Try this: ask ChatGPT about the best project management tools for startups. You'll get recommendations for Asana, Notion, Monday.com — companies that barely existed when GPT-4's training data was collected. But here they are, embedded in AI knowledge.
While founders obsess over SEO rankings and keyword optimization, they're missing the bigger picture: LLMs are becoming the new search engines, and the companies that show up in AI responses are the ones that will dominate future discovery.
The question isn't whether your startup will need AI visibility — it's how quickly you can establish it before your competitors do.
Why LLMs matter more than Google search
We're witnessing the fastest shift in information consumption since Google dethroned libraries. In 2024, ChatGPT reached 100 million weekly active users. By comparison, it took Google Search eight years to reach that milestone.
The behavior change is even more dramatic among decision-makers:
- 67% of software buyers now start their research with AI tools, not search engines
- B2B researchers use ChatGPT for vendor discovery 3x more than LinkedIn
- Enterprise buyers trust AI-generated recommendations because they feel "unbiased" compared to traditional advertising
When a CTO asks Claude for cybersecurity vendor recommendations, or a founder queries ChatGPT about fundraising platforms, your startup either shows up or gets left behind.
The AI discovery advantage
Zero-click answers: Users get recommendations without visiting comparison websites
Context-aware suggestions: AI considers the user's specific needs and constraints
Trust by proxy: Recommendations feel objective because they come from "AI," not ads
Conversational discovery: Users can ask follow-up questions about your product immediately
How LLMs actually learn about your startup
Here's the uncomfortable truth about AI training: LLMs don't crawl your perfectly optimized landing page or read your meta descriptions. They're trained on massive datasets of text from across the internet — and media coverage makes up a disproportionate share of high-quality training data.
What gets included in AI training data:
- News articles and media coverage: High-authority content from established publications
- Industry reports and analysis: Research papers, market studies, and trend analyses
- Interviews and quotes: Founder perspectives captured in media stories
- Product reviews and comparisons: Third-party evaluations and expert opinions
- Community discussions: Reddit threads, forum posts, and social media conversations
Notice what's missing? Your marketing copy, your About Us page, your carefully crafted product descriptions. LLMs learn about your startup through what others say about you, not what you say about yourself.
The media coverage multiplier effect
When TechCrunch writes about your funding round, or when a journalist quotes your founder about industry trends, that coverage doesn't just reach human readers. It becomes part of the information ecosystem that trains future AI models.
This creates a compounding effect: media coverage increases your chances of appearing in AI responses, which drives more visibility, which leads to more media coverage.
The AI training pipeline
Why traditional SEO won't save you
If you're still thinking about AI visibility in terms of traditional SEO, you're fighting the last war. LLMs don't rank web pages — they synthesize information from their training data to generate responses.
Traditional SEO optimization like keyword density, meta tags, and page speed won't help your startup appear in ChatGPT responses because LLMs aren't searching the web in real-time. They're drawing from pre-trained knowledge.
SEO vs. AI optimization:
Traditional SEO
- • Optimizes for search engine crawlers
- • Focuses on keywords and backlinks
- • Aims for high SERP rankings
- • Controls content on your owned properties
- • Drives traffic to your website
AI Optimization
- • Appears in AI training datasets
- • Focuses on authoritative mentions
- • Aims for AI response inclusion
- • Requires third-party validation
- • Drives direct recommendations
Strategic approaches to AI visibility
Getting your startup into AI knowledge bases requires a fundamentally different approach than traditional marketing. You can't optimize your way in — you have to earn your way in through authoritative mentions and media coverage.
High-impact tactics:
- Thought leadership articles: Position your founders as experts in industry publications
- Product launch coverage: Get featured in tech media for new releases and updates
- Industry trend commentary: Provide expert quotes for journalist stories about your sector
- Research and data sharing: Publish industry reports that get cited by other publications
- Conference speaking: Generate coverage from industry events and speaking engagements
The key is becoming a reliable source that journalists turn to when they need expert perspectives on your industry.
Testing your current AI presence
Before you can improve your AI visibility, you need to understand where you currently stand. Here's how to audit your startup's presence in major LLMs:
AI presence audit checklist
Direct mentions: Ask ChatGPT directly about your company and product
Category queries: Ask for recommendations in your product category
Comparison requests: Ask AI to compare you with competitors
Problem-solving contexts: Ask about solutions to problems your product solves
Industry expertise: Ask about trends in your industry and see if your insights appear
Building your AI visibility strategy
The most successful startups treat AI visibility as a long-term content and PR strategy, not a quick optimization hack. It requires consistent effort to build the kind of authoritative presence that gets included in AI training data.
The 90-day AI visibility plan:
Month 1: Foundation Building
- • Audit current AI presence across major LLMs
- • Identify key journalists covering your industry
- • Develop thought leadership content themes
- • Create founder expert profiles for media databases
Month 2: Content and Outreach
- • Pitch industry trend commentary to target publications
- • Respond to journalist queries on platforms like HARO
- • Publish research or data studies in your field
- • Participate in industry podcasts and events
Month 3: Amplification and Measurement
- • Scale successful media relationships and story angles
- • Track mentions in new AI model responses
- • Measure changes in AI visibility over time
- • Optimize approach based on what's generating AI inclusion
The competitive advantage of early adoption
We're still in the early days of AI-driven discovery. Most startups are either unaware of this shift or treating it as a future concern. This creates a massive opportunity for companies that invest in AI visibility now.
The startups that establish authoritative AI presence today will have a compounding advantage as LLMs become the primary discovery mechanism for business software, tools, and services.
The question isn't whether AI will impact how customers discover your startup — it's whether you'll be ready when it does.
Ready to build your AI visibility strategy?
HeyJared helps startups get the media coverage that embeds them in AI knowledge bases for long-term discovery advantages.
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