Table of Contents

Quick answer — what you’ll learn

• How to legally register a clothing brand in the USA
• Step-by-step Shopify store setup for fashion brands
• How to source products, set pricing, and scale
• Top SEO and marketing moves to drive traffic in 2025

Starting a clothing brand in the USA using Shopify is one of the most achievable business goals in 2026 but only if you follow the right steps. The global apparel market is projected to reach $1.94 trillion by 2027 [Source: Statista], and Shopify powers over 4.5 million active stores worldwide. The window is open. Here is exactly how to walk through it.

1. Define Your Niche and Brand Identity

The #1 mistake new clothing brands make is trying to sell everything to everyone. The most successful Shopify fashion stores dominate a single niche first streetwear, plus-size athleisure, sustainable basics, or workwear for women. Pick one and own it.

• Choose a niche: streetwear, sustainable fashion, activewear, workwear, kidswear, or luxury basics
• Research your target customer age, income, values, style references (use Pinterest and TikTok trends)
• Create a brand name, logo, and color palette before touching Shopify
• Write a one-sentence brand mission: “We make X for Y who want Z”
• Validate demand using Google Trends, Exploding Topics, and Reddit communities in your niche

2. Register Your Business Legally in the USA

Before you sell a single item, you need legal protection. The USA has clear pathways to register a clothing brand and it protects both your brand name and your money from day one.

• Form an LLC (Limited Liability Company) most affordable protection for small brands. Use Stripe Atlas, ZenBusiness, or your state’s Secretary of State website
• Apply for an EIN (Employer Identification Number) free via IRS.gov, needed for taxes and Shopify Payments
• Trademark your brand name with the USPTO (United States Patent and Trademark Office) costs $250–$350 per class
• Open a dedicated business bank account (Mercury, Relay, or Chase Business are popular with Shopify brands)
• Register for state sales tax compliance use TaxJar or Avalara to automate this across US states

3. Set Up Your Shopify Store

Shopify is the undisputed best platform for clothing brands in 2025. It handles payments, inventory, shipping, and marketing in one place. According to BuiltWith, Shopify holds a 32% share of the US e-commerce platform market [Source: BuiltWith, 2024].

• Sign up at Shopify.com start with the Basic plan ($39/month) or use the 3-day free trial
• Choose a fashion-focused theme: Dawn (free), Impulse, or Prestige are top picks for clothing
• Set up product pages with high-quality photos — at minimum: front, back, detail shot, and lifestyle photo
• Write SEO-optimized product titles and descriptions — include size, material, fit type, and occasion
• Install essential apps: Klaviyo (email), Judge.me (reviews), Loox (UGC photos), and Printful or Printify if using print-on-demand
• Enable Shopify Payments to avoid third-party fees accepts cards, Apple Pay, Google Pay, and Shop Pay
• Set up a custom domain (yourclothingbrand.com) buy via Shopify or Namecheap for ~$12/year

4. Source Your Products or Use Print-on-Demand

You have two main paths: source physical inventory, or use a print-on-demand (POD) model with zero upfront cost. Both work it depends on your capital and how hands-on you want to be.

• Print-on-demand: Use Printful or Printify they print and ship directly to customers. No inventory risk. Perfect for beginners
• Private label: Source blank garments from LA Showroom, Alibaba, or Fashion Go and add your own labels/tags
• Cut and sew: Create original designs with a US-based manufacturer — higher cost but full brand control
• Order samples before selling — always test sizing, color accuracy, and print quality yourself
• Aim for a 60–70% gross margin on clothing — if a T-shirt costs you $8, price it at $22–$28

5. Price Your Clothing Brand Correctly

Pricing is a brand signal as much as a financial decision. Underpricing signals low quality. Overpricing without brand authority loses sales. Here is a proven formula used by successful Shopify clothing brands.

• Use the keystone pricing formula: Cost of Goods × 2.5 to 3 = Retail Price
• Research competitors on Google Shopping and Amazon before setting final prices
• Offer a launch discount of 15–20% to incentivize first purchases and collect email addresses
• Bundle products (e.g “Buy 2 tees, save $10”) to increase average order value
• Never compete on price alone compete on story, quality, and community

6. Build Your SEO and Marketing Strategy

Traffic is the lifeblood of any Shopify clothing brand. In 2025, a multi-channel approach SEO, social media, and email is not optional. Brands that rely on paid ads alone have 3× higher customer acquisition costs than those with strong organic presence [Source: HubSpot, 2024].

• Optimize every product page for keywords like “buy [niche] clothing online USA” and “affordable [style] brand”
• Start a blog on your Shopify store write “How to style X for Y occasion” content that ranks on Google
• Build Instagram and TikTok profiles post 4–5 times per week with reels, outfit inspiration, and behind-the-scenes content
• Partner with micro-influencers (10K–100K followers) in your niche they convert better than mega-influencers
• Use Klaviyo to send a welcome email series, abandoned cart emails, and post-purchase flows
• Run Google Shopping ads once you have 10+ reviews and proven product-market fit
• At Digital Idea2Grow, we consistently see SEO + email deliver the highest ROI for fashion brands in the $10K–$100K revenue range

7. Scale with Data and Customer Loyalty

The brands that go from side project to real business are the ones that obsess over data and retention. Acquiring a new customer costs 5× more than retaining an existing one. Build loyalty from day one.

• Install Shopify Analytics and Google Analytics 4 track which products, pages, and traffic sources convert best
• Launch a loyalty or rewards program using apps like Smile.io or LoyaltyLion
• Send a post-purchase survey (Typeform or Google Forms) ask: “What almost stopped you from buying?”
• Run seasonal sales strategically: Black Friday, Labor Day, and back-to-school are peak periods for US clothing brands
• Expand to wholesale or B2B once you have a proven product reach out to boutiques via Faire Marketplace
• Consider Amazon Handmade or Etsy as secondary channels to capture additional US shoppers

Start now !! If you want to do SEO for your new

Shopify

you can simply fill the form our team will reach out you :

Sanjivan Dhakal | Founder | Idea2grow

Table of Contents

How To Start an E-Commerce Business

I wanted to write something that was a bit gutsier, and a bit more step-by-step. That said, this post ain’t going to wipe so, it relies on you to put in research and effort, and getting comfortable working in the grey and working stuff out for yourself.

This blog is written for people that want to start a real business that has a chance of succeeding in a competitive marketplace. 

1. Before Starting your business Educate Yourself

Starting a business is more akin to learning to fly a plane than taking up tennis. In tennis, you can pick up a racket, start taping the ball over the net with a mate, and slowly learn the techniques while putting it into practice. 

