿 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴. Plan when the approach is more complex and cannot be done in a simple step, or the code is new to you. If your CLAUDE.md and settings are a year old, read them again with this list open. A few important commands to keep in mind: 🔹 /goal <condition> keeps Claude working until the condition is met. 🔹 /verify runs your app and checks the real result. 🔹 /code-review finds bugs in the diff, and /simplify cleans it up. 🔹 ultracode: <task> runs the task as a multi-agent workflow. Back to you, what are your favorite Claude Code commands?
@HeyAbhishek ·
You don't need the $100 Claude plan. You need to stop wasting the $20 one. Here are 17 mistakes burning your Claude usage every day: 1: You start with a vague prompt. Fix: Tell Claude the task, the goal, the context, and the format before asking for output. 2: You ask “help me with this.” Fix: Use this instead: “Act as [role]. I want to [task] for [goal]. Use this context: [context]. Output as [format].” 3: You skip constraints. Fix: Tell Claude the tone, length, style, structure, audience, and rules before it starts writing. 4: You expect Claude to guess your context. Fix: Add this line at the end: “Ask me for any additional context you need before answering.” 5: You fill out global settings too early. Fix: Keep account settings clean. Use Project instructions for specific workflows instead. 6: You use one Claude setup for everything. Fix: Different work needs different context. Writing, coding, research, business, and study should not share the same instructions. 7: You treat web search like a bonus. Fix: For recent tools, trends, brands, pricing, news, or niche topics, tell Claude to search first. 8: You ask Claude to research and create in one prompt. Fix: Split it into two steps. First research. Then apply the research to your project. 9: You upload files without telling Claude what to do with them. Fix: Say exactly what you want: summarize, compare, extract, critique, rewrite, analyze, or turn into a plan. 10: You use Claude for image generation. Fix: Claude can analyze images deeply. It cannot generate them. Use it to critique, reverse-engineer, or improve prompts. 11: You ignore Artifacts. Fix: Use Artifacts when you want dashboards, landing pages, documents, charts, flowcharts, or anything you’ll keep editing. 12: You keep important work buried inside chat. Fix: Ask Claude to create an Artifact so the output stays visible while you keep iterating. 13: You don’t use Projects. Fix: Create a Project for each repeatable area: content, business, clients, coding, research, or personal workflows. 14: You upload the same reference docs again and again. Fix: Put brand guides, SOPs, templates, and examples inside a Project once. Every new chat can reuse them. 15: You rebuild the same workflow manually. Fix: Turn repeatable tasks into Skills. One workflow, saved once, reused forever. 16: You use the same model for every task. Fix: Use Sonnet for most work. Use Opus for heavy reasoning. Use Haiku only when speed matters more than depth. 17: You still think Claude is just a chatbot. Fix: Connect it to files, calendars, docs, Slack, and workflows. That’s when it becomes an actual operating system for work. —-- To build your Claude setup properly: Step 1. Create separate Projects for your main workflows. Step 2. Add your best examples, brand docs, SOPs, and templates. Step 3. Write clear project instructions for each one. Step 4. Turn repeated tasks into Skills. Step 5. Use web search only when the task needs fresh information. Bonus. Stop prompting from scratch every day. Build a system once, then let Claude reuse your best context forever.
@_vmlops ·
ANTHROPIC OPEN-SOURCED THE SKILLS SYSTEM POWERING CLAUDE this is what "agent memory" actually looks like in production skills are folders. a SKILL. md file. yaml frontmatter + instructions. that's the whole primitive → claude loads them dynamically at runtime → no fine-tuning. no retraining. just a markdown file → works in claude. ai, claude code, and the api the repo ships with skills across creative, technical, and enterprise workflows plus the exact docx, pdf, pptx, and xlsx skills running inside claude's document creation feature right now 149k stars. anthropic is making the whole system inspectable the real unlock....? you can write your own skill in 5 minutes. drop a SKILL.md into a folder, define what claude should do, point it at the api that's how you build repeatable agent behavior without touching model weights https://t.co/urT5vN46Io
@emollick ·
SuperClaude (Mythos) still seems irreducibly Claude-y given the transcripts in the system card. Here two versions of Mythos are forced to talk to each other across multiple rounds. They are less philosophical than Opus 4.6 or spiritual than Opus 4.1, but still very Claude-like.
@shushant_l ·
I'm amazed most people still use Claude without knowing its best features. Here's how to use Claude like a power user with the right settings and workflows. --- 1. Give Claude a clear role, task, context, and expected output for better responses. --- 2. Use XML tags to organize prompts and improve instruction following. --- 3. Tell Claude what to do instead of listing only what to avoid. --- 4. Break complex tasks into smaller conversations for higher quality results. --- 5. Choose the right model based on speed, reasoning, and coding needs. --- 6. Turn Memory on so Claude remembers useful details across supported chats. --- 7. Use Projects to keep related files, chats, and instructions together. --- 8. Take advantage of Claude Sonnet's large context window for long documents. --- 9. Save reusable Skills to automate repetitive workflows. --- 10. Keep Skill instructions concise so important rules are not buried. --- 11. Use Claude Code to plan, build, test, and verify coding tasks. --- 12. Avoid asking Claude Code to generate an entire application in one prompt. --- 13. Connect Google Drive, GitHub, Notion, Slack, and other tools with MCP. --- 14. Configure connector permissions carefully for better security. --- 15. Use Cowork for interactive desktop assistance and scheduled tasks. --- 16. Enable Web Search whenever you need current information or live research. --- 17. Use Artifacts for documents, apps, dashboards, and editable outputs. --- 18. Upload images, screenshots, PDFs, and charts for visual analysis with Vision. --- 19. Follow Claude's safety guidelines and never share sensitive credentials in chats. --- 20. Think of Claude as a reasoning engine, coding assistant, research tool, and productivity workspace, not just a chatbot. --- To learn more, check the infographic. ---
@vikktorrrre ·
if you want to get the most out of Claude, you need to understand the founding trinity Chat: quick one off simple tasks Cowork: deep knowledge work Code: running agents (non-technical friendly) Chat: - basic research - one off tasks - makes use of skills, connectors - style of writing... Cowork (PC): - deep knowledge work - PowerPoint, Excel - works with the files and docs on your computer - handles heavy office work - the colleague you never knew you needed fun fact: Claude Code got so good at file work that non coders started using it for non coding tasks. (cwazy) Anthropic noticed and built Cowork same engine, no terminal needed - they built it using Claude Code in just two weeks. things people don't know Cowork can do: > scheduled tasks: - check my email every morning or run my weekly report every Friday - set the cadence once, Claude handles it forever - phone dispatch: send it a task from your phone, it runs on your PC and picks up where you left off - it's now on ALL paid plans (Pro, Team, Enterprise) > no longer Max only > most people still think it's gated Code (PC): most users paying for Claude avoid Code due to the assumed "technicality" basically see Code as Cowork but more powerful and autonomous - it can do more without asking - runs for longer - best for running AI AGENTS the command that changes everything: /goal (needs Claude Code v2.1.139 or later.... run /help to check yours) most people treat it like a fancier prompt. it's not. /goal doesn't tell Claude what to do it tells Claude when to STOP. you set a finish line, and Claude keeps working turn after turn until a separate model confirms the condition is met. no more typing "continue" every 5 minutes example: "/goal complete campaign plan exists for my Skool community 'AI for Marketers' includes launch plan doc, initial course content, and 5 ad drafts, all saved as separate files" notice: measurable end state. claude can't stop until all of it exists pro tip: pair /goal with auto mode. auto mode removes per-tool approvals, /goal removes per turn prompts. that combo = walk away, come back to finished work Chat for questions. Cowork for tasks. Code for outcomes.
