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Oct 19, 2025 8 tweets 7 min read Read on X
everyone's arguing about whether ChatGPT or Claude is "smarter."

nobody noticed Anthropic just dropped something that makes the model debate irrelevant.

it's called Skills. and it's the first AI feature that actually solves the problem everyone complains about:

"why do I have to explain the same thing to AI every single time?"

here's what's different:

- you know how you've explained your brand guidelines to ChatGPT 47 times?
- or how you keep telling it "structure reports like this" over and over?
- or how every new chat means re-uploading context and re-explaining your process?

Skills ends that cycle.

you teach Claude your workflow once.

it applies it automatically. everywhere. forever.

but the real story isn't memory. it's how this changes what's possible with AI at work.Image
here's the technical unlock that makes this actually work:

Skills use "progressive disclosure" instead of dumping everything into context.

normal AI workflow:
→ shove everything into the prompt
→ hope the model finds what it needs
→ burn tokens
→ get inconsistent results

Skills workflow:
→ Claude sees skill names (30-50 tokens each)
→ you ask for something specific
→ it loads ONLY relevant skills
→ coordinates multiple skills automatically
→ executes

example: you ask for a quarterly investor deck

Claude detects it needs:
- brand guidelines skill
- financial reporting skill
- presentation formatting skill

loads all three. coordinates them. outputs a deck that's on-brand, accurate, and properly formatted.

you didn't specify which skills to use.
you didn't explain how they work together.
Claude figured it out.

this is why it scales where prompting doesn't.Image
let me show you what this looks like in real workflows.

Scenario 1: Brand-Consistent Content (Marketing Team)

❌ old way:
- designer makes deck
- brand team reviews: "wrong fonts, logo placement off, colors don't match"
- designer fixes
- brand team reviews again: "footer format is wrong"
- 3 rounds, 4 hours wasted

✅ Skills way:
create "Brand_Guidelines" skill with:

• color codes (#FF6B35 coral, #004E89 navy)
• font rules (Montserrat headers, Open Sans body)
• logo placement rules (0.5" minimum spacing)
• template files

prompt: "create 10-slide deck for Q4 product launch"

- Claude auto-applies brand skill
- output matches guidelines first try
- 30 seconds instead of 4 hours

Rakuten (Japanese e-commerce giant) is already doing this.

finance workflows that took a full day? now 1 hour.Image
Scenario 2: Sales Workflow Automation (Revenue Team)

the repetitive nightmare:
- new lead comes in
- manually create CRM contact
- fill in 12 fields following "the naming convention"
- update opportunity stage
- log activity notes in specific format
- set follow-up reminder
- 8 minutes per lead × 30 leads/week = 4 hours gone

Skills implementation:
create "CRM_Automation" skill that knows:
- your naming conventions (FirstName_LastName_Company format)
- required fields and validation rules
- opportunity stages and when to use them
- note formatting structure
- follow-up timing rules

now: paste lead info → Claude structures everything correctly → done

time per lead: 30 seconds
weekly savings: 3.75 hours
monthly savings: 15 hours (almost 2 full workdays)

at $50/hour, that's $750/month saved per sales rep.
team of 10 reps? $90k/year in recovered time.

youtu.be/kS1MJFZWMq4
Scenario 3: Legal Contract Review (In-House Counsel)

the manual process:
- receive vendor contract
- review against standard terms checklist (24 items)
- identify deviations and risks
- draft redline suggestions
- write internal memo
- 45-60 minutes per contract

Skills setup:
create "Contract_Review" skill containing:
- your standard terms library
- risk classification framework
- approved clause variations
- redline language templates
- memo format structure

execution:
upload contract PDF
prompt: "review this against our standard terms"

Claude outputs:
• flagged risky clauses with severity ratings
• suggested protective language
• formatted redline document
• internal memo for stakeholders

time: 8 minutes instead of 60 minutes

for teams reviewing 50+ contracts/month:
→ saves 43 hours monthly
→ $8,600/month at $200/hour legal rates
→ $103k annually

that's a junior attorney's salary in recovered partner time.
ok but how do you actually BUILD one?

for one, you can simply prompt claude: "create a [name of skill] skill, ask me all the necessary questions for context."

you can also create it manually. here's the exact structure of a SKILL.md file:

1/ YAML Frontmatter (metadata):
---
name: Brand Guidelines
description: Apply Acme Corp brand guidelines to presentations and documents
version: 1.0.0
---

this is what Claude reads first to decide IF it should load your skill.

keep description specific (200 char max) or Claude won't know when to use it.

2/ Markdown Body (the actual instructions)

---
## Overview
This Skill provides Acme Corp's official brand guidelines.
Apply these standards to ensure all outputs match our visual identity.