In business, you need to have a baseline understanding before sinking time, effort, and capital. Tennis you’re playing with a mate in your backyard or at a local court. The stakes are low, not much can go wrong. It’s a game. In business, you’re competing in the actual market, which is akin to going up against Federer. The market will indiscriminately chew you up and spit you out if you’re not match fit. 

So, how do you educate yourself on business? 

Google/ChatGPT

Yes, seriously. Everything starts with Google and increasingly ChatGPT or your AI of choice. 

The sort of stuff you should be searching to begin with:

‘how to set up a business in [your country]’

‘business 101’

‘advertising 101’

‘business finance 101’

As you search stuff, go down all the rabbit holes. 

“Hmm, I am reading a lot about P&Ls and unit economics when I study business finance. What are they?” Go down the rabbit holes. 

Whenever you come up against a new word, phrase, concept, search it, learn it, know it. This is how you build knowledge. 

By all means, use YouTube as a research tool. But, be careful. The broader your search, e.g. ‘how to start an e-commerce business’ the more likely you are to wade into murky dropbro territory. You’re going to find heaps of over-simplified, ‘it’s easy, all you have to do is XYZ, look I have the Lambo to prove it’ type content that largely perform as lead magnets for courses, blueprints, and coaching programs. 

Searching ‘how to use GA4’ or ‘how to calculate unit economics’ on YouTube is likely to turn up some really good stuff. 

Books

Remember those? Nothing can quite replace the experience of reading a book. Especially a physical book. 

Here are some of my recommendations:

• How Brands Grow by Byron Sharp
• Stark Naked Numbers by Jason Andrew
• Blue Ocean Strategy by Renée Mauborgne and W. Chan Kim
• 7 Powers by Hamilton Helmer
• Purple Cow by Seth Godin

There are loads of great business books out there. These are just a few that I have read and refer back to regularly. How Brands Grow by Byron Sharp is probably my number one recommendation as it’s central to how marketing actually works. It’s an influential book that’s on the bookshelves of any marketer worth their salt no doubt the CMOs of Coke, McDonalds, Nike, and Ford, all have a copy. 

Don’t want to splash out $30 a book? Go to your local library. Borrow a copy. Remember those?

Study Other Businesses

What did all the successful businesses out there do to get started? How did they find success? How did they differentiate in a competitive market? How did they grow to where they are today? 

Go and find out. 

Study their backstories. Study their founders. If they’re publicly listed, go and study their annual reports. Learn from the best. 

Watch some episodes of Shark Tank and Dragon’s Den too. Great show, real businesses, real business people talking business.

Notice something by the way you’re not going to find any of these ‘winning product, test with ads’ spaghetti against the wall dropshipping businesses in this research. I can’t name a single verifiably successful business that started that way. If it was successful as an approach, there should be hundreds of businesses out there that started that way that the media has reported on? We know about them through shared Shopify screenshots and blokes with beards saying ‘trust me bro’. Convincing, right? ~ rolls eyes ~

While you’re on Google and ChatGPT, reading books, and studying your favourite brands and retailers, take notes. Fire up a clean Google Doc and jot down things as you go, stitch things together, and start to triangulate what you’re learning. You’re starting to build knowledge.

2. Search for the Market Gap

So, you have an idea about how business works now. You’re keen to start your own. But where do you start? You start with a gap or opportunity. 

The best place to find a gap is in a category/niche that you’re already familiar with. It could relate to a passion, a hobby, what you do for work, or a community you’re involved in. 

Why start here? Leverage. Leverage, along with compound, is one of the most powerful tools in your arsenal. You should always be playing to your strengths in business. By starting with a category that you’re familiar with you’re going to have better insights, you probably have a solid understanding of how the category is structured, who the major players are, what the trends are, the various customer segments, and what’s good and what could be better. What’s more, you’re probably connected with other people that engage in the category, and you probably know how to talk-the-talk. And, importantly, you’re already a savvy consumer. 

What have you observed? When it comes to shopping with brands and retailers what do you like, what do you dislike, what do you think you could improve?

When I started my hiking gear brand this is exactly the approach I took. I knew the category and its subcategories—I had been a hiker for 20 years and had spent thousands of dollars on gear—and was sick of the shortcomings with a particular subcategory of products. I had purchased 15-20 over the years and they all experienced the same issue. “I reckon I can do better” I thought. 

3. Identify Socialise & Validate

I identified what I thought was a gap in the market. An opportunity to do better. I knew the category well, I knew my stuff, but we’re very good at talking ourselves into things without being fully honest with ourselves. 

I needed to test my thinking so I socialised my idea. I went out to some hiking buddies to begin with and their feedback was interesting. There were certain aspects they were totally supportive of, and others they were a bit more lukewarm on. This feedback allowed me to strengthen and tighten up my idea. I asked some questions on some hiking forums I was involved with. The overall response was positive, I seemed to be onto something, I decided to move forward to the next step. 

The whole ‘winning product, quick website, test with ads’ approach in dropshipping is meant to be about testing demand and failing fast so you can move onto the next thing without wasting a lot of time and capital. What we of course see is heaps of churn and burn with nothing rarely sticking. Socialisation and validation starts early, at the idea stage. If you can’t sell an idea, good luck selling a physical product that costs money. 

The purpose of this early validation and feedback is to help shape the idea and your execution. You get to know your customer, you get to know what they want, and you get to know how best to communicate with them. No good creating a blue thing if your customers hate blue. 

At this stage you should also develop a really really intimate understanding of your category, the competition, and of course the customer. This will help you durably shape your offering, your value proposition, and how you’re going to be positioned in the market. Get it down on paper/pixels. Find a business plan template on the internet and start building it out. Start structuring your thinking and going about filling in the gaps in your thinking.

4. Build your business in Public

Socialisation and validation isn’t a one-and-done task. It’s something you should do constantly as you shape your product, your brand, your business. 

I shared the entire process of building my hiking gear brand with my audience. That audience grew as word got out and people took a keen interest in what I was doing. 

What colours was I going to launch with? I’ll crowdsource it. What sizes? I’ll ask. 

Sure, sometimes the customer isn’t right but it’s ultimately up to you, as the business owner, to make sensible decisions based on a variety of inputs. These inputs directly from customers were valuable. 

The other benefit of this approach is you’re building awareness, you’re building hype. I had customers along the way giving me the ol’ ‘shut up and take my money’ treatment. What a great position to be in, right? Definitely a vote of confidence. 

I built a mailing list as I went so I had an ‘owned’ source of contacts. I built this to 500+ contacts by launch. 