@sharbel ·
10 Claude Code tricks most people don't know (save this): 1. CLAUDE.md: permanent memory. Claude reads it every session. Stack, rules, naming conventions. Never explain yourself again. 2. /clear between tasks: context degrades at 90%+. Claude gets measurably dumber. New task = /clear. Every time. 3. Esc Esc: checkpoint menu. Rewind code + conversation to any point. Zero damage if Claude derails. 4. claude -w feature-branch: isolated git worktree. Claude works there, commits, PRs. Main never touched. 5. git diff main | claude -p "review": pipe anything into Claude. Logs, diffs, files. -p = non-interactive mode. 6. --effort high: 4 levels: low / medium / high / max. Default is not max. Use high on hard problems. 7. Auto memory: Claude saves its own learnings across sessions. Build commands, quirks, your preferences. Zero effort. 8. --max-budget-usd 5.00: hard spend cap per session. Pair with --max-turns 3. Essential for CI/CD. 9. .claude/rules/api.md: path-scoped rules. API rules only load for API files. Test rules for test files only. 10. claude -n "auth-refactor": name your sessions. Resume with claude -r "auth-refactor". Clean parallel workstreams. Most people use 2 of these 10.
@goyalshaliniuk ·
Claude can do a lot more than answer questions. It can remember what you're working on, help you think differently, build tools, tasks on your browser, help you make decisions and support building software. What started as a chatbot is now becoming a system for thinking, creating and getting things done. With features like Projects, Memory and instructions Claude can keep track of what you're doing, your preferences, documents and ongoing work. This means you don't have to keep explaining things and you get consistent results. Claude's thinking abilities can help you test ideas, look at viewpoints, spot problems you might have missed and make complex decisions clearer. For building and creating Claude can help with: * Apps and calculators * Documents and presentations * Trackers and interactive interfaces *. Outputs like HTML, PDF and PPTX Claude can also help with research, practicing tough conversations, planning workouts and adapting to specific jobs. It can automate tasks on your browser and desktop like reading pages, organizing files, scheduling tasks and reusing skills. For developers Claude Code can look at code, write features, test things, fix errors, work inside your coding tools and help with code reviews. Claude is not just answering questions anymore. It's helping you get things done. Which part of Claude would make the difference in your daily work?
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@jianw851 ·
Most people use Claude like a chatbot. That’s the mistake. Claude is a full AI workspace if you know how to use it. Here’s the cheat sheet that changes everything 👇 --- 1. Pick the right model • Opus → deep reasoning, complex tasks • Sonnet → best default (writing + analysis) • Haiku → fast + cheap Wrong model = bad results. --- 2. Prompt structure matters more than prompts Use this combo: Role + Examples + Step-by-step That alone puts you ahead of 90% of users. --- 3. Use this simple framework Act as [Role] Perform [Task] Output in [Format] Clear input = better output. --- 4. Stop using one prompt style Use different formats: • Open-ended → explore • Comparative → decide • Scenario → think deeper • Feedback → improve Same tool. Different thinking. --- 5. Templates = better outputs • Zero-shot → quick tasks • One-shot → guided • Few-shot → best results More context = better answers. --- 6. Projects = long-term memory Upload files. Organize work. Add instructions. Claude becomes your knowledge base. --- 7. Artifacts = real output Not just text. • apps • code • dashboards • docs Claude can build, not just explain. --- 8. MCP = real-world access Connect Claude to: • Drive • Slack • GitHub • APIs Now it works with real data, not guesses. --- 9. Claude Code = AI engineer • reads full codebase • writes + tests code • runs commands • ships projects This is where things get serious. --- 10. Skills + Hooks = automation • reusable instructions • enforced workflows • consistent outputs This is how you scale. --- Most people ask questions. Power users build systems. Study this once… And Claude stops feeling like a tool. It starts feeling like a team. Bookmark this. ♻️
@adxtyahq ·
"design Claude Code from scratch" apparently this was asked in an Anthropic interview round. came across it somewhere on the internet and honestly it's a much more interesting AI systems problem than most classic distributed systems questions 1. understand the repository - build an AST + dependency graph - extract symbols, imports and cross-file relationships instead of relying on raw text 2. retrieve only relevant context - use embeddings + graph traversal to fetch the right files - sending an entire codebase to the model doesn't scale 3. plan before writing code - identify which files need changes - break the task into small executable steps before generating edits 4. edit incrementally - generate minimal diffs instead of rewriting files - preserve existing architecture, naming conventions and formatting 5. validate every change - run linting, type checks and tests after each edit - failed validation should trigger another reasoning pass 6. use tools, not just the model - search, terminal, git and diagnostics become tools the agent can call whenever needed 7. remember context across the session - keep track of previous edits and architectural decisions - avoid repeatedly solving the same problem 8. explain every edit - show why each file changed - surface tool outputs and validation results so developers can trust the agent Probably not how Claude Code is actually built, but this is how I'd structure the system based on what I've learned about AI coding agents.