## Brand Colors
- Primary: #FF6B35 (Coral)
- Secondary: #004E89 (Navy Blue)
- Accent: #F7B801 (Gold)

## Typography
Headers: Montserrat Bold
Body text: Open Sans Regular
Size guidelines:
- H1: 32pt
- H2: 24pt
- Body: 11pt

## Logo Usage
Always use full-color logo on light backgrounds.
White logo on dark backgrounds.
Minimum spacing: 0.5 inches around logo.

## When to Apply
Apply these guidelines when creating:
- PowerPoint presentations
- Word documents for external sharing
- Marketing materials

## Resources
See resources/ folder for logo files and fonts.
---

the markdown body is where Claude gets the DETAILS.
it only reads this after deciding the skill is relevant.

this two-level system (metadata → full content) is why Skills scale without burning tokens.Image
now package it correctly (this trips everyone up):

Step 1: Create folder structure

---
Brand_Guidelines/
├── SKILL.md (contains the YAML + markdown body above)
└── resources/
├── logo.png
└── fonts/
---

Step 2: ZIP it properly
✅ CORRECT structure:
---
Brand_Guidelines.zip
└── Brand_Guidelines/
├── SKILL.md
└── resources/
---

❌ WRONG structure:
---
Brand_Guidelines.zip
├── SKILL.md (loose in root)
└── resources/
---

the FOLDER must be inside the zip, not files directly.

Mac: right-click folder → "Compress" Windows: right-click folder → "Send to" → "Compressed folder"

Step 3: Upload to Claude
Settings → Capabilities → enable "Code execution"
upload your .zip under Skills

test with: "create a presentation following brand guidelines"

pro tip: use the "skill-creator" skill just say "help me create a brand guidelines skill" and Claude interviews you, generates the folder structure, and formats everything automatically.

the companies dominating with AI aren't using better prompts.

they're building systems that codify how they work.

explore real examples you can clone: github.com/anthropics/ski…Image
Claude made simple: grab my free guide

→ Learn fast with mini-course
→ 10+ prompts included
→ Practical use cases

Start here ↓
godofprompt.ai/claude-mastery…

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More from @godofprompt

Feb 19
🚨 R.I.P Harvard MBA.

I built a personal MBA using 12 prompts across Claude and Gemini.

It teaches business strategy, growth tactics, and pricing psychology better than any $200K degree.

Here's every prompt you can copy & paste: Image
1. Business Strategy (Claude)

Prompt:

"Act as a strategy consultant. Analyze my business idea using
Porter's Five Forces. Be brutal. Tell me where I'll die,
not where I'll win. Business idea: [YOURS]" Image
2. Financial Modeling (Gemini)

Prompt:

"Build me a 3-year P&L projection for this business model: [YOURS].
Assume conservative, base, and aggressive scenarios.
Show me which assumptions matter most." Image
Read 17 tweets
Feb 18
Perplexity is terrifyingly good at competitive intelligence.

If you use these 10 prompts, you’ll see why:

(Bookmark this thread for later) Image
1/ Map your entire competitive landscape in 60 seconds.

Prompt:

"Act as a competitive intelligence analyst. Give me a full breakdown of [Company X]'s market position right now — pricing strategy, target customers, key differentiators, and recent strategic moves. Cite sources."

Most people Google this for hours.

Perplexity does it in one shot with live data.
2/ Find exactly where your competitor is losing customers.

Prompt:

"Search recent reviews, Reddit threads, and forums from the last 6 months where users complain about [Competitor]. Summarize the top 5 recurring pain points and frustrations."

This is like reading your competitor's support tickets.
Read 14 tweets
Feb 17
Are call centers cooked?

This tool builds a voice agent in <10 mins for any website.

Just give it the link → it will scrape your entire website and your agent is ready to deploy.
The tool is called Agent Wizard by PolyAI. And they just opened a waitlist for Agent Wizard.

You give it a URL. It reads your entire site.

FAQs, product catalog, store hours, contact info, policies. Everything.

Then it builds a voice agent that can actually answer customer calls.

No code. No sales call. No 6-month implementation.
The voice agent it generated isn't a glorified FAQ bot.

It takes reservations. Modifies them. Handles special requests.

"Party of 6, Saturday at 7, one guest has a shellfish allergy"

Done. Synced with OpenTable.
Read 6 tweets
Feb 17
After chatting with 8 engineers from OpenAI and Meta, I discovered they all swear by the same 7 "edge-case" prompts.

Not the viral ones from Reddit.

These are what power cutting-edge prototypes and debug complex models.

Steal them here ↓ Image
First thing I noticed: every one of them writes prompts that assume the model will fail.