5. Ready to Launch

Smart businesses when they launch aren’t launching to crickets, to a cold audience. They have built awareness, they have built hype, and they have customers excited for them and wanting them to succeed. 

There’s a new chicken restaurant around the corner from my place. As soon as construction began, they erected branded hoarding around the site with their Instagram handle on it and QR codes. Their Instagram was a sea of activity as they shared the behind the scenes and got people excited for what was coming. Sure enough, on launch day, there was a line down the street of excited punters wanting to see what it was like. The place hasn’t been quiet since launch and I can verify having eaten there now it was worth the hype bloody delicious. 

When I launched my hiking gear brand I got 70+ sales on my first day. The power of building a business around something people want, getting early feedback and validation, and building in public to build awareness and to get early buy-in. 

Why should you consider this approach?

You should consider this approach because real, successful businesses do it. Study a bunch of businesses as I advise in #1 and you’ll see. 

People ask me all the time “Why should I listen to you?” Well, for a start, I have been in e-commerce for around 5 years and have worked for some of Nepal’s, India, and New Zealand brands and retailers, and have had a couple of businesses of my own in that time (Sanjivan, 2026).

I have a bit of experience in the space. But, the stuff I bang on about is verifiably effective. There’s no ‘trust me bro’ business going on here. I don’t need to share pixellated screenshots. All you need to do is go out there, get an understanding of how business actually works and what got your favorite businesses to where they are today, to understand what the magic or not so magic formula is. The formula is pretty straight-forward, really, and it starts with identifying a gap in the market that you’re well placed to address.

Table of Contents

AI Tool Guide

AI Art Generator No Sign Up – Create Images Instantly (2026)

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Step 1: Open idea2grow and scroll down to free AI tools

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Try Free AI Generator

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Try out : AI to text humanizer

]]> https://idea2grow.com/ai-art-generator-no-sign-up/feed 0 https://idea2grow.com/how-ai-works-limits-strengths-smart-usage-guide https://idea2grow.com/how-ai-works-limits-strengths-smart-usage-guide#comments Tue, 31 Mar 2026 09:31:53 +0000 https://idea2grow.com/?p=584 Key takeaways

• It generates answers based on what sounds right, not what is always true.
• The more widely discussed a topic is, the more accurate AI tends to be.
• AI may guess, hallucinate, or create incorrect details.
• The more specific and structured your prompt, the better the output.
• Always check facts, add your own insights, and never rely on AI blindly.

Table of Contents

People think of intelligence like a magic box. The ones who are really good at using intelligence know what is going on inside the machine. Here is the complete breakdown. You do not need to know a lot about technology to understand it. Artificial intelligence is a tool that can be very helpful if you know how it works. The people who are winning with intelligence are the ones who take the time to learn about the machine underneath the artificial intelligence. They know how the artificial intelligence machine works. That is why they are successful, with artificial intelligence.

Why Understanding AI Changes Everything

There are two kinds of people using AI tools today.

The first group treats AI like a vending machine. They put something in hope something good comes out and get confused or upset when it does not.

The second group gets what is happening inside the machine. They know when to trust it. They know when to check. They get results.

If you do SEO or content marketing or you run a business in 2026 you already use AI.

• Google’s ranking systems use AI.

• The writing tools you use are AI.

• Your competitors use AI to make content. They use AI to find keywords.

“You don’t need a technical background to master AI. You need a mental model a clear picture of what AI is and isn’t doing.”

This article is based on Anthropic’s official AI Fluency Framework: Capabilities & Limitations (Anthropic, 2026). It gives you exactly that mental model. By the end, you will be able to look at any AI output, a blog post, an SEO recommendation, a keyword list and know exactly what kind of output it is, where it might be wrong, and how to fix it.

1

Next Token Prediction

How AI generates words one piece at a time

2

Knowledge

What AI knows — and crucially, what it doesn’t

3

Working Memory

What AI is paying attention to right now

4

Steerability

How much control you actually have over AI outputs

What We Actually Mean by “AI”

AI stands for Artificial Intelligent. When people say “AI is taking over” they are often lumping together several very different technologies. To use AI intelligently you need to separate them.

The AI You Already Use (But Don’t Think About)

Most AI in the world is not generative. The recommendation engine that suggests;

• Your next YouTube video? AI
• The spam filter in your Gmail? AI. 
• The fraud detection system at your bank? AI

These systems sort, rank, classify, and predict. They don’t create anything new. They look at patterns in existing data and make decisions.

These systems are everywhere and they power a lot of how Google’s search algorithm works when deciding which pages to rank.

The AI That Creates New Things

What has changed a lot lately is AI. These are systems that create new things. Like text, images, code, audio and video. When you use ChatGPT, Claude, Gemini, Midjourney or any AI writing assistant you are using these tools.

Even inside generative AI there’s variation. Image generators use diffusion models (they start with noise and sculpt it into an image). Text generators use transformers (they predict what word comes next, over and over). Understanding this distinction is what separates people who get great AI results from those who are constantly confused by it.

KEY DISTINCTION

This entire article is about generative AI specifically the transformer-based text models that power tools like Claude, ChatGPT, and Gemini. These are the ones you’re using to write blog posts, generate SEO outlines, write meta descriptions, and create content at scale.

How AI Gets Its Character

Have you ever imagined Why does AI try to be helpful? Why does it decline certain requests? Why does it sometimes sound confident when it’s completely wrong? None of this is accidental. It’s built in two distinct stages, and each stage leaves a permanent fingerprint on how the AI behaves.

Stage 1: Pre-training — The Document Completer

In the first stage, a model is exposed to enormous quantities of text websites, books, Wikipedia articles, research papers, forums, and much more. It is trained on a single task: given everything written so far, predict what comes next. This is repeated billions of times.

What emerges from pretraining isn’t an assistant at all. It’s a complete document. If you ask it “Who is the prime minister of New Zealand?” it won’t answer your question. It will continue the document in whatever direction seems statistically likely, maybe a civics lesson, maybe a quiz, maybe a list of all presidents. It has no concept of you as a person asking for help.

THINK OF IT THIS WAY

Imagine locking someone in a library for 10 years with every book ever written, and only letting them do one thing: read, and predict what sentence comes next. They’d become incredibly good at knowing what tends to follow what in human language. But they’d have no idea that someone’s standing outside the library wanting help.

Stage 2: Fine-Tuning — The Assistant Layer

To turn that document completely into something useful, the model goes through a second stage: fine-tuning. It’s shown examples of what good assistant behavior looks like. Then it’s guided by human feedback to favor helpful, safe, accurate responses.