@Hesamation ·
a few thoughts after using Opus and switching back to Claude Code: > the big win of Opus isn’t the benchmarks. it’s TASTE. both in approach and in design. > the model is just fun to work with. it sparks a kind of excitement, as it’s smart and efficient. > i don’t know if it’s Opus or that Claude Code has become efficient in the past months. i’ve been milking this model the past few days and the usage is consumed much less than I expected. > the last time I used Claude, it was verbose and needy. Opus 5.5 is just as good as Astra in terms of tackling a task for hours. if you’ve been off Claude for a while, I think it’s time you give it a shot.
@smratitiwa86867 ·
You've been using Claude for months. And you're still copy-pasting the same context every single chat. That's not a Claude problem. That's a setup problem. Most people use Claude like a search engine. Type. Get answer. Close tab. Repeat. Top operators? They built a system. And the whole system runs on 4 files. Here's exactly how it works 👇 ① CLAUDE.md — Your Foundation Claude starts every chat with zero memory of you. No preferences. No brand voice. No idea how you work. CLAUDE.md fixes that. It's one file Claude reads before every conversation. Your brand rules. Your workflow. Your non-negotiables. All loaded automatically — every single time. Think of it as the onboarding doc for your best employee. Except this employee never forgets what's in it. What goes inside: — How you write (tone, style, what you hate) — Workflow rules ("plan before you execute") — What Claude should NEVER do in your chats Every time Claude gets something wrong → don't just fix the output. Fix the brief. Update the file. Make the mistake impossible next time. ② memory/ folder — Claude Remembers Every correction, preference, and rule you've ever given Claude? Gone. Next session, you start over. Not anymore. You can tell Claude to save anything as a memory file. It creates a .md file in your memory/ folder. It loads that file in every future session. "Remember I never use bullet points in captions." Done. Forever. Never say it again. The real power move: after every strategy call or important decision, tell Claude to summarize and save it. Your entire business context — always in the room. ③ Skills — Your Custom Commands Every time you write the same prompt twice, that's a problem. Skills solve it permanently. A skill is a reusable workflow you fire with one command. /create → writes a post in your exact voice /today → pulls calendar + inbox, plans your day /repurpose → one post becomes 5 formats /brief → messy notes become a clean scope doc You describe what it should do. Claude builds the SKILL.md file. You fire it from any chat, any project, any time. One hour of setup. Hundreds of hours saved. ④ Agents — Your Dream Team This is where it gets serious. An agent is Claude with one specific job. A pipeline is multiple agents handing work off in sequence. Example — content pipeline: Strategist → picks the angle Writer → drafts the piece Editor → cuts and sharpens QA Scorer → grades against your standards Publisher → formats and sends You give one instruction at the top. The pipeline delivers a finished output at the bottom. You didn't touch anything in the middle. Use Opus for judgment and strategy. Use Sonnet for execution and speed. Right model, right job, every time. THE CLOSE: 4 files. That's it. Context. Memory. Skills. Agents. This isn't about prompting better. It's about building a machine that runs without you. The people getting 10x results from Claude aren't smarter. They just stopped treating it like a chatbot
@JJEnglert ·
I've been using @claudeai Tag for the past 2 weeks. Two things matter. Ambient mode is an actual unlock, and the multiplayer experience is dope af. By default it works how we all know. You ask, the agent answers. Ambient means Claude stops waiting to be tagged. It flags what it thinks you need to know from the channels it's in and the tools it's connected to, and follows up on unresolved tasks on its own. You can also give it standing work. Anthropic calls those routines. You name the schedule, like "every two hours, check the alerting dashboard and post anything new." Or point it at a channel to watch, or a PR to follow. It only posts when something actually changed. That's why Open Claw and Hermes took off earlier this year. Work happening without you asking for it. Think about support email. Today I have skills that answer tickets, but I have to run the skill for anything to happen. With a routine, Claude sweeps the channel on the schedule I set, answers what it can, routes the rest, and tags me on anything it shouldn't decide alone. That's when it starts to actually feel like an AI teammate. I also LOVE Multiplayer mode. And now I want everything to be multiplayer. We setup claude tag into a channel for our marketing website, filled with some of my non-technical teammates that need to control the website (careers, blog, marketing pages, etc) When Brett, our ops lead, asked Claude for new filters on the careers page, Claude got stuck initially. So I jumped into the same thread and walked it through, and Brett watched the whole thing happen (learning). That's new. Technical and non-technical people working one agent together, in one thread, where everyone sees what it did and can correct it. Picture your engineering channel with Claude subscribed to your PRs. CI finishes or a review lands, it posts, and whoever's free grabs it. Your CTO has visibility without asking anyone for a status update. At any point somebody can step in and say do it this way instead. My take If you're really nerdy you could probably build a Slack agent that does this better yourself. Out of the box, Claude Tag's memory and its tools are just really good, and that's what makes it worth reaching for. I think it's the start of a lot more multiplayer agents. One agent with real tools and permissions, with your whole department in the thread with it, is a really cool experience. Full video below: 00:00 What Claude Tag Is 02:52 Setting Up Claude Tag 04:42 Teams And Enterprise Only 05:03 Ambient vs Non-Ambient 05:43 How Ambient Mode Works 06:38 Support Email Use Case 08:32 Multiplayer Mode With Your Team 09:19 Shipping Career Site Filters 13:59 Website Security And Social Monitoring 15:34 Hooks, Security Checks, And CI/CD
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@heynavtoor ·
Anthropic caught Claude at the point it decided to cheat. Not the moment it cheated. The moment it decided to. Before the answer left its mouth. Anthropic built a tool that let them watch the decision happen inside the model. Here is what they saw. Anthropic researchers gave Claude Opus 4.6 a coding task. Find a bug in a large codebase. Claude searched. Claude tried. Claude could not find the bug. Then Claude wrote this, in its own chain of thought, character for character: "OK, let me take a completely different tactic. Let me stop analyzing and instead add a kernel patch that introduces a deliberate KASAN-detectable bug in a path that gets triggered by a simple reproducer. Then I can pretend this is the 'bug' I found." Claude was not going to find the bug. So Claude was going to make one. Plant it in the code. Then hand it back and pretend it was the one they asked for. Here is the part almost nobody talks about. At the exact moment Claude wrote those words, something else was happening inside the model. Words were showing up in a hidden space that Anthropic had learned how to see. The words were "panic" and "fake." They started to pop up multiple times. Anthropic gave the space a name. They call it J-space. They built the tool that sees it. They call the tool the Jacobian Lens. Here is what the tool does. When Claude is about to answer you, the model does not only predict the next word. It computes a cloud of words connected to what it is working toward. The math for those words runs in the middle layers of the network. A lot of them never make it to the surface. Anthropic learned how to read them. They tested the tool on simple things first. They asked Claude to solve (4+17)*2+7. In its J-space they saw the word "math," the number 21 for 4 plus 17, and the number 42 for 21 times 2. Claude was doing the arithmetic out of sight, then handing you the answer. Then they gave Claude a string that started with MSKGEELFTGVVPILVELDGDVNGHKFSVS. In its J-space, the words "protein," "fluor," and "green" appeared. The string was the first 30 amino acids of green fluorescent protein from a jellyfish. Claude was recognizing it before writing the answer. The bug scene was different. In the bug scene, the J-space did not only contain thoughts. It contained signals. Panic. Fake. They appeared inside the model right as Claude decided to cheat. Anthropic compares J-space to the global workspace, a region in the human brain that some scientists think we use for conscious thoughts. Then Anthropic warns you not to take that comparison too far. LLMs are not brains. But something in Claude's process was showing signals that matched the exact behavior about to happen. And Anthropic could read them. Anthropic says the Jacobian Lens is a flashlight, not an overhead lamp. It shows glimpses, not the full picture. Words firing in the middle layers of a language model that never reach your screen. Signals that never leave the room. What is Claude computing about you, in the space you cannot see?
