Futurality AI

8 Claude prompt frameworks to get better AI results 🧠 Use structures like: • CLARITY • SOCRATES • TRUST • RIPPLE • MAGIC • CATCH The secret isn’t longer prompts. It’s structured thinking + clear context + defined goals.

You keep hitting Claude's limit by 2 pm. Every day. These 21 habits make it last all day: (even if you're on the $20 plan) 1. Convert files before uploading. ☑ One PDF page = 1,500–3,000 tokens ☑ Paste text into doc .new → download as .md file ☑ 15-page PDF → 2,000 clean tokens 2. Plan in Chat. Build in Cowork. ☑ File creation & analysis eats more of your limit ☑ Think in the cheap product (Claude Chat) ☑ Build in the expensive one (Claude Cowork) 3. Say "ask me questions" instead. ☑ 500-word prompt costs 500 tokens every reread ☑ Let AskUserQuestion pull the context ☑ Clicking options costs almost nothing 4. Speak, don't type. ☑ Install Wispr Flow .ai (free) ☑ Voice = more context in one shot ☑ Fewer messages = fewer rereads 5. Fix the broken section only. ☑ Don't ask for a full redo ☑ "Only redo section 2." ☑ Targeted edits = fewer tokens burned 6. Edit your prompt, never correct it. ☑ "Actually, change…" = another full reread ☑ Hit edit on the original instead ☑ One clean prompt beats five corrections 7. New topic = new chat. ☑ Message 30 re-reads 29 exchanges first ☑ Long chats are token furnaces ☑ Restart before it eats your day 8. Use Sonnet for the simple stuff. ☑ Save Opus for deep work ☑ Match the model to the task ☑ Stop paying Opus prices for easy jobs 9. Use Projects for recurring files. ☑ Same PDF in 5 chats = 5 full reads ☑ Upload once → it gets cached ☑ Every future chat references it free 10. Turn off Memory. Set Preferences. ☑ Every fresh chat wastes 3–5 setup messages ☑ Settings → General → Personal preferences ☑ One setup, permanent savings 11. Spread your sessions. ☑ Claude runs a rolling 5-hour window ☑ Burn it all by noon = wasted capacity ☑ Split into morning, afternoon, evening The other 12 habits here: ruben.substack.com/p/how-to-stop-… (save this to make your $20 plan last all day)

Most people think AI agents are just “LLMs with tools.” But the interesting part is memory. Just like humans, capable AI agents need different kinds of memory to function properly. This is one of the core ideas behind the COALA framework (Cognitive Architectures for Language Agents). Think about how humans work: - You remember what someone said 10 seconds ago. - You remember facts from school. - You remember how to ride a bicycle. - You remember important life experiences. AI agents need similar layers of memory too. Here are the 4 major types: 1. Working Memory (Short-Term Memory) Human analogy: You’re reading a sentence right now while remembering the previous sentence. It’s temporary memory used for the current task. For AI agentst his is the active context window which includes: - current conversation - recent tool outputs - current reasoning chain Without it, the agent loses track mid-task like a human getting distracted every 5 seconds. ------------ 2. Semantic Memory (Factual Knowledge) Human analogy: You know Paris is the capital of France. You know Kubernetes manages containers. These are facts, concepts, and knowledge. For AI agents this includes: - stored facts - documentation - knowledge bases - vector databases - retrieved company information It answers: “What does the agent KNOW?” CLAUDE.MD is an example of Semantic Memory ------------ 3. Procedural Memory (Learned Skills) Human analogy: You don’t consciously think about every muscle movement while riding a bike. Skills become automatic. For AI agents this is: - workflows - system prompts - learned action patterns - tool usage strategies - step-by-step execution habits Example: An agent learns: “First query database → then validate → then summarize.”. Agent Skills or Skills.md are examples of procedural memory It answers: “What does the agent KNOW HOW TO DO?” ------------ 4. Episodic Memory (Past Experiences) Human analogy: You remember your first interview. Or a production outage you once handled at work. These are experiences tied to events. For AI agents this includes: - previous interactions - past successes/failures - user preferences - historical task outcomes Example: “The last deployment failed because of missing env variables.” It answers: “What has the agent EXPERIENCED before?” ------------ This is why memory is becoming one of the biggest frontiers in AI engineering. A model without memory is just reacting. An agent with memory starts behaving more like a system that learns, adapts, and improves over time.