This is where the AI learns to treat your input as a request, to answer rather than ramble, to decline harmful instructions, and to acknowledge uncertainty. The assistant personality you experience when using AI is this trained overlay, built on top of the document-completion engine.

WHY THIS MATTERS FOR YOU

The helpful assistant you’re talking to is a learned behavior — a performance of helpfulness trained on top of a pattern-prediction engine. This explains why AI can be very helpful most of the time, but confidently wrong in specific situations. The pattern-predictor underneath doesn’t switch off.

Property 1: Next Token Prediction

This is the single most important thing to understand about modern AI. Everything else flows from it.

At the heart of every modern AI assistant is a remarkably simple operation performed at remarkable scale: given everything written so far, predict what comes next. The system does this one small piece called a “token” at a time. Each word you read in an AI response is the result of this process running hundreds or thousands of times in sequence.

Artificial intelligence(AI) is not searching a database. It is not thinking through a problem. The artificial intelligence is writing, word by word based on patterns the artificial intelligence learned from training. The artificial intelligence is more sophisticated than the predictive text on your phone but the basic way it works is the same.

Artificial intelligence(AI) is not looking for an answer. Artificial intelligence(AI) is writing one, word by word based on what tends to follow what in the things the artificial intelligence was trained on.

AI isn’t looking up an answer. It’s writing one, word by word, based on what tends to follow what.”

The Capability Zone vs. The Edge

The same generative process is always running. What changes is how well-worn the path is:

TASK TYPE	CAPABILITY ZONE	LIMITATION EDGE
Summarization	Excellent — follows highly common patterns	May miss nuanced details or misrepresent source
Explaining concepts	Great for widely-covered topics	Weak for niche, new, or technical edge cases
Writing in a style/format	Strong — mimics patterns well	May lose instructions over long sessions
Stating specific facts	Works for mainstream, well-documented facts	May hallucinate plausible-sounding but false details
Math & formal logic	Simple operations	Pattern-matching ≠ real calculation

Let’s take an example

What This Mean 

When you use AI to write a blog post about a topic that has been explained thousands of times online like “how to lose weight” you will usually get a clear well structured article. That’s AI working in its capability zone.

But when you ask AI to write about something very specific or new like “the best diet plan for a 22-year-old student in United State who wants to gain muscle on a low budget in 2026” you’re pushing toward the edge. The AI will still write smoothly, but it may guess details, create information that isn’t fully accurate, or give advice that sounds right but isn’t completely reliable.

ACTION FOR CONTENT CREATORS

Use AI confidently for structure, drafts, and frameworks. But always personally verify specific claims, statistics, business names, and recent events. AI fluency + human fact-checking = unstoppable content.

Property 2: Knowledge

AI models learn by looking at a lot of text from the internet books and other things that are written. The model goes through this text many times and tries to guess what word comes next. This helps the model understand language and things like ideas and facts. The model learns about relationships between things too. This is how the model knows things, about the world and language and concepts and facts. The model knows things.

It is also the only way it knows things.

The model doesn’t browse the web in real time (unless explicitly given tools to do so). It doesn’t have experiences. Its knowledge was fixed at the end of its training — a specific moment called the knowledge cutoff.

Why Knowledge Is Uneven

AI’s knowledge isn’t uniform. The question to ask is never “does the AI know this?” The right question is: how well-represented was this topic in the training data?

THE REPRESENTATION RULE

Well-represented = reliable knowledge. Topics that appear frequently, recently, and consistently online are easier for AI to handle. These include common subjects like basic science, popular programming languages, general history, and widely-used marketing strategies.

Poorly represented = risky knowledge. Topics that are rare, very new, or highly specific are harder for AI to get right. This includes local business details, recent updates, niche industries, or anything that isn’t widely available online.

Property 3: Working Memory (The Context Window)

When you talk to an intelligence all the important stuff for the conversation is stored in a special area called the context window. This area holds your instructions any documents you have sent the intelligences previous answers and the entire conversation so far.

The artificial intelligence can only look at what’s inside this area. It cannot look at anything outside of this area. Not at conversations unless the system has a way to remember things not at external websites not at your files. The artificial intelligence only uses what is, in the context window to understand what you are talking about.

Two Critical Consequences

1. The window has a hard size limit. When a conversation or document exceeds it, something gets cut off. The model simply stops being able to reference content from earlier in the conversation it literally cannot see it anymore.

2. By default, the window empties between sessions. When you start a new conversation, the AI has no memory of what you discussed before unless the platform (like Claude.ai’s memory feature) explicitly provides that history.

“Working memory is the property with the hardest edge. Things work until they don’t — often with a cliff rather than a gradient.”

This Explains So Much

Have you ever noticed that after a very long AI conversation, the output starts getting worse? The AI seems to forget your original instructions, or starts giving responses that contradict what you established earlier. That’s the context window filling up. Earlier context fades. Later instructions start to dominate.

PRO TIP FOR LONG PROJECTS

For big, ongoing projects like a full website SEO audit, a content calendar, or a multi-week campaign break your work into focused sessions. Start each new session with a short context summary: who you are, what project you’re working on, and what you need today. This keeps the AI working in its capability zone every single time.

Practical Working Memory Rules

SITUATION	DO THIS
Starting a new project	Give AI full context upfront in a structured brief
Long research conversation	Summarize key decisions at each milestone and paste them in fresh sessions
Uploading long documents	Ask targeted, specific questions instead of “summarize everything”
Multi-day work	Keep a running “context note” doc to paste at the start of each session

Property 4: Steerability

The model learns what it means to be an assistant by fine-tuning. This means it knows how to respond in a way follow the rules that the user sets and break down big tasks into smaller steps. The result is a system that you can control well. You can tell the model what role to play what tone to use, what format to follow, how long to make something and what rules to follow.. It will do all of those things.

This is really amazing. But being able to control the model has a limitation: just because the model follows your instructions does not mean it understands what you really want.

The model does what you tell it to do by finding a pattern and going with it. There is always a difference, between what you want the model to do and what it actually does. The interesting mistakes happen because of this difference. The model learns to be an assistant but it does not really understand what being a helpful assistant means.

The Steerability Spectrum

What is control: control is when you give instructions that’re short and to the point. You say things like “Respond as a table” or “Keep it under 150 words”. You also say “Use bullet points, not paragraphs” or “Start every section with a question”. The Steerability Spectrum is about instructions like these. High control instructions are easy for AI to follow because it is clear what you want. You can tell away if the AI is doing what you asked.