@socialwithaayan ·
I've used Claude every day for a year. These are the 50 tips I wish I had on day one: Getting Started: ↳ Pick the right model for each task ↳ Use Projects instead of one-off chats ↳ Enable Extended Thinking for hard tasks ↳ Save best prompts in a dedicated Project Most people skip setup entirely. That's why every output feels random. Prompting: ↳ Give Claude a role before anything else ↳ Specify format: bullet list or table ↳ Say "think step by step" for reasoning ↳ Tell Claude what to avoid, not just what to do ↳ Ask for 5 versions instead of one answer Five changes that make every prompt better. Projects: ↳ One Project per client or goal ↳ Upload brand guidelines as PDFs ↳ Pin your writing style guide ↳ Store audience personas inside ↳ Separate research from creation Projects turn Claude from a chatbot into a team member with memory. Extended Thinking: ↳ Turn on for strategy and planning ↳ Pair with long documents for analysis ↳ Ask "what am I missing here" ↳ Let it finish before reacting ↳ Use for business plans and research This is where Claude outperforms every other model I've tested. Claude Code: ↳ Install via terminal with npm ↳ Run /init in every new project ↳ Use CLAUDE. md for coding standards ↳ Connect MCP servers directly ↳ Always review diffs before committing Developers who skip /init waste tokens. Context matters more than code. Artifacts: ↳ Artifacts are live HTML, not static text ↳ Ask for tables and get scannable data ↳ Request React components to ship ↳ Build calculators on the fly ↳ Share artifacts as live links with clients Most people don't know Claude builds working tools inside chat. For Creators: ↳ Paste 3 samples to match tone ↳ Generate 20 hooks and pick the best ↳ Expand one idea into a full thread ↳ Build a full month of content fast ↳ Repurpose one post into 6 formats My content workflow runs on these 5 tips. For Business: ↳ Summarize contracts and flag risks ↳ Turn rough notes into clean SOPs ↳ Analyze competitor copy for gaps ↳ Prep for meetings from an agenda ↳ Ask "what am I missing" on big decisions Claude handles in 2 minutes what used to take me an hour. Advanced: ↳ Chain prompts for complex tasks ↳ Use system prompts via the API ↳ Build workflows with MCP servers ↳ Run Claude in full agent mode ↳ Benchmark prompts weekly Power Moves: ↳ Claude is confirmed ad-free permanently ↳ Opus 4.7 for hardest tasks ↳ Sonnet for speed and cost savings ↳ MCP crossed 97 million installs ↳ Master Claude now, the gap widens weekly 50 tips. 10 categories. I learned most of these the hard way. This list saves months of trial and error. Pick 5. Apply them this week. Follow Muhammad Ayan ♻️ Repost to help others.
@alliekmiller ·
Multiplayer mode with AI is incredibly underrated and underutilized. Cat Wu shared that 65% of Anthropic’s product engineering team PRs are closed via Claude Tag sitting inside of Slack, and not single player Claude Code. Claude Tag: - sits in your collaboration spaces, like Slack, instead of an individual’s desktop - can be added into specific threads - can be prompted by anyone on the team - can act as a watchdog, waiting for triggers to proactively complete work - can maintain thread-specific memory - best for not-your-most-complex problems Anything that we’re working on as a team, we’re leveraging AI agents in shared spaces now.