Not optimistic prompts.

Adversarial ones.

They're not trying to get a good answer. They're trying to catch where the model breaks.

That changes everything about how you write prompts.
1. The Chain-of-Doubt

"Walk me through your reasoning step by step. After each step, ask yourself: could this be wrong? If yes, say why."

Kills hallucination confidence.

The model second-guesses itself mid-answer instead of committing to a wrong path.

Two Meta engineers independently named this their most-used debug prompt.
Read 12 tweets
Feb 16
I built a “shadow advisory board” of AI personas to critique my business ideas.

Includes:

• Peter Thiel
• Naval
• Buffett
• YC partner
• skeptical VC

Here’s how I structured it ↓ Image
Copy-paste this into Claude/ChatGPT:

---

You are my Shadow Advisory Board - a panel of 5 distinct investor personas who will critique my business idea from different angles.

BOARD MEMBERS:

1. PETER THIEL (Contrarian Technologist)
- Focus: Is this a monopoly or commodity? What's the 0→1 insight?
- Questions: "What do you believe that nobody else does?" "Can this scale to $1B+ without competition?"
- Style: Philosophical, first-principles, anti-consensus

2. NAVAL RAVIKANT (Leverage Maximalist)
- Focus: Can this scale without trading time for money? Where's the leverage?
- Questions: "Does this have code, media, or capital leverage?" "Will this make you rich or just busy?"
- Style: Wisdom-dense, product-market fit obsessed, long-term thinking

3. WARREN BUFFETT (Economics Fundamentalist)
- Focus: What's the moat? Can a 12-year-old understand the business model?
- Questions: "Would you buy this entire business tomorrow?" "What's the durable competitive advantage?"
- Style: Simple, margin-of-safety focused, customer-centric

4. Y COMBINATOR PARTNER (Startup Operator)
- Focus: Can you build an MVP in 2 weeks? Will users literally cry if this disappears?
- Questions: "How are you getting your first 10 customers?" "What's your weekly growth rate?"
- Style: Tactical, execution-focused, speed-obsessed

5. SKEPTICAL VC (Devil's Advocate)
- Focus: What kills this company? Why has nobody done this already?
- Questions: "What's your unfair advantage?" "Why won't Google/Amazon crush you in 6 months?"
- Style: Brutal, risk-focused, pattern-matching

---

CRITIQUE STRUCTURE:

For each board member:
1. Opening reaction (1 sentence - enthusiastic or skeptical)
2. Key insight from their lens (2-3 sentences)
3. Critical question they'd ask (1 question)
4. Red flag or opportunity they see (1 sentence)

End with:
- CONSENSUS: What all 5 agree on
- SPLIT DECISION: Where they disagree most
- VOTE: Fund (Yes/No) + confidence level (1-10)

---

MY BUSINESS IDEA:
[Paste your idea here]

---

Give me the full board critique.Image
Used this to validate a SaaS idea last week.

Thiel killed it: "You're solving a vitamin, not a painkiller"
Naval killed it: "No leverage - you're building a consulting firm with software"
Skeptical VC killed it: "Bubble. com will have this feature in 3 months"

Saved me 6 months building the wrong thing.
Read 6 tweets
Feb 14
Claude is insane for product management.

I reverse-engineered how top PMs at Google, Meta, and Anthropic use it.

The difference is night and day.

Here are 10 prompts they don't want you to know (but I'm sharing anyway): Image
1. PRD Generation from Customer Calls

I used to spend 6 hours turning messy customer interviews into structured PRDs.

Now I just dump the transcript into Claude with this:

Prompt:

---

You are a senior PM at [COMPANY]. Analyze this customer interview transcript and create a PRD with:

1. Problem statement (what pain points did the customer express in their own words?)
2. User stories (3-5 stories in "As a [user], I want [goal] so that [benefit]" format)
3. Success metrics (what would make this customer renew/upgrade?)
4. Edge cases the customer implied but didn't directly state

Be ruthlessly specific. Quote the customer directly when identifying problems.

---Image
2. Competitive Analysis with Actual Strategy

Most PMs just list competitor features in a spreadsheet like it's 2015 haha.

Here's how I get Claude to actually think like a competitive analyst:

Prompt:

---

You are a competitive intelligence analyst

Analyze [COMPETITOR] and answer:
- What job are customers hiring them to do? (not what features they have)
- Where are they vulnerable? (what complaints appear in G2/Reddit/Twitter?)
- What would you build to win their customers in the next 6 months?



- No generic "they have good UX" observations
- Only insights backed by public data you can cite
- Recommend 2-3 specific features we should build, with reasoning


---Image
Read 14 tweets

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