What is Degraded control: Degraded control is when you give instructions that’re not clear. The Steerability Spectrum shows that degraded control instructions are abstract or hard to understand. You might say something like “Make this sound more professional” or “Write like a thought leader”. You could also say “Optimize this for SEO”. These instructions are not clear because what you mean by “professional” might be different, from what the AI thinks it means. The Steerability Spectrum is important because it helps us understand how to give instructions to AI. Degraded control instructions can cause problems because the AI might not do what you want it to do. The Steerability Spectrum and high control instructions are better because they are clear and easy to follow.

STEERABILITY IN PRACTICE – SEO META DESCRIPTIONS

Vague: “Write a good meta description for my SEO services page.”

Specific: “Write a meta description for my SEO services page. Max 155 characters. Target keyword: ‘affordable SEO services USA’. Include a clear benefit and a soft call to action. Do not use the word ‘best’.”

The Skill: Closing the Gap

Becoming skilled at steerability means learning to close the gap between your intent and your words. The more you can specify concrete, verifiable constraints, the more reliably you’ll get what you actually want.

BUILD YOUR PROMPT TEMPLATE LIBRARY

For recurring tasks — meta descriptions, blog outlines, email subject lines, schema markup, service page copy — build reusable prompt templates with specific constraints baked in. This is how professional AI users operate. Less rethinking, more reliable output, faster delivery.

When Properties Collide — Understanding AI Failure Modes

The four properties do not work alone. Most of the time when things go wrong with intelligence it is because two of the properties are not working well together at the same time. When you understand the four properties you are not surprised by intelligence mistakes anymore. You start to see what kind of problem you are dealing with when artificial intelligence fails. The four properties are important to consider when you are trying to figure out what went wrong with intelligence

The Confident Hallucination

Next Token Prediction (generating what sounds plausible) + Knowledge Gap (a fact the model doesn’t actually know). Result: AI states a specific statistic, name, or citation that sounds exactly right but is completely fabricated.

Instruction Drift

Working Memory (early context fading) + Steerability (later instructions overwriting earlier ones). Result: You start a long project with clear rules, and over time, the AI begins to ignore some of them.

Fluent but Wrong Math

Next Token Prediction (pattern-based fluency) + Steerability limits (no real mathematical reasoning). Result: AI presents a calculation that looks correct and well-structured but arrives at the wrong answer.

Sycophantic Agreement

Trained behavior (agreeing with the user) + Next Token Prediction (continuing your framing). Result: AI agrees with incorrect assumptions instead of challenging them, which can lead to poor decisions.

How to Apply This Framework in Work & Academy

Now let’s make this practical. Here’s how the four properties translate directly into your Work & Academy.

Now lets make this real. Think about what you do every day. Assignments, research, presentations, reports and work.

The four properties of AI affect how well it works in each of these areas. If you know what AI is good, at and where it falls short you can use it effectively. And avoid errors that could cost you grades, trust or results.

Using Artificial Intelligence for Research and Study

Artificial Intelligence is really good at helping you with subjects. Like basic ideas, summaries or explanations from your textbooks. It can make things simpler help you make notes. You will understand things faster.

You have to be careful with subjects that are very specific, new or complicated. Artificial Intelligence might miss some details give you old information or sound right but actually be wrong. You should always check facts with your textbooks, journals or sources that you trust.

Using Artificial Intelligence for Assignments and Writing

Artificial Intelligence is very good at organizing content. Essays, reports and presentations. It helps you put your ideas in order keep everything flowing smoothly and follow the formats.

However if you want your work to be really good you have to add your thoughts. You cannot just rely on Artificial Intelligence to give you understanding, analysis, examples and critical points. If you only use Artificial Intelligence your work might look good. It will not be very deep.

Using Artificial Intelligence for Problem Solving and Learning

Artificial Intelligence can help you understand steps guide you through problems and break down ideas.

For subjects like math, logic or technical problems do not just trust the answer that Artificial Intelligence gives you. Artificial Intelligence might make mistakes. You should use it to learn how to do things not just copy the answer.

Using Artificial Intelligence for Presentations and Communication

Artificial Intelligence is great for creating outlines for presentations content for slides and making your writing, like emails, reports or explanations.

It works best when you give it instructions:

• Topic
• Audience
• Purpose

The specific you are the better it will be.

THE 5-STEP AI WORKFLOW FOR SEO PROFESSIONALS

✓

Define the task clearly — what property zone am I working in?

✓

Provide full context — don’t rely on AI to fill in gaps (working memory)

✓

Use specific, verifiable instructions — maximize steerability

✓

Generate the output — let AI work in its strength zone

✓

Verify and add the human layer — facts, experience, original insight

Conclusion

Artificial intelligence(AI) is not something that can just magically do things for you. It is a system that does things in a way it has its own limits and it works really well when you know how it works. The thing that sets people who’re good at using artificial intelligence apart from people who are not so good at it is not that they have access to artificial intelligence but that they actually understand how it works. When you figure out how artificial intelligence comes up with answers, where it gets its information, from how it remembers things and how to tell it what you want it to do you can stop trying to guess what it will do and start making it do what you want.

Whether you are doing homework making something or doing your job using intelligence to go fast and also using your own brain to check things and think about what you are doing is what gets you good results that you can really trust.

Learn: How to Write Clear and Direct Prompts for Claude AI

]]> https://idea2grow.com/how-ai-works-limits-strengths-smart-usage-guide/feed 1 https://idea2grow.com/how-to-build-a-resume-for-free-without-signing-up https://idea2grow.com/how-to-build-a-resume-for-free-without-signing-up#respond Tue, 24 Mar 2026 14:34:12 +0000 https://idea2grow.com/?p=557

How-to Guide

How to Build a Resume for Free Without Signing Up (2026 Guide)

Learn how to build resume free no signup using simple steps and create a professional CV instantly.

Build Resume Now

Why Build Resume Without Signup?

Many tools ask for accounts, emails, and subscriptions. But you can now create a resume instantly without wasting time on registration.

Main advantages:

• No account required
• Fast and easy process
• Instant download
• Completely free

Step-by-Step Guide to Build Resume Free

Step 1: Open the Resume Builder

Go to the free tool and start building your resume directly in your browser.

Step 2: Enter Your Details

Add your personal information, education, skills, and experience.

Step 3: Choose a Template

Pick a clean and professional design that fits your job role.

Step 4: Download Instantly

Download your resume without signup or payment.

Create Resume Free

Tips for Better Resume

• Keep it simple: Avoid unnecessary design
• Use keywords: Match job descriptions
• Highlight skills: Focus on strengths
• Proofread: Remove errors

FAQs

Can I build resume free no signup?

Yes, you can create and download your resume without creating an account.

Is it completely free?

Yes, there are no hidden charges or subscriptions.