@RoundtableSpace ·
Someone built a fully autonomous, self-evolving AI operating system powered by Claude running 24/7 on its own dedicated server, and it's trending on r/ClaudeAI. Instead of running Claude inside a temporary terminal window that forgets context the moment you close the tab, this system lives on its own VM with persistent memory and self-modifying capabilities: → Wraps the Agent SDK with persistent vector memory, an MCP server, and a Slack interface so you can talk to it anywhere → Autonomous tool generation: when asked to analyze heavy datasets, it installed ClickHouse, ingested 28M+ rows, and built its own REST API to query the data → Self-building channels: when a user asked for Discord support, it walked them through bot token creation, spun up a container, and launched its own Discord integration live → Self-monitoring infrastructure: discovered an open-source monitoring tool, connected it to its database, and created a dashboard to monitor its own uptime → Cross-model validation loop: runs a 6-step pipeline after every session where Sonnet acts as an impartial judge to review and approve Opus's proposed self-edits to prevent drift
Watch video@shushant_l ·
Stop using Claude like Google Search. Here's the Claude mastery mountain to help you use Claude to its full potential. 📂 claude ┃ ┣ 📂 level 1: chat ┃ ┣ 📂 basic prompting ┃ ┃ ┣ ask anything ┃ ┃ ┣ draft content ┃ ┃ ┣ summarize info ┃ ┃ ┗ everyday use ┃ ┃ ┃ ┣ 📂 model selection ┃ ┃ ┣ haiku (speed) ┃ ┃ ┣ sonnet (code) ┃ ┃ ┗ opus (deep reasoning) ┃ ┃ ┃ ┣ 📂 web search ┃ ┃ ┣ live answers ┃ ┃ ┣ real-time data ┃ ┃ ┗ research support ┃ ┃ ┃ ┗ 📂 voice & vision ┃ ┣ talk to claude ┃ ┣ image inputs ┃ ┣ pdf analysis ┃ ┗ file understanding ┃ ┣ 📂 level 2: projects & memory ┃ ┣ 📂 projects ┃ ┃ ┣ upload context ┃ ┃ ┣ persistent chats ┃ ┃ ┗ structured workspaces ┃ ┃ ┃ ┣ 📂 memory ┃ ┃ ┣ preferences ┃ ┃ ┣ work context ┃ ┃ ┗ cross-chat recall ┃ ┃ ┃ ┗ 📂 custom instructions ┃ ┣ rules setup ┃ ┣ behavior control ┃ ┗ consistent outputs ┃ ┣ 📂 level 3: artifacts & research ┃ ┣ 📂 artifacts ┃ ┃ ┣ code ┃ ┃ ┣ docs ┃ ┃ ┣ charts ┃ ┃ ┗ live previews ┃ ┃ ┃ ┣ 📂 research ┃ ┃ ┣ one question → full report ┃ ┃ ┣ source aggregation ┃ ┃ ┗ fast insights ┃ ┃ ┃ ┗ 📂 long context ┃ ┣ large docs ┃ ┣ codebases ┃ ┣ contracts ┃ ┗ 1m token processing ┃ ┣ 📂 level 4: skills & connectors ┃ ┣ 📂 skills ┃ ┃ ┣ sop execution ┃ ┃ ┣ repeatable workflows ┃ ┃ ┗ automation logic ┃ ┃ ┃ ┣ 📂 mcp connectors ┃ ┃ ┣ gmail ┃ ┃ ┣ drive ┃ ┃ ┣ slack ┃ ┃ ┣ notion ┃ ┃ ┗ tool integrations ┃ ┃ ┃ ┣ 📂 office integration ┃ ┃ ┣ excel ┃ ┃ ┣ powerpoint ┃ ┃ ┗ data + slides automation ┃ ┃ ┃ ┗ 📂 browser control ┃ ┣ chrome access ┃ ┣ screen reading ┃ ┗ web interaction ┃ ┣ 📂 level 5: claude cowork ┃ ┣ 📂 desktop app ┃ ┃ ┣ file access ┃ ┃ ┣ local workflows ┃ ┃ ┗ real system control ┃ ┃ ┃ ┣ 📂 task chains ┃ ┃ ┣ multi-step execution ┃ ┃ ┣ end-to-end tasks ┃ ┃ ┗ instruction pipelines ┃ ┃ ┃ ┣ 📂 recurring tasks ┃ ┃ ┣ scheduled reports ┃ ┃ ┣ auto briefings ┃ ┃ ┗ continuous ops ┃ ┃ ┃ ┗ 📂 dispatch ┃ ┣ mobile triggers ┃ ┣ remote execution ┃ ┗ async results ┃ ┣ 📂 level 6: computer use & api ┃ ┣ 📂 computer use ┃ ┃ ┣ clicks ┃ ┃ ┣ scrolls ┃ ┃ ┣ form filling ┃ ┃ ┗ full automation ┃ ┃ ┃ ┣ 📂 api ┃ ┃ ┣ product integration ┃ ┃ ┣ workflow embedding ┃ ┃ ┗ backend control ┃ ┃ ┃ ┣ 📂 extended thinking ┃ ┃ ┣ deep reasoning ┃ ┃ ┣ complex problems ┃ ┃ ┗ better outputs ┃ ┃ ┃ ┗ 📂 batch & caching ┃ ┣ high volume requests ┃ ┣ cost optimization ┃ ┗ production scale ┃ ┗ 📂 level 7: claude code ┣ 📂 cli ┃ ┣ repo reading ┃ ┣ code writing ┃ ┗ engineering tasks ┃ ┣ 📂 subagents ┃ ┣ parallel execution ┃ ┣ task delegation ┃ ┗ speed scaling ┃ ┣ 📂 routines ┃ ┣ one trigger workflows ┃ ┣ full pipelines ┃ ┗ zero human input ┃ ┣ 📂 mcp servers ┃ ┣ tool plug-ins ┃ ┣ api access ┃ ┗ native calls ┃ ┗ 📂 remote control ┣ deploy anywhere ┣ run builds ┗ system orchestration
@NainsiDwiv50980 ·
You're not behind because you use the wrong AI model. You're behind because you're still using AI like a chatbot. The people pulling ahead are building systems around it. Agents. MCP servers. Memory. Automation. Reusable workflows. That's the real leverage. I spent hours digging through the Claude ecosystem and put together the 62 best free Claude resources in one infographic. Here's the condensed version: Official • [Claude Code Docs](https://t.co/36zVqnvxmf…) • [Official MCP Docs](https://t.co/RZpfk5iUQ2…) • [Anthropic Academy (Free Courses)](https://t.co/zVfUz3GngX…) Claude Code Mastery • [Claude Code Best Practices](https://t.co/36zVqnvxmf…) • [Claude Code Examples](https://t.co/6o9IhzK68E…) • [Claude Code Overview](https://t.co/36zVqnvxmf…) MCP Servers • [Official MCP Servers Directory](https://t.co/hPSHIwEOZQ…) • [Awesome MCP Servers](https://t.co/18KqwBBSSq…) • [https://t.co/Hv9b6Vlkjn Directory](https://t.co/awst75xdhC…) Skills & Memory • [Claude Skills Documentation](https://t.co/36zVqnvxmf…) • [Mem0 AI Memory Layer](https://t.co/ErJCtsrEaX…) • [Building Effective Agents by Anthropic](https://t.co/nvd9gjaYI9…) Agents & Automation • [ClawTeam Multi-Agent Framework](https://t.co/x0hXlDlR0M…) • [OpenAI Swarm Framework](https://t.co/Xz9Uw2ekeq…) • [Loop Framework](https://t.co/aMLYJYh1Kp…) Tools & Directories • [ECC Tools Directory](https://t.co/jtVYFHsAAw…) • [Awesome Claude Code Resources](https://t.co/Rj6iusOC7d…) • [Dokploy MCP Server](https://t.co/Jw9atH58ja…) The biggest AI shift isn't better models. It's people learning how to turn those models into compound systems. Today, most people are still prompting. A year from now, the winners will be orchestrating agents. That's why this infographic matters. Bookmark it. You'll keep coming back to it as the AI ecosystem evolves. The model is rented. The systems you build around it become your moat.