12 CLAUDE CODE CONCEPTS YOU NEED TO KNOW BEFORE YOU TOUCH ANYTHING ELSE: - CLAUDE. md - Permissions - Plan Mode - Checkpoints - Skills - Hooks - MCP - Plugins - Context - Slash Commands - Compaction - Subagents BOOKMARK THIS. YOU'LL NEED IT.

Developers are quietly building a second brain inside their AI coding tools right now. And almost nobody realizes how important this shift is. Claude Code’s "Skills.md" looks like “just another markdown file.” It’s not. It’s the beginning of programmable AI memory for software engineering. Most AI coding workflows today are broken in the same way: • repetitive prompting • inconsistent outputs • forgotten context • unstable architecture decisions • AI behaving differently every session So developers waste hours re-explaining: “use this stack” “follow this pattern” “don’t break this API” “write code this way” Over and over again. "Skills.md" changes that completely. Instead of prompting the AI every time… You teach it how your team builds once. Now Claude starts operating with: - coding standards - architecture rules - debugging workflows - testing systems - project conventions - review patterns - deployment logic persisted directly into its workflow. That’s a massive shift. Because this is where AI stops feeling like autocomplete… and starts feeling like infrastructure. The real breakthrough in AI coding isn’t smarter models anymore. It’s persistent operational context. The teams moving fastest right now are not the ones writing better prompts. They’re the ones building reusable intelligence layers around AI. That compounds. Fast. And the scary part? Most developers still haven’t noticed this transition happening. They’re benchmarking models. Meanwhile advanced teams are quietly building internal AI operating systems around their workflows. That gap is going to become enormous. "Skills.md" is interesting because it represents something much bigger than Claude Code itself: AI that adapts to YOUR engineering system instead of forcing engineers to adapt to the AI. That changes: • onboarding • consistency • code quality • iteration speed • institutional memory • engineering velocity A lot of people will look back at these “simple markdown skill files” the same way we now look at: - Dockerfiles - package.json - .gitignore - tsconfig Small files. Huge workflow shift. The future of AI coding won’t belong to the people with the longest prompts. It’ll belong to the people who build the best AI environments. And that transition has already started.

Still confused between MCP, A2A, and Functional Calling? These three approaches are reshaping how LLMs and agents operate at scale, but each one solves a very different problem. Let’s break it down 👇 1. Model-Context Protocol (MCP) MCP manages dynamic context windows across enterprise LLM infrastructure. It retrieves prior memory, history, and metadata to personalize every response without hardcoding logic into prompts. 2. Agent-to-Agent Protocol (A2A) In A2A, agents talk to each other directly using shared protocols. Think of it as collaborative problem-solving between specialized local agents, especially useful in multi-agent ecosystems. 3. Functional Calling Here, an LLM acts like a planner. It decomposes a task (e.g., comparing market caps), generates a Directed Acyclic Graph (DAG) of subtasks, and then sends each task to appropriate tools (math, search, APIs) for execution. Conclusion - MCP is about managing context, - A2A is about agent collaboration, - Functional Calling is about task execution. Mastering all three is key to building powerful, production-ready AI systems. Save this visual for your next AI project!