Can I download instantly?

Yes, your resume is ready to download in seconds.

]]> https://idea2grow.com/how-to-build-a-resume-for-free-without-signing-up/feed 0 https://idea2grow.com/free-resume-builder-online https://idea2grow.com/free-resume-builder-online#respond Tue, 24 Mar 2026 14:19:56 +0000 https://idea2grow.com/?p=551

Informational Guide

Free Resume Builder Online: Create a Professional Resume in Minutes

Discover the easiest way to craft a compelling, perfectly formatted resume without spending a dime.

Create Your Resume Now

What Is a Free Resume Builder?

A free resume builder online is a simple tool that helps you create a professional CV without design or formatting issues. You just enter your details, and the system generates a clean resume instantly.

Why Use an Online Resume Builder?

Recruiters spend only a few seconds reviewing resumes. A well-structured resume builder helps you stand out quickly.

Top benefits include:

• No formatting issues
• Professional templates
• Works on any device
• Instant PDF download

Key Features of idea2grow Resume Builder

Unlike many tools, this builder is completely free and does not require signup. It focuses on clean design and fast results.

How It Compares

Compared to Word or design tools, resume builders remove complexity and save time.

Tips for Creating a Professional Resume

• Use action words: Managed, created, led
• Show results: Use numbers and achievements
• Keep it relevant: Focus on job-related skills
• Proofread: Avoid small mistakes

Build Resume Free

FAQs

Is this resume builder free?

Yes, it is completely free to use.

Do I need to sign up?

No, you can create and download your resume without signup.

Is it ATS-friendly?

Yes, it uses clean formatting suitable for job applications.

]]> https://idea2grow.com/free-resume-builder-online/feed 0 https://idea2grow.com/how-audit-ai-visibility-for-your-brand https://idea2grow.com/how-audit-ai-visibility-for-your-brand#respond Fri, 06 Mar 2026 06:08:17 +0000 https://idea2grow.com/?p=514 AI Visibility is one of the prominent topic to discuss. Every business in the world wants their brand listed in the AI Chat bot- ChatGPT, Gemini, Perplexity, Claude, and google overview. Many of the Top brands pays high to make there brand available in the AI. Many SEO expert and agency owner still don’t know the easiest way to check whether your brand is been cited on AI search or not.

Table of Contents

What is Audit AI visibility ?

A Audit AI visibility is a process to check whether your brand, content, and products are being cited and recommended across AI chatbots and search engines like ChatGPT, Google Gemini, Perplexity, and Claude. It helps you understand your presence in AI-powered search results and answer engines.

In this blog, you will learn the how to check the AI visibility Audit for your “brand”.

Check: AI tools for mobile search visibility

Quickest 4 steps your can Audit AI Visibility of your Brand

Step 1: Check AI Answers for Your Key Queries

Test 10-20 of your most important queries across platforms:

Query	Google AI Overview	ChatGPT	Perplexity	You Cited?	Competitors Cited?
[query 1]	Yes/No	Yes/No	Yes/No	Yes/No	[who]
[query 2]	Yes/No	Yes/No	Yes/No	Yes/No	[who]

Query types to test:

• “What is [your product category]?”
• “Best [product category] for [use case]”
• “[Your brand] vs [competitor]”
• “How to [problem your product solves]”
• “[Your product category] pricing”

Step 2: Analyze Citation Patterns

When your competitors get cited and you don’t, examine:

• Content structure — Is their content more extractable?
• Authority signals — Do they have more citations, stats, expert quotes?
• Freshness — Is their content more recently updated?
• Schema markup — Do they have structured data you’re missing?
• Third-party presence — Are they cited via Wikipedia, Reddit, review sites?

Step 3: Content Extractability Check

For each priority page, verify:

Check	Pass/Fail
Clear definition in first paragraph?
Self-contained answer blocks (work without surrounding context)?
Statistics with sources cited?
Comparison tables for “[X] vs [Y]” queries?
FAQ section with natural-language questions?
Schema markup (FAQ, HowTo, Article, Product)?
Expert attribution (author name, credentials)?
Recently updated (within 6 months)?
Does the heading structure match query patterns?
Are AI bots allowed in robots.txt?

Step 4: AI Bot Access Check

Verify your robots.txt allows AI crawlers. Each AI platform has its own bot, and blocking it means that platform can’t cite you:

• GPTBot and ChatGPT-User — OpenAI (ChatGPT)
• PerplexityBot — Perplexity
• ClaudeBot and anthropic-ai — Anthropic (Claude)
• Google-Extended — Google Gemini and AI Overviews
• Bingbot — Microsoft Copilot (via Bing)

Check your robots.txt for Disallow rules targeting any of these. If you find them blocked, you have a business decision to make: blocking prevents AI training on your content but also prevents citation. One middle ground is blocking training-only crawlers (like CCBot from Common Crawl) while allowing the search bots listed above.

Cited your brand in AI overview

Frequently Asked Question

1. What is Audit AI visibility ?

A Audit AI visibility is a process to check whether your brand, content, and products are being cited and recommended across AI chatbots and search engines like ChatGPT, Google Gemini, Perplexity, and Claude. It helps you understand your presence in AI-powered search results and answer engines.

2. Why is AI visibility important for SEO?

AI visibility is critical because AI-powered answer engines are becoming the primary way users find information. Being cited by AI models drives brand authority, increases website traffic through AI recommendations, and improves your overall online visibility in the AI era of search.

3. How do I check if my brand is cited in AI search results?

Follow the 4-step method: (1) Test 10-20 priority queries in ChatGPT, Gemini, Perplexity, and Google AI Overview. (2) Analyze citation patterns against competitors. (3) Check your content extractability for AI. (4) Verify your robots.txt allows AI bot access.

4. What queries should I test for AI visibility?

Test these query types: (1) ‘What is [your product]?’ (2) ‘Best [product] for [use case]’ (3) ‘[Your brand] vs [competitor]’ (4) ‘How to [problem your product solves]’ (5) ‘[Product] pricing’. These represent the most common AI-answered queries.

5. What are AI citation patterns and why do they matter?

Citation patterns show which competitors rank in AI answers and why. Analyze their content structure, authority signals, freshness, schema markup, and third-party presence. Understanding these patterns helps you optimize your content for AI rankings.

6. What is content extractability and how does it affect AI rankings?

Content extractability measures how easily AI models can pull information from your pages. Use clear definitions, self-contained answer blocks, statistics with sources, comparison tables, FAQs, structured data (schema), expert attribution, fresh updates (within 6 months), and proper heading structure for better AI extractability.