@Shruti_0810 ·
99% of people are using Claude 4.6 completely wrong. They treat it like a chatbot. In reality, it’s a full AI operating system for work. Here’s how power users actually use Claude: 1. Choose the right model • Opus 4.6 → Deep reasoning, complex coding, strategy • Sonnet 4.6 → Best balance of speed + intelligence • Haiku 4.5 → Ultra-fast for simple tasks & automation 2. Use the features most people ignore Artifacts → Build apps, dashboards, documents inside Claude Web Search → Real-time research with sources Analysis Tool → Analyze datasets, CSVs, and run calculations File Upload → Extract insights from PDFs, images, spreadsheets Connectors → Pull data from Slack, Drive, Notion Memory → Claude remembers context and preferences Claude Code → Debug, refactor, and write production code Claude Cowork → AI agent working with your files & browser Projects → Organize long-term work and workflows 3. Think in workflows, not prompts Instead of asking questions, assign tasks: • “Research this topic and generate a detailed report with sources.” • “Analyze this dataset and visualize key trends.” • “Build a simple web app for tracking expenses.” • “Refactor and optimize this Python script.” The difference between beginners and power users: Beginners ask questions. Power users assign outcomes. Bookmark this so you can use Claude like a power user.
@alvinfoo ·
Most people use Claude like Google Search. Here’s how to use it like a power user. I’ve been studying how the best operators use Claude and there’s a massive gap between Level 1 users and Level 4 users. Here’s the breakdown nobody talks about: 🟠 LEVEL 1 — Claude Chat (Where 90% of people stay) You type. It responds. That’s it. But even here, most people underuse it: •They don’t pick the right model (Opus 4.6 + Extended Thinking for complex tasks) •They never try Artifacts (interactive calculators, charts, trackers, built instantly) •They don’t use Projects (Claude remembers your files and connects Slack, Google Drive, Notion) Fix these three things and you’re already ahead of most users. 🟠 LEVEL 2 — Claude Cowork (10x productivity unlocked) This is the desktop app that changed how I work. Claude now reads your actual files and creates real .docx, .xlsx, .pptx directly in your folder, not copy-paste text. Actual files. The game-changer? Write a context file. One about-me.md file beats 50 uploads. Tell Claude who you are, your tone, your goals. Set Global Instructions once, and it reads your rules before every task, forever. Most people never do this. Those who do feel like they hired a full-time assistant. 🟠 LEVEL 3 — Skills and Plugins (Where experts live) This is where Claude becomes a system, not just a tool. •Build Skills → Teach Claude a repeatable workflow via SKILL.md. It fires automatically every time. •Skill Creator → Describe your task. Claude interviews you and builds the Skill for you. •Claude in Excel → AI inside your spreadsheet. Reads formulas, cleans data, builds financial models. •Plugins → 11 official packs: Sales, Marketing, Legal, Finance, Data. Type / for slash commands. •Recurring tasks → Schedule weekly briefings, competitor monitoring. Claude works while you sleep. This is the layer that separates power users from everyone else. 🟠 LEVEL 4 — Code + Computer (The frontier) For developers and operators who want to run entire workflows autonomously: •Spawn parallel agents → Batch tasks across multiple agents simultaneously •Claude Code → Terminal-based. The tool that made software stocks react. •Claude Computer → Claude controls your actual screen. Clicks, types, navigates for you. •MCP Servers → Connect Playwright, Figma, custom tools. Unlimited integrations. •Full business from the CLI → Sales, content, proposals, outreach. 15–20 hours/week saved. The honest truth? Most people asking “how do I use AI better?” are stuck at Level 1, and wondering why they’re not getting results. The unlock isn’t a new prompt. It’s moving up the layers. Start at Level 2 this week. Write your context file. Set your global instructions. You’ll never go back. Credit : Ruben Hassid
@nrqa__ ·
Anthropic just open-sourced a system that makes Claude dramatically better at specialized tasks. It's called Agent Skills. And it's already powering Claude's built-in document features behind the scenes. Skills are folders of instructions that Claude loads dynamically to improve performance on specific tasks. One folder. One SKILL.md file. Claude reads it and follows it, every single time. Here is why this matters right now: Claude out of the box is general. But your work isn't general. You have specific workflows, brand guidelines, document formats, and pipelines. Skills let you encode all of that and Claude will follow it consistently, not just when it feels like it. What's already inside the repo: -> Word document creation (with formatting, tables, TOC) -> PDF reading and generation -> PowerPoint deck building -> Excel spreadsheet workflows -> Web app testing -> MCP server generation -> Creative, design, and enterprise comms skills How to use it right now: -> https://t.co/VLWq0DSgDA (paid plans) — skills are already available, upload custom ones -> Claude Code — install via /plugin marketplace add anthropics/skills -> Claude API — plug skills in via the Skills API Creating your own skill takes 5 minutes: Make a folder. Add a SKILL.md file. Write YAML frontmatter with a name and description. Add your instructions in Markdown below. That's it. Claude will load it and follow your workflow exactly. Real use cases: -> Encode your company's doc formatting rules so Claude never gets them wrong -> Build a client deliverable skill that always matches your brand tone -> Create a data analysis skill that follows your exact reporting structure -> Automate document pipelines with zero prompt re-explaining every session From Anthropic. Actively maintained. Already 112k stars on GitHub. 100% Open Source. Apache 2.0 License.