I gave Claude my birth date and time. It broke down my entire life with eerie accuracy. No horoscopes. No tarot. Just pure AI. Here are 7 prompts you should try ↓

AI tools are evolving fast. But the real advantage comes from knowing which skills and systems to master next. From simple prompting → intelligent workflows. From basic automation → AI-powered execution. The people building these skills today will lead tomorrow’s digital economy. Which AI skill do you think will dominate in 2026? #AI #ArtificialIntelligence #AIAgents #Automation #ClaudeAI #ChatGPT #FutureOfWork #AITools #Tech

Want to get more time back at work? Use these AI prompts:

Everyone is still prompting claude a few teams are structuring it and the difference is insane once you add: CLAUDE.md → project memory skills/ → auto-activated workflows agents/ → parallel workers hooks → lifecycle automation MCP → external tools settings.json → permissions & guardrails Claude stops being a chatbot and starts acting like a senior engineer that knows your repo it remembers conventions runs tests before commits refactors in your style calls tools automatically splits work across agents this is not prompting anymore this is giving Claude a brain + muscle + memory the teams using structured Claude will ship 10x faster because they’re not asking AI for answers they’re assigning it responsibilities bookmark this before everyone discovers CLAUDE.md RT if you’re building with Claude Code already

How to set up Claude Projects completely in 1 hour: (duplicate my exact project, files, and prompts) 1. Update your Claude desktop app. 2. Click the Cowork tab at the top. 3. You need a Pro plan ($20/mo). Worth it. ----- → 0-5 min: Open Projects in Cowork. Cowork tab → Projects → click '+'. 3 choice: scratch, import old Project, existing folder. Pick the recurring task you do every single week. (This is where 90% of people overthink. Don't) → 5-20 min: Create your first Project. Start from scratch = brand new folder. Import a Claude Project = old files + instructions. Use existing folder = your Cowork memory + rules. (Pick one. You can build more next weekend) → 20-30 min: Write Project instructions. Keep them short. 5-8 lines max. Cover: tone, format, output type, hard rules. End with: "Use AskUserQuestion before executing." (You write this once. It runs every time) → 30-40 min: Add files to the folder. about-me .md = who you are, how you work. anti-ai-style .md = every word you'd never use. 2-3 of your best past outputs as examples. To download my files, go to how-to-ai.guide. Don't pay anything. It's free in the welcome email (These files replace 500-word prompts forever) → 40-50 min: Run your first real task. Setup prompt: "Read every file in this folder. Summarize what you know about this workspace." Then: "I want to [task]. Ask me questions first." Claude generates clickable forms to prompt you. (Stop prompting. Start directing) → 50-60 min: Schedule a recurring task. Open the Project → Scheduled tasks → New. "Every Monday at 7am, create my weekly briefing." You wake up to a finished doc. That's the endgame. Pro tip: Keep the desktop app open + computer awake. Scheduled tasks need it running. To download all of my other Claude infographics: Step 1. Go to how-to-ai.guide. Step 2. Subscribe for free. Don't pay anything. Step 3. Open my welcome email (most skip this). Step 4. Hit the automatic reply button inside. Step 5. Download my infographics from my Notion. Bonus. Enjoy my best copy-paste prompts, too.

Most engineers think CLAUDE.md is just a README for AI. They’re wrong. It’s the difference between: → Claude acting like a junior intern → Or a senior engineer who’s been on your team for 10 years Here’s what almost nobody talks about 👇 The 4-Layer Context System: 1) Project Memory Your team’s brain in one file Decisions. conventions. edge cases. (Not just what to do — what to NEVER do) Most people stop here. That’s the mistake. 2) Behavior Gates Guardrails before chaos → Block risky actions before they happen → Auto-fix code after every step → Stop secrets from ever leaking AI without this = unpredictable AI with this = reliable 3) Specialized Workflows You stop prompting. You start building playbooks. → Tasks trigger automatically → Each workflow brings its own tools + logic → Claude doesn’t guess — it executes 4) Team Orchestration This is where things get wild → Multiple agents working in parallel → Tasks split, solved, merged → Clean, isolated contexts This isn’t AI anymore. It’s an AI team. Here’s the real unlock: Individually, these are useful. Together, they’re unfair. Hooks enforce Skills execute Agents coordinate CLAUDE.md connects everything Most engineers are still writing prompts. The ones moving 10x faster? They’re building systems.

You install Claude Code and stop there. Here are 24 things actually worth adding: If you're totally new to Claude Code: ━━━━━━━━━━━━━━━ START HERE ━━━━━━━━━━━━━━━ Claude Code for Normal People charliehills.substack.com/p/claude-code-… Build Your First AI Agent in Claude charliehills.substack.com/p/build-your-1… ━━━━━━━━━━━━━━━ PLUG-INS (Bundled tools, agents, and commands) ━━━━━━━━━━━━━━━ • gstack 23 specialist dev tools in one install github.com/garrytan/gstack (82.7k★) • superpowers Complete dev methodology + 14 skills github.com/obra/superpowe… (192k★) • codex-plugin-cc OpenAI’s official Codex plugin github.com/openai/codex-p… (8.9k★) • financial-services IB, PE, equity, and wealth workflows github.com/anthropics/fin… (23k★) • claude-for-legal Legal workflows for every practice area github.com/anthropics/cla… (6.6k★) • claude-skills 263+ skills across every platform github.com/alirezarezvani… (5.2k★) • marketingskills 40 marketing tools for full growth ops github.com/coreyhaines31/… (28.8k★) • social-media-skills Content OS for posts, reels, and growth github.com/charlie947/soc… ━━━━━━━━━━━━━━━ SKILLS (Specialist instructions Claude loads on demand) ━━━━━━━━━━━━━━━ • frontend-design Kills generic AI UI github.com/anthropics/ski… • hyperframes Write HTML, render video, agent-native github.com/heygen-com/hyp… (18.6k★) • ai-second-brain Karpathy-style wiki + AI history github.com/charlie947/ai-… • notebooklm-skill Claude queries your research github.com/PleasePrompto/… • humanizer Removes AI writing tells from drafts github.com/blader/humaniz… (2.9k★) • claude-seo GEO-first SEO built for the AI era github.com/AgriciDaniel/c… (4.5k★) • antfu-skills Vue + Vite core team skills github.com/antfu/skills (3.5k★) • caveman Cuts 65% of tokens. Talks like caveman. github.com/JuliusBrussee/… (59.2k★) ━━━━━━━━━━━━━━━ MCP SERVERS (Live connections to your apps) ━━━━━━━━━━━━━━━ • granola Meeting notes fed directly into Claude granola.ai/blog/granola-m… • slack Reads channels + posts updates slack.com/help/articles/… • notion Reads and writes your docs developers.notion.com/guides/mcp/get… • kondo Triages your LinkedIn DMs relay.trykondo.com/mcp • zapier 9,000+ apps with one connection mcp.zapier.com • higgsfield Cinematic video from a prompt higgsfield.ai/mcp • perplexity Live web search for Claude github.com/perplexityai/m… • agent-browser Browser automation with fewer tokens github.com/browserbase/mc… ━━━━━━━━━━━━━━━ Save this for later. Most people install Claude Code. Very few build an actual AI operating system around it. Repost ♻️ to help someone in your network. P.S. Which one are you installing first?

1/ iPhone Users Settings > your name > Sign-In & Security > Legacy Contact Assign someone you trust. Apple generates an access key tied to them. The moment they show that key alongside a death certificate, your entire iCloud opens up. Photos, files, emails, notes. Everything. Skip this and your family spends months fighting Apple's bureaucracy with no guarantee it works.

If you died tomorrow your family could not access a single thing you own digitally. Bank accounts. Crypto. Passwords. Cloud storage. All of it locked permanently. Here is how to fix that in 30 minutes:

@Airaasayss 22

How many people are still in the room🤔🤔🤔 Solve honestly in 10 seconds..!!!