7. Which AI bots do I need to allow in robots.txt?

Allow these AI bots: GPTBot & ChatGPT-User (OpenAI), PerplexityBot (Perplexity), ClaudeBot & anthropic-ai (Anthropic), Google-Extended (Google Gemini/AI Overview), Bingbot (Microsoft Copilot). Blocking them prevents both AI training on your content AND citation in AI results.

8. Should I block AI bots in robots.txt?

It depends on your strategy. Blocking prevents AI training on your content but also prevents AI citations. A middle ground: allow search-and-citation bots (GPTBot, PerplexityBot, etc.) but block training-only crawlers (CCBot from Common Crawl). This balances visibility with content protection.

9. What schema markup do I need for AI visibility?

Implement: FAQ schema (for Q&A content), HowTo schema (for instructional content), Article schema (for blog posts), Product schema (for product pages), and Organization schema (for brand authority). Structured data helps AI models understand and extract your content more accurately.

10. How often should I audit AI visibility?

Conduct AI visibility audits quarterly (every 3 months) to track changes in citation patterns, monitor competitor performance, and adjust your AI SEO strategy. Monthly checks are recommended for high-priority keywords targeting your top markets.

]]> https://idea2grow.com/how-audit-ai-visibility-for-your-brand/feed 0 https://idea2grow.com/clear-and-direct-prompts-for-beginners https://idea2grow.com/clear-and-direct-prompts-for-beginners#respond Thu, 05 Mar 2026 05:44:38 +0000 https://idea2grow.com/?p=487 Most people use Claude AI every day — and get average results. Not because Claude is bad. But because their prompts are vague.

In this guide, you’ll learn exactly how to write clear and direct prompts that get you specific, powerful, and ready-to-use answers — even if you’ve never used AI before.

This is Chapter 2 of the Prompt Engineering for Beginners series by Digital Idea2grow. Read Chapter 1 here

Digital AI

What is a Clear and Direct Prompt?

Let’s start with the basics.

Every time you open Claude AI and type something that message is called a prompt.

It could be:

• “Write a blog post for AI Automation”
• “Give me SEO key word tips”
• “Help me write an professional business email”
• “Write report for Market Research for sales strategy”

That’s a prompt. Simple.

But here’s where most beginners go wrong.

They type something short and vague and then wonder/worried why Claude’s answer feels generic, won’t meet the expectation, boring, or off-topic.

The problem is never Claude. The problem is the instruction.

A clear and direct prompt means you tell Claude exactly what you want, how you want it, and what to avoid before it starts writing.
By Sanjivan Dhakal | Founder – digital idea2grow

Think of it like ordering food at a restaurant.

If you say “give me food” — the waiter is confused. They might bring you anything.

But if you say “I want a medium spicy chicken pizza, thin crust, no onions, extra cheese” — you get EXACTLY what you wanted. (Note*-you have express your specific what you want and waiter delivery as per your expectation.)

That’s the difference between a vague prompt and a clear and direct prompt.

A clear prompt always answers these 5 questions:

Example:

Question	Example
What do you want?	A blog intro
For who?	Digital Idea2grow readers
About what?	On-page SEO for beginners
In what tone?	Simple and confident
How long?	150 words

When Claude has all 5 answers it delivers results that feel like they were written by a human expert on your team.

Why Vague Prompts Fail Every Time

When your prompt is vague, Claude does its best but it has to fill in the blanks itself. And when Claude fills in those blanks, it defaults to the most generic, average, middle-ground answer possible.

Why? Because it’s trying to be safe and broadly useful for everyone.

Here what does it mean,
In my case, Claude knows my business but I need to specific the Claude to understand my content and strategy towards my specific niche to understand by brand voice.

But you’re not everyone. You are Digital Idea2grow an SEO, AEO E-Commerce SEO agency targeting the US market/WORDLD WIDE. You need content that speaks to YOUR audience, in YOUR voice, about YOUR niche.

– THINK IN YOUR BUSINESS OR YOUR WORK PERSPECTIVE

Claude is not a mind reader. It only knows what you type.

Weak Prompt vs Strong Prompt — Real Examples

In this blog you will be learning about the Weak and Strong Prompt. Which means provide the clear instructions prompt that provide Claude with a clear instruction, what the user wants from the Claude to be specific and clear answer.  

Understand the Weak Prompt  

 Example:  

You type to the Claude:  
 
Claude: “Write an SEO blog post.” 

And Claude Answer with: “Here is an SEO blog post for you! SEO stands for Search Engine Optimization. It is the process of optimizing your website so that it ranks higher on search engines like Google. There are many factors that affect SEO including keywords, backlinks, page speed” 
 
Generic. Boring. No direction. Could be for ANY website. 

Understand the Stronger Prompt  

Example: 

This prompt is quite specific as per your niche, which you shall get your expected answer 

Now you Provide the niche specific Prompt to Claude:  
 
Claude: “Write a 150-word blog intro for Digital Idea2grow targeting the keyword ‘on-page SEO for beginners’. Tone: simple and confident. Skip the preamble, go straight into the hook. End with a curiosity line that makes them read more.” 
 
And Claude replies: “Most websites never rank on Google — not because they have bad products, but because they have bad on-page SEO. The good news? Fixing it doesn’t require a computer science degree. Whether you’re running a business, a blog, or an SEO agency like Digital Idea2grow — mastering on-page SEO is the single fastest way to get Google to notice you. And in this guide, we’re breaking it down so simply that even a complete beginner can start winning search rankings today. Let’s dive in…” 

Specific. Punchy. Targeted. Ready to publish. 

Frequently Asked Question

1. What is a clear and direct prompt?

A clear and direct prompt is an instruction that tells Claude AI exactly what you want, how you want it, and what to avoid. It answers five key questions: what you want, for who, about what, in what tone, and how long.

2. Why do vague prompts fail with Claude AI?

Vague prompts fail because Claude has to fill in the blanks itself, defaulting to generic, average answers. Claude only knows what you type, so unclear instructions lead to unfocused results.

3. What are the 5 questions a clear prompt should answer?

Every clear prompt should answer: What do you want? For who? About what? In what tone? How long? These elements ensure Claude delivers specific, targeted, and ready-to-use results.

4. How do I improve my Claude AI prompts?

Improve your prompts by being specific about your requirements. Include details like target audience, desired tone, length, format, and what to avoid. Replace vague requests with precise instructions.

5. What is the difference between weak and strong prompts?

Weak prompts are vague like ‘Write an SEO blog post’ while strong prompts include specific details like word count, target keyword, tone, audience, and format requirements, resulting in targeted, publishable content.