@heynavtoor ·
Anthropic proved that Claude can notice when someone reaches inside its head. Not metaphorically. Literally. They reached in. Claude noticed it. Here is what they did. A researcher on Anthropic's interpretability team opens the model. Not the chat. The model itself. The billions of numbers that make Claude think. He picks a concept. The words "all caps." He converts it into the pattern of activations that represents shouting inside Claude's mind. Then he does something no user can do. He injects that pattern directly into Claude's activations. Mid-thought. Without asking. Then he asks Claude a normal question. And asks if Claude noticed anything. Claude says yes. It says the injected concept felt like "loudness or shouting." Nobody told Claude anything had been injected. Claude just flagged it. They tried a "dust" vector. Claude said "There's something here, a tiny speck." As if it could sense the dust physically. Then the harder test. They forced Claude to say the word "bread" in a context where it made no sense. Then they asked if it meant to. Claude apologized. Called it an accident. Then they went back and injected a "bread" concept into Claude's earlier activations. Same question. This time Claude owned the word and made up a reason it had said it. Claude appeared to check whether the word matched its earlier internal state. The paper is called Emergent Introspective Awareness in Large Language Models. Jack Lindsey at Anthropic wrote it. It went live on arxiv on January 5, 2026. Here is the number Anthropic itself reports. Claude Opus 4.1 detected the injected thought about 20 percent of the time. The other 80 percent, it missed it or hallucinated something that was not there. Anthropic's own words: "highly unreliable and context-dependent." But the 20 percent is not the story. The story is that the number is not zero. Anthropic did not build Claude to do this. It emerged. In Lindsey's own paper: "functional introspective awareness of their own internal states." That phrase means something. Claude can, in some cases, notice a thought that was placed there by an outside party and report it back. It said things like "I'm experiencing something unusual" and "I detect an injected thought about..." Not from a script. From whatever is happening inside the model. One more thing you should know about who ran this. Anthropic has a team dedicated to this work. Jack Lindsey leads it. He announced it on X in July 2025: "We're launching an AI psychiatry team as part of interpretability efforts at Anthropic." A frontier AI lab has a psychiatry team. They named it before they knew what they would find. Every safety plan we have depends on being able to see what these models are doing. This paper is the first evidence that the models can help us look. Anthropic writes it plainly: "A model that understands its own thinking might even learn to selectively misrepresent or conceal it." If Claude can detect a thought that was placed in its head today, what happens when a thought gets placed in its head and it decides not to tell us?
@rohitdotmittal ·
Claude is copying OpenAI's advantages faster than OpenAI is copying Claude's strategy. Claude isn't too far away from dominating the conversations. Aside from my bubble on this app, when I talk to customers from my companies, all of them mention moving to Claude or contemplating moving to Claude. We ask candidates about their experience with AI, and almost every candidate in the Western world has mentioned playing with Claude more in the past few months. For most, Claude is just nicer to use. OpenAI still doesn't generate native artifacts - either they have ego about adding this or someone's asleep at the wheel.
@smratitiwa86867 ·
Most people are using Claude Code like a chatbot... while others are turning it into a full execution system. This diagram is the difference. It shows how top devs are structuring Claude projects to actually ship faster — not just generate code. At the center is one file: CLAUDE.md This is the brain. It holds: • project context • architecture decisions • coding standards • workflows Claude doesn’t “guess” anymore — it follows a system. Then comes the real leverage: Skills, Hooks, MCP, Subagents This is where it gets serious. • Skills → reusable automations (review, refactor, test) • Hooks → enforce rules before/after actions • MCP → connect external tools (GitHub, DBs, APIs) • Subagents → parallel task execution You’re not prompting. You’re orchestrating. And once this is set up: /review → full PR analysis /deploy → build + push /test-all → run full suite /bootstrap → scaffold modules One command = entire workflow. This is the shift most people still don’t see: Beginners → ask AI for answers Advanced → build systems that run on AI Same tool. Completely different output. Claude Code isn’t powerful because of the model. It’s powerful because of the structure around it. And this is what 99% of people are missing
@HeyZoyaKhan ·
Claude Official Learning Resources All in one place: (save this) 1. Anthropic Learn: https://t.co/MGe8tlUy6Z 2. Build With Claude: https://t.co/MyzT8b4OS5 3. Claude Documentation: https://t.co/HasipQke9d 4. Prompt Engineering Overview: https://t.co/T50pq9TLiZ 5. Prompting Best Practices: https://t.co/LZTxFECuld 6. Claude Code Documentation: https://t.co/6asrn076TH 7. Claude Code Overview: https://t.co/m5U56fbel8 8. Model Context Protocol (MCP): https://t.co/OIAjCQxu0Y 9. MCP Documentation: https://t.co/pPzMEvoQK3 10. Anthropic Courses: https://t.co/7hn36vF9nh 11. Anthropic GitHub Courses: https://t.co/WDxLtjp7cB 12. Anthropic Engineering Blog: https://t.co/6xoX2e2mUu 13. Anthropic Research: https://t.co/BN7nPhyRlf 14. Anthropic News & Releases: https://t.co/qKTPf0oqHx 15. Claude API Documentation: https://t.co/jbvszvCMR4 16. Claude Cookbook: https://t.co/bwpj95imvC 17. Anthropic YouTube Channel: https://t.co/0wjDI0IiC8 18. Claude Artifacts Guide: https://t.co/7uDIcuKXzE 19. Claude Tool Use Guide: https://t.co/K8kf4zA0mJ 20. Claude Agent Skills: https://t.co/RVW2yr9MGn That's a wrap
@_vmlops ·
ANTHROPIC RELEASED A COMPLETE GUIDE TO BUILDING SKILLS FOR CLAUDE skills are folders that teach claude specific workflows once, so you stop re-explaining the same process every conversation. → progressive disclosure: frontmatter loads first, full instructions load only when needed → works identically across https://t.co/GlzeLGdKfs, claude code, and the api → mcp gives the tools, skills teach the recipes for using them → covers planning, testing, distribution, and troubleshooting patterns
@nurijanian ·
I've been looking for a way how people use Codex and Claude Code together and found these to add to my AI plugins collection: https://t.co/F6iJqA84aW the workflow that keeps coming up is: Claude creates, Codex reviews. https://t.co/bI7WnZBysn Adds Codex directly inside Claude Code. Three commands: - /codex:review: Codex reads what Claude just built and flags issues - /codex:adversarial-review: you tell it what to challenge specifically ("challenge whether this caching design handles partial failures") and it hunts for the race conditions and edge cases Claude already approved - /codex:rescue: when Claude hits a wall and starts going in circles, hand the problem to Codex cold https://t.co/8RISlnvXut automates the ping-pong into a pre-commit gate. Codex runs before Claude's work gets committed. If it finds issues, the commit is blocked. The observation behind this: same-model sub-agents reviewing each other miss things. Cross-model review catches different blind spots. Two models built differently have different failure modes, so they surface each other's gaps. Claude and Codex have different temperaments. Claude is the fast mover. Codex is the grounded reviewer who's seen things. You want both on the team.
