What is the difference between AEO and GEO?

AEO (Answer Engine Optimization) is specifically about getting cited as a source when AI engines answer questions. GEO (Generative Engine Optimization) is broader — optimizing for inclusion in any AI-generated output, including product recommendations, comparisons, lists, and summaries. AEO is a subset of GEO.

Do I still need traditional SEO?

Yes. AEO doesn't replace SEO — it complements it. Traditional Google search still drives the majority of organic traffic for most B2B and ecommerce businesses. AI Overviews appear on roughly 47% of searches, but they often pull from the top SEO results. Strong SEO foundations make AEO 5-10x more effective.

How do you actually track AI citations?

We run a defined prompt set (30-100 queries depending on package) across ChatGPT, Perplexity, Claude, Gemini, and Google AI Overviews on a weekly cadence. We log whether your brand is mentioned, where you appear in the response, what context, and which competitors are cited alongside or above you.

How long until I see results?

Faster than traditional SEO, slower than paid ads. Schema and structural fixes get reflected by AI engines within 2-4 weeks. Citation increases on existing pages: 4-8 weeks. New AEO content getting indexed and cited: 8-16 weeks. Compounding effects: 4-6 months.

What is the pricing for AEO services?

Three packages. Starter at $2,500/month for SMBs. Growth at $5,500/month for $5M-$25M brands. Enterprise from $12,500/month for $25M+ brands. Quarter-to-quarter contracts with no 12-month lock-ins. INR pricing available for India clients.

Will AI eventually replace traditional search?

For some use cases, yes. For others, no. Research-heavy queries increasingly happen in AI tools. Transactional queries still happen in Google. The right strategy is to optimize for both surfaces — your content engine produces material that ranks in SERPs AND gets cited by AI.

How to Build an MVP Without Coding in 2026 (Founder Guide)

Quick answer

To build an MVP without coding in 2026: validate the problem with real users, write a clear feature spec, use an AI app builder like Emergent.sh to generate a full-stack app from plain English, test the core flows, then launch and focus on getting users. The biggest mistakes are over-building before validation and neglecting distribution after launch.

"I have an idea but I can't code" used to end the conversation. In 2026 it does not. Here is how to build and launch an MVP without writing code — done properly.

Step 1: Validate before you build

The cheapest MVP is a conversation. Talk to 10–20 potential users first. Confirm the problem is real and painful before generating anything. Most failed products skip this.

Step 2: Write a tight spec

Define the one core job your MVP does, the key screens, the data it stores, and the main user actions. Resist adding features — an MVP proves one thing.

Step 3: Generate it with an AI app builder

Use a tool like Emergent.sh to turn that spec into a real full-stack app — front end, back end, database — from plain English. No coding, but the code is real and yours.

Generate your MVP free

We set up Emergent.sh for clients and run the marketing around it. Start free, or have us do it for you.

Try Emergent.sh free → Read our full review →

Step 4: Test the core flow

Click through the single most important user journey end to end. Fix friction. Ignore nice-to-haves.

Step 5: Launch and get users

Ship it. Then the real work: a landing page, clear positioning, SEO/AEO, and a content + paid engine to drive signups.

Mistakes to avoid

Building before validating the problem
Cramming in features beyond the core job
Treating "built" as "done" — distribution is the hard part
Ignoring that you own hosting/scaling

The honest truth

Building is now the easy 20%. Distribution is the 80%. That is exactly where GrowwithBA plugs in after the MVP is live.

FAQ

Can I really build an MVP without coding?

Yes — AI app builders like Emergent.sh generate a full-stack app from a plain-English spec, so you can validate and launch without engineers.

What is the biggest mistake building a no-code MVP?

Two: building before validating the problem, and treating launch as the finish line when distribution is the real work.

Ready to move?

Start Emergent.sh free through our link, or read our full hands-on review first.

Try Emergent.sh free → Read the Emergent.sh review →

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How to build an MVP without coding in 2026