]]> https://idea2grow.com/clear-and-direct-prompts-for-beginners/feed 0 https://idea2grow.com/prompt-engineering-for-beginners https://idea2grow.com/prompt-engineering-for-beginners#respond Wed, 04 Mar 2026 07:03:40 +0000 https://idea2grow.com/?p=476

As you guys know about that, people use the prompt in a very basic and vague way.  just like, for example:  What is SEO? As a beginner, who can I walk through this?  

Prompt Engineering for Beginners: How Claude Processes Your Formula

Step-by-Step Breakdown of the CLAUDE Formula

Formula:  =CLAUDEMESSAGES(“{PROMPT}”, “{MODEL_VERSION}”, “system”, “{SYSTEM_PROMPT}”) 

1. 1. Go the Claude

2. 2. Type this formula =CLAUDEMESSAGES(“{PROMPT}”, “{MODEL_VERSION}”, “system”, “{SYSTEM_PROMPT}”)

3. 3. And insert your prompt, Claude version which you are using (I am using sonnet 4.6), in system “You basically enter your label like: Beginner, key words, tags as per your prompt context”, lastly enter your prompt what do you want to ask “Claude”

4. 4. These steps you can use in while prompting with the Claude AI

Why Structured Prompts Give Better Answers Than Basic Questions

=CLAUDEMESSAGES (“User: I am an agency owner”, “claude-sonnet-4-6”, “system”, “I am a startup founder running an SEO agency with zero prior business knowledge. I am good at SEO and want to work with Travel Agencies. Can you give me a 30-day execution plan to land and serve my first travel agency client?”)

Prompt Engineering for Beginners: How Claude Processes Your Formula

In the below image it has shown that how Claude process the Prompt. For this I have insert this formula =CLAUDEMESSAGES (“User: what is seo”, “claude-sonnet-4-6”, “system”, “I am a beginner in SEO so, please let me know how I can learn SEO from fundamentals”). After inserting formula Claude process as per your intend and solve your complex problem in a easiest way.

How Beginners Can Use Prompt Engineering in Google Sheets with Claude AI

Step-by-Step Breakdown of the CLAUDE Formula

1. 1. First go to your google sheets

2. 2. Then click on the Extension > Add-ons > Get add-ons

3. 3. Search Anthropic and install

4. 4. Purchase API Key from this link https://platform.claude.com/ and You can use it into your google sheet like this

• • Install Claude from extension

• • Add: KEY words, Tags, context in heading like I have shown you in the image as I have mention Key word being a SEO expert. As per your profession role add heading like that

• • And Claude Slide bar open and insert your formula and boom you get the instant result for different Keyword, tags, context. Mainly, SEO experts are being used faster and more efficiently.

• • If You don’t have idea, then you can simply use that given formula in Claude. Try this AI for your E-commerce brand: https://idea2grow.com/meta-title-and-description-generator/

Frequently Asked Question

Anthropic has said it will not back down in a fight with the US Department of Defense (DoD) over how its artificial intelligence (AI) technology is used.
The firm’s chief executive Dario Amodei said on Thursday that his company would rather not work with the Pentagon than agree to uses of its tech that may “undermine, rather than defend, democratic values.”

His comments come two days after a meeting with US Secretary of Defense Pete Hegseth over demands that Anthropic accept “any lawful use” of its tools. It ended with a threat to remove Anthropic from the DoD’s supply chain.
“These threats do not change our position: we cannot in good conscience accede to their request,” Amodei said.

At issue for Anthropic is the potential use of its AI tools like Claude for two purposes: “Mass domestic surveillance” and “Fully autonomous weapons.”
Amodei said “such use cases have never been included in our contracts with the Department of War, and we believe they should not be included now.”
The Department of War is a secondary name for the Defense Department under an executive order signed by US President Donald Trump in September.
“Should the Department choose to offboard Anthropic, we will work to enable a smooth transition to another provider,” Amodei said.
An Anthropic spokeswoman added on Thursday that while the company received updated wording from the DoD for its contract on Wednesday night, it represented “virtually no progress on preventing Claude’s use for mass surveillance of Americans or in fully autonomous weapons.”
“New language framed as compromise was paired with legalese that would allow those safeguards to be disregarded at will,” she said. “Despite [the Department of War’s] recent public statements, these narrow safeguards have been the crux of our negotiations for months.”
A representative of the Defense Department could not be reached for comment.
Emil Michael, the US Undersecretary for Defense, personally attacked Amodei on Thursday night, writing on X that the executive “wants nothing more than to try to personally control the US Military and is ok putting our nation’s safety at risk.”

In an interview with CBS News, Michael said: “At some level, you have to trust your military to do the right thing.”
The uses of AI that Anthropic is fearful of are already barred by the law and by Pentagon policies, he said. And asked why the Pentagon would not agree to contract language demanded by Anthropic, he said: “We do have to be prepared for what China is doing.”

A Pentagon official previously told the BBC that should Anthropic not comply, Hegseth would ensure the Defense Production Act was invoked on the company.
The act essentially gives a US president the authority to deem a given company or its product so important that the government can require it to meet defence needs.
But Hegseth also threatened to label Anthropic a “supply chain risk”, meaning the company would be designated as not secure enough for government use.
A former DoD official who asked not to be named told the BBC on Thursday that Hegseth’s grounds for either measure were “extremely flimsy”.
A person familiar with the negotiations who asked not to be named said tensions between Anthropic and the Pentagon “go back several months,” before it was publicly known that Claude was used as part of a US operation to seize Venezuelan President Nicolás Maduro.
While Amodei did not specify exactly how Anthropic could be or had been used by the DoD for mass surveillance or fully autonomous weapons, he wrote in a company blog post that AI can be used to “assemble scattered, individually innocuous data into a comprehensive picture of any person’s life – automatically and at massive scale.”
“We support the use of AI for lawful foreign intelligence and counterintelligence missions,” Amodei said. “But using these systems for mass domestic surveillance is incompatible with democratic values.”
As for AI being used in weapons, Amodei said even today’s most advanced and capable AI systems “are simply not reliable enough to power fully autonomous weapons.”
“We will not knowingly provide a product that puts America’s warfighters and civilians at risk,” Amodei said. “Without proper oversight, fully autonomous weapons cannot be relied upon to exercise the critical judgment that our highly trained, professional troops exhibit every day. They need to be deployed with proper guardrails, which don’t exist today.”
He added that Anthropic had “offered to work directly with the Department of War on R&D to improve the reliability of these systems, but they have not accepted this offer.”
Hegseth had demanded the Tuesday meeting with Amodei, a source previously told the BBC.
Artificial intelligence

source: bbc | Anthropic