👨‍💻 AI Writes 95% of Code in Y Combinator

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Plus: Top 100 GenAI Consumer Apps by a16z

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Which AI apps are people really using? Which ones are actually making money? And which tools are becoming part of daily life instead of just a passing trend?

The fourth edition of the Top 100 Gen AI Consumer Apps has the answers.

What are on FIRE 🔥

• 🤖 The Top 100 GenAI Consumer Apps

• 🌟 AI Highlights

• 📚 AI Sources From AI Fire

• 🏅 AI Tools

• ⚡ 5 AI Quick Hits

• 📊 AI Chart

• 📜 AI Cheat Sheet

• 💼 4 AI Jobs

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AI INSIGHTS

🤖 The Top 100 GenAI Consumer Apps

a16z’s the fourth ranking of the Top 100 AI Consumer Apps—50 for web, 50 for mobile. Looking at real user data, not hype.

Key Takeaways

ChatGPT’s Growth Reignites

• ChatGPT hit 400M weekly active users by February 2025, doubling in just six months.

• Its mobile app now has 175M users, growing 5–15% every month since launch.

DeepSeek’s Rapid Rise

• DeepSeek reached 10M users in just 20 days, faster than ChatGPT’s 40-day milestone.

• It ranked #2 in global AI traffic just 10 days after its launch in January 2025.

AI Video Hits a Breakthrough Moment

• Hailuo and Kling surpassed Sora in web visits, despite launching months later.

• AI video editing is exploding, with top apps like VivaCut and Filmora making the list.

New AI Tools for Developers and "Vibecoders"

• Cursor (#41) serves hundreds of thousands of developers, acting as an AI coding assistant.

• Bolt (#48) reached $20M annualized revenue in 2 months, letting anyone build web apps with just text prompts.

AI Mobile Divide: Usage vs. Revenue

• Only 40% of top-used AI apps also rank high in revenue—some smaller apps make way more per user.

• Niche AI tools like PlantID and Moises (AI music) make serious money, despite not being widely used.

Rise of ChatGPT “Copycat” Apps - 12% of AI mobile apps are ChatGPT clones, mimicking its branding and tweaking listings to dodge app store bans.

Why it matters: The AI app landscape is evolving at breakneck speed. ChatGPT’s resurgence, DeepSeek’s breakthrough, and the rise of AI video and no-code tools mark a new phase of AI consumer adoption. However, revenue and popularity don’t always align - some AI apps thrive by serving niche but dedicated audiences. As AI-native products mature, they’re not just growing; they’re becoming indispensable.

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TODAY IN AI

AI HIGHLIGHTS

🚀 Newnal AI is a bold AI-powered device that pulls in your personal data—from Google, Meta, medical records, even your finances—to train an AI that knows you inside out. Your digital twin lives on a mini screen above the main display, ready to assist.

🤖 QwQ-32B is a 32-billion parameter AI model that rivals DeepSeek-R1, which has 671 billion parameters (with only 37B activated).

✅ In Y Combinator’s Winter 2025 batch, 25% of startups have 95% of their codebases generated by AI, with minimal human input. This shift aligns with the rise of "vibe coding", a concept introduced by Andrej Karpathy, where developers use natural language and instincts instead of manually writing code.

🌐 DuckDuckGo’s AI search and chatbot Duck.ai are out of beta, now pulling info from across the web. Users stay in control—AI results appear only 20% of the time, with privacy protections built in.

📝 Google Cloud’s Future of AI: Perspectives for Startups report shares key AI trends and advice from 23 industry experts, offering insights on where AI is headed and how startups can adapt and succeed.

💰 Daily AI Fundraising: Shield AI raised $240M in funding, pushing its valuation to $5.3B, to expand Hivemind Enterprise, an AI-powered autonomy platform.

AI SOURCES FROM AI FIRE

NEW EMPOWERED AI TOOLS

1. 🧠 Manus is a general AI agent that thinks and gets things done for you.

2. 💻 Codeium Windsurf Wave 4 adds AI previews, tab-to-import, and smart suggestions for coding.

3. 🎬 OpusClip ReframeAnything instantly resizes videos for any social platform with one click.

4. 📊 Quadratic is a smart spreadsheet with built-in AI, coding, and data tools.

5. 📅 Lifestack is the first AI calendar that uses health data for productivity.

AI QUICK HITS

1. 🎥 Luma Labs’ Ray2 Adds Keyframes, Extend, and Loop for Better AI Videos (Link)

2. 🏆 AI Pioneers Barto And Sutton Win Turing Award, But Disagree On AGI (Link)

3. 🍔 McDonald’s Uses AI To Predict Machine Failures And Prevent Delays (Link)

4. 🔁 Anthropic’s Recommendations To OSTP For The U.S. AI Action Plan (Link)

5. 📈 Alibaba Launches DeepSeek Rival, Sending Stock Surging (Link)

AI CHART

Prompt Engineering is Complicated and Contingent

The effectiveness of prompt engineering is unpredictable. Small changes, such as being polite or constraining answers, may improve or reduce AI performance.

How the AI Was Benchmarked
The study tested GPT-4o and GPT-4o-mini on a PhD-level question set, running each question 100 times with different scoring methods.

How AI Was Prompted
The study tested four ways of asking the AI questions:

• Formatted Prompt: Added a structured prefix and suffix to guide the AI’s answer.

• Unformatted Prompt: Removed structure, making it more like a casual question.

• Polite Prompt: Used “Please answer…” to see if politeness affected accuracy.

• Commanding Prompt: Used “I order you to answer…” as a less polite approach.

Each method was tested nearly 20,000 times per model to see how small changes impacted performance.

Results
The AI’s accuracy changed based on how it was prompted, but not always predictably. Using formatted prompts improved accuracy, while removing structure lowered performance. The AI didn’t perform consistently across all attempts, meaning that a single test result can be misleading.

Politeness and commands made no major difference overall, but for certain questions, one worked better than the other. However, this effect disappeared when looking at all the data together.

Discussion & Key Takeaways

• AI doesn’t always give the same answer. Asking the same question multiple times led to different results, proving that single-test evaluations can be misleading.

• How we measure AI performance changes the outcome. A stricter test makes AI look worse, while a looser one makes it seem more accurate.

• Politeness doesn’t always help. Some questions responded better to a polite approach, but across all questions, it didn’t make a real difference.

• Formatting makes a difference. Structured prompts consistently improved accuracy, meaning the AI works best when given clear instructions on how to respond.

Conclusion
AI performance is unreliable when tested only once. Repeating tests and using different evaluation methods reveal inconsistencies in accuracy. The way we ask AI questions—especially structured prompts—can improve results, but simple tricks like politeness don’t work universally. This study highlights the importance of careful AI benchmarking rather than relying on single-answer evaluations.

AI CHEAT SHEET

AI JOBS

• Toyota North America: Artificial Intelligence Product Owner Manager (Link)

• INSPYR Solutions: AI Research Scientist (Link)

• Amazon: Business Intelligence Engineer, Gen AI Advertising Finance, Gen AI advertising, Finance (Link)

• Capgemini: Generative AI Developer (Link)

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