Lovable reportedly in talks to double its valuation to $13.2B ⁠51%

By Marina Temkin⁠65%

7/8/2026, 10:41:33 PM

BS Summary: This article contains 19 faulty reasoning types, including Representativeness Heuristic, Halo Effect, and Appeal to Authority, with Recency Bias as the most egregious example at 25.3% saturation with 83 hits. Analysis detected 698 faulty-reasoning hits from 328 analyzed words, generating a BS Score of 50.8% and a BS Rank of ⁠51% (10,432 of 21,179 articles). This article is worse (more manipulative) than 50.70% of the article peer group.

3:41 PM PDT · July 8, 2026 
Image Credits: Bruno de Carvalho/SOPA Images/LightRocket / Getty Images 
Lovable reportedly in talks to double its valuation to $13.2B 
Lovable, a Swedish vibe-coding startup, is in talks to raise $300 million at a valuation of $13.2 billion — exactly double the $6.6 billion valuation the company achieved last December, Sifted reported . 
Menlo Ventures, a firm that announced its latest $3 billion fund last month, is expected to lead the round, according to the report. 
The less-than-three-year-old startup hit $500 million in annualized revenue run rate in June. 
Lovable’s users include founders, individual designers, and salespeople building websites and e-commerce storefronts. 
The company also sells its vibe-coding tool to large enterprises, including Workday, Asana, and Nvidia. 
Vibe coding, which allows users to build software simply by describing it, is by far the most popular and lucrative use case for AI. 
Other high-profile vibe-coding startups include Replit, valued at $9 billion in March, and Factory, a startup that helps enterprises develop AI agents, which raised $150 million at a $1.5 billion valuation in April. 
Meanwhile, Cursor, which offers vibe coding for developers, was acquired by SpaceX for $60 billion last month. 
AI , In Brief , Lovable , menlo ventures , Startups , vibe coding 
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Article reasoning-pattern comparisonThis article: 10.1%Marina Temkin: 3.3%TechCrunch: 3.0%Confirmation Bias10.1%This article: 6.1%Marina Temkin: 6.1%TechCrunch: 1.4%Anchoring Bias6.1%This article: 7.3%Marina Temkin: 5.2%TechCrunch: 3.5%Availability Heuristic7.3%This article: 20.1%Marina Temkin: 2.4%TechCrunch: 1.1%Representativeness Heuristic20.1%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.6%Hindsight Bias0.0%This article: 7.3%Marina Temkin: 1.5%TechCrunch: 2.5%Overconfidence Bias7.3%This article: 3.0%Marina Temkin: 3.0%TechCrunch: 4.8%Framing Effect3.0%This article: 5.2%Marina Temkin: 0.5%TechCrunch: 0.6%Loss Aversion5.2%This article: 0.0%Marina Temkin: 0.3%TechCrunch: 0.6%Status Quo Bias0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.2%Sunk Cost Effect0.0%This article: 7.3%Marina Temkin: 10.2%TechCrunch: 5.0%Optimism Bias7.3%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 1.2%Pessimism Bias0.0%This article: 4.6%Marina Temkin: 1.0%TechCrunch: 5.0%Negativity Bias4.6%This article: 0.0%Marina Temkin: 2.5%TechCrunch: 2.1%Self-Serving Bias0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.5%Fundamental Attribution Error0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%Actor-Observer Bias0.0%This article: 0.0%Marina Temkin: 0.7%TechCrunch: 0.6%In-Group Bias0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.3%Out-Group Homogeneity Bias0.0%This article: 19.5%Marina Temkin: 12.0%TechCrunch: 3.3%Halo Effect19.5%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%Horn Effect0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.0%Dunning-Kruger Effect0.0%This article: 25.3%Marina Temkin: 4.9%TechCrunch: 2.3%Recency Bias25.3%This article: 3.0%Marina Temkin: 0.3%TechCrunch: 0.3%Primacy Effect3.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%Blind-Spot Bias0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.3%Ad Hominem0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.6%Straw Man0.0%This article: 18.3%Marina Temkin: 7.7%TechCrunch: 4.3%Appeal to Authority18.3%This article: 0.0%Marina Temkin: 1.4%TechCrunch: 1.7%False Dilemma0.0%This article: 0.0%Marina Temkin: 0.6%TechCrunch: 0.6%Slippery Slope0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.2%Circular Reasoning0.0%This article: 13.4%Marina Temkin: 7.2%TechCrunch: 6.0%Hasty Generalization13.4%This article: 0.0%Marina Temkin: 0.2%TechCrunch: 0.2%Red Herring0.0%This article: 10.7%Marina Temkin: 3.8%TechCrunch: 1.2%Bandwagon10.7%This article: 13.4%Marina Temkin: 0.9%TechCrunch: 2.2%Appeal to Emotion13.4%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.6%Begging the Question0.0%This article: 0.0%Marina Temkin: 2.7%TechCrunch: 2.9%Post Hoc (False Cause)0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%Tu Quoque0.0%This article: 0.0%Marina Temkin: 1.1%TechCrunch: 0.5%Burden of Proof0.0%This article: 0.0%Marina Temkin: 0.3%TechCrunch: 0.2%Appeal to Nature0.0%This article: 0.0%Marina Temkin: 0.7%TechCrunch: 0.3%Composition/Division0.0%This article: 7.3%Marina Temkin: 1.9%TechCrunch: 2.4%Anecdotal7.3%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%No True Scotsman0.0%This article: 13.4%Marina Temkin