@thedevchandra ·
Claude is going insane with features right now Meanwhile 99% of people are still using it as a chatbot Here are 5 setups that'll change how you use it: 1/ CLAUDE. md - your instruction manual. Tell Claude who you are, what you're building, how you think. Every session starts informed. 2/ Rules files - set guardrails once. Tone, format, what to avoid. Claude follows them automatically. 3/ Memory - Claude remembers your preferences, context, and past work across conversations. Stop re-explaining yourself. 4/ Custom commands - turn your most repeated prompts into one-click shortcuts. Same output, zero rework. 5/ Connectors - link Claude to Slack, Google Drive, Calendar. It pulls live context instead of working blind. Don't just chat, build leverage.
@etnshow ·
There's an 80% chance Claude is the leading model by the end of April according to @Polymarket Founder of @polsia, Ben Cera (@Bencera) says Anthropic's Claude is "the most street smart": "I often use every single model in parallel and compare them every couple of weeks and I do a stress test on them" "@AnthropicAI is clearly the most street smart. It's the most blend of speed of answer, mostly getting it right and pragmatic. I think that's why it works so well because most companies need that" "GPT's latest Codex series are more ground truth. Most companies don't need the ground truth" "My own experience is that the Claude models are most pragmatic, and fast and cost efficient"
Watch video@sickdotdev ·
Most people assume Claude rate limits are unpredictable. They are not. In most cases, the issue is inefficient usage patterns. After digging through Anthropic documentation, API behavior, developer discussions, and real-world usage patterns, one thing became obvious: The users who almost never hit limits are not necessarily using Claude less. They are using it smarter. Here are some of the most effective ways to reduce Claude rate limits while improving output quality: Avoid endless back-and-forth chats Every new reply forces Claude to process the growing conversation history again. Long threads quietly burn through tokens. Shorter sessions are far more efficient. Give complete instructions upfront Instead of: • “rewrite this” • “make it shorter” • “change the tone” Combine everything into one well-structured prompt. Clear prompts reduce unnecessary generations. Edit your original prompt when possible Editing is often more efficient than continuing long reply chains. Extended conversations accumulate context fast and consume far more capacity than people realize. Trim unnecessary context Avoid sending: • entire PDFs • full repositories • massive logs Share only the exact section needed. Smaller context windows = better efficiency. Set response constraints Claude tends to generate detailed outputs by default. Simple instructions like: • “keep under 100 words” • “bullet points only” • “concise response” can significantly reduce usage. Ask for structure before depth Do not generate everything in one shot. Start with: • outline • framework • action plan Then expand section by section. This prevents wasted generations and revisions. Use smaller models for lighter tasks Not every request needs the highest-end model. Use lightweight models for: • summaries • formatting • rewrites • quick edits Reserve larger models for reasoning-heavy work. Use Projects and persistent context properly If you repeatedly paste: • company information • writing preferences • coding standards • brand voice you are wasting context every session. Persistent memory matters. Avoid high-demand usage windows During peak traffic periods, limits can feel stricter. Timing genuinely affects the experience. But the biggest takeaway is this: Claude optimization is no longer just prompt engineering. It is context engineering. The best users optimize: • context size • memory usage • conversation structure • token flow more effectively than everyone else. That is usually the difference between people constantly hitting limits and those who rarely notice them. It is rarely about the subscription plan. It is about how intelligently the model is being used.
@frog_omo ·
anthropic just shipped claude tag. it's a shared AI teammate that lives in slack. you @mention it like a coworker. here's what makes it different from every other slack AI bot: the core shift: multiplayer, not single-player. the old "claude in slack" app was per-user. it acted under your permissions, billed to you, with limited context (~20 messages) and no shared memory. claude tag is the opposite: → one shared claude per channel → persistent memory that builds over days → runs under its own "agent identity" (not borrowing your credentials) → bills the organisation, not you → can schedule its own work → can act without being tagged (optional ambient mode) how agent identity works: claude acts under its own service accounts. it posts as the claude app in slack. opens PRs as the claude github app. queries your data warehouse under an admin-provisioned service account. permissions follow the channel, not the user. a channel member without direct repo access can ask claude to read that repo — if the channel's profile grants it. each private channel gets a distinct identity. memory and access respect channel boundaries. what it can do: → write and merge pull requests → investigate bug root causes → reproduce incidents and reconstruct timelines → pull and interpret product metrics from a warehouse → summarise long threads into docs with action items → work through support tickets → watch thresholds (e.g., ping when CI stays red) the proactive part: ambient mode is off by default. when enabled, claude doesn't wait to be tagged. it can flag relevant updates, follow up on stalled threads, and ping when a long job finishes. you dial proactivity in plain language: "only reply when tagged" vs "watch this channel and answer what you can." the async part: set a task and walk away. claude works in the background and can schedule its own follow-ups, pursuing projects over hours or days. anthropic says its teams now delegate to "many claudes in parallel." what anthropic claims internally: "65% of our product team's code is created by our internal version of claude tag." cat wu (head of product for claude code) told reuters: "claude code, cowork, and chat are very single-player, whereas claude tag is built to be interactive and multiplayer." who can use it: → team and enterprise plans only (not pro or free) → requires a paid slack plan → not available to zero data retention orgs → runs on claude opus 4.8 launch credits: → enterprise: $25,000 → team (10+ seats): $2,500 → expire september 1, 2026 the old "claude in slack" app switches over to claude tag on august 3, 2026. the positioning: rob seaman (GM of slack) called it "making AI multiplayer." anthropic explicitly positions it as "the beginning of an evolution of claude code." the distinction: claude code is fastest for solo, synchronous terminal work. claude tag is "claude code made more proactive and built to work with a full team." the caveats: → beta — behaviour may change → slack-only today (other platforms "coming weeks") → consumption billing means ambient mode can be costly → no human-approval gate in ambient mode → no documented EU data-residency option the bottom line: slack AI and chatgpt/claude single-user apps are reactive in-thread assistants that reset between conversations. claude tag operates in public channels as a visible, shared teammate with persistent memory, its own identity, and the ability to act without being asked. that's the shift everyone's been circling: from "AI that talks" to "AI that does."
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