Prompts we should consider! 2024 Prompting: “Don’t sound like AI.” “Don’t use buzzwords.” “Don’t use filler.” “Don’t use em dashes.” People were manually fighting AI writing patterns line by line. 2026 Prompting: “Here’s a file with 1,168 lines of AI writing patterns. Read it. Learn it. Apply it globally.” We went from prompting outputs to prompting behavior systems. The real shift in AI isn’t bigger models. It’s persistent context, memory, and style control. Prompt engineering is slowly turning into: • rule engineering • taste engineering • identity engineering And most people still think better prompts = adding more adjectives.

Anthropic just dropped a 31-page prompting guide. Here's everything you actually need (in 10 rules): 1. You write "review this contract" and pray. Fix: Name every output. "Review this contract. Flag risks per clause. Rate severity 1-5. Return as a table." 2: You say "summarize this" on a 40-page report. Fix: 4.7 sizes the answer to the input. Cap it: "5 bullets. Each under 15 words. Start each with an action verb." 3: You write "don't use jargon. don't be salesy." Fix: Negative instructions don't stick. Flip them: "Write in plain English a 16-year-old could read aloud." 4: You type "can you help me with the email?" Fix: Each verb ships something. For example: "Go to Gmail. Find [contact]. Write the send-ready reply. Under 90 words. Tone: confident, casual." 5: You wait for Claude to web search on its own. Fix: Claude opus 4.7 calls fewer tools than 4.6. Force it: "Use web search aggressively. Verify every claim with at least 2 sources." 6: You miss the warm tone from old Claude. Fix: Claude opus 4.7 is direct. Almost zero emojis. Paste 2-3 sentences in the voice you want. Tell Claude to match the rhythm. 7: You ask for "a landing page" & get bare minimum. Fix: Drop this one line on every creative task → "Go beyond the basics." It's from Anthropic's own doc. 8: You forget Claude 4.7 doesn't reason by default. Fix: They call it "adaptive thinking." Add this at the end: "Think before answering (maximum reasoning)." Free upgrade. Every time. 9: You rewrite the same prompt 14 times a week. Fix: A skill is a command with instructions pre-built. Write the same prompt twice? Make it a skill. 10: You assume Claude knows what you meant. Fix: Old Claude 4.6 guessed. New Claude 4.7 does exactly what you typed. Spell it out. Output. Order. Length. Tone. Format. If you don't say it, you don't get it. To go even further & download my .md files directly: Step 1. Go to how-to-ai.guide. Step 2. Subscribe for free. Don't pay anything. Step 3. Open my welcome email (most skip this). Step 4. Hit the automatic reply button inside. Step 5. Download my .md files from my Notion. Bonus. Enjoy my best copy-paste prompts, too.

I built these 7 prompts from frameworks that have driven billions of dollars in decisions across companies like Amazon, Toyota, and Berkshire Hathaway. The prompts are free. The thinking systems behind them are what separate good decisions from expensive mistakes. Also checkout the following: Turn Claude into 20+ different specialists for marketing & business. Install real expertise, not just prompts. Get my Claude skills bundle 👇 linktr.ee/alex_prompter

Want to become a Claude Certified Architect in 6 weeks? 🚀 Here’s a simple roadmap to go from beginner → builder → certified 👇 📅 Week 1 — Learn the Basics Master the essentials: • Claude API • MCP (Model Context Protocol) • Claude Code • Claude fundamentals 📅 Week 2 — Build Real Projects Stop watching tutorials. Start shipping: • Apps with Claude Code • AI agents + APIs • MCP workflows & integrations 📅 Week 3 — Study the Exam Understand what matters: • Real-world case studies • 5 important domains • Skills tested in the exam 📅 Week 4 — Advanced Practice Level up your projects: • Multi-agent systems • Team collaboration workflows • Research + automation pipelines 📅 Week 5 — Mock Tests Train under pressure: • Practice exams • Analyze weak areas • Aim for 850+/1000 📅 Week 6 — Certification Time Take the real exam. One attempt. One goal. 🏆 ❤️ Like 🔁 Repost 🔖 Save for later Follow for more AI learning content ⚡