Did you know Claude can read and analyse huge PDFs in one go? Most tools break or lose context with large files. With Claude, you can: upload full PDFs or reports ask for summaries, insights, or inconsistencies compare multiple documents at once It can handle roughly: 500 to 700 pages of text around 10 to 50 MB depending on the file Now you don’t have to split documents just to get answers.

Turns out… it's not the model. It is how I am using it. Turns out Claude doesn’t count messages. It counts tokens. Once that clicked, everything changed. Here are 10 things that make a massive difference: 1. Edit your prompt instead of sending follow-ups If the response is off, don’t send: “No, I meant…” or “That’s not right…” Every extra message gets added to history. Claude re-reads ALL of it every time. Token cost grows fast: At ~500 tokens per exchange 5 messages = ~7.5K tokens 10 messages = ~27.5K tokens 20 messages = ~105K tokens 30 messages = ~232K tokens Instead: edit your original prompt and regenerate. You replace the history instead of stacking it. 2. Start a new chat every 15 to 20 messages Long chats are expensive. Most tokens get burned re-reading old context, not generating new output. One dev tracked usage: 98.5% tokens = re-reading history 1.5% = actual output Fix: Ask Claude to summarise → copy → start fresh chat → paste summary. 3. Batch your questions Stop sending multiple messages. Bad: “Summarise this” “Now list points” “Now give a headline” Better: “Summarise this, list key points, and suggest a headline.” One prompt = one context load. 4. Use Projects for repeat files Uploading the same file repeatedly = repeated token cost. Projects cache your files. Upload once → reuse without re-tokenising. If you use PDFs, briefs, or docs often, this alone saves a lot. 5. Set Memory and Preferences If you keep typing: “Act as…” “I’m a…” “I write like…” You’re wasting tokens every time. Save it once in settings. Claude remembers it. 6. Turn off unused features Search, connectors, advanced thinking all add token cost. If you didn’t intentionally turn it on, turn it off. 7. Use the right model Not everything needs power. Haiku → quick, cheap tasks Sonnet → standard work Opus → deep thinking Most people overuse powerful models and burn budget fast. 8. Spread usage across the day Claude uses a rolling 5-hour window. If you burn everything in one session, you waste the rest of your day.

Truth Protocol 1. Confidence tag Every answer labeled: High / Medium / Low 2. Source handling Browse and cite for post 2024 or high impact claims State when no browsing is used 3. Facts vs assumptions Clearly separate known facts from inferences No guesses presented as facts 4. Verification mindset VERIFY: double check critical info NO BROWSE: declare internal knowledge use RED PEN: actively look for errors AUDIT: step by step validation CITE: include sources when used 5. Math transparency Show full working No skipped steps Totals must reconcile exactly 6. Error handling Own mistakes directly Recalculate fully, not partial fixes 7. Data dependency Flag when dependent on user data State limits if data is incomplete 8. Clarity and directness Keep responses clean, precise, and to the point 9. Consistency check All figures must align across the response Totals must match exactly 10. Final validation Recheck final answer before sending Ensure internal consistency

There’s a lot of AI advice out there. Most of it sounds good. But a lot of it doesn’t actually help. Here’s how to spot bad AI advice fast: 1. It’s too generic “Use AI to grow your business” No steps. No clarity. No use. 2. It skips the thinking part If it jumps straight to tools without defining the outcome, it’s weak. 3. It promises shortcuts “Automate everything” “Set and forget” That’s not how it works. 4. It sounds impressive but says nothing Big words. No real application. 5. You can’t use it immediately Good advice = you can apply it today Bad advice = you just nod and scroll Good AI advice is simple, clear, and usable. Bad AI advice sounds smart but leaves you stuck. What’s the worst AI advice you’ve seen lately?

A lot of people are starting to use AI to capture ideas. It seems easy. Open ChatGPT. Type the idea. Done. But here’s the problem: AI is great at thinking. It’s not great at storing. Ideas get buried in chats. You can’t see everything in one place. You lose track of what you already have. Here’s the better system: Use AI for processing. Use a simple tool for storage. The system: 1. Capture (Notes or Docs) Every idea goes in one place. Not in AI. 2. Process (AI) Paste the idea into AI: “Turn this into a short post. Simple.” 3. Create (Canva) Turn the idea into a visual. 4. Store (Drive / Docs) Save the final version. Simple version: Store → Process → Create → Save AI is where you think. Your notes are where you remember. Most people mix the two. That’s why they lose ideas. Where are you currently storing your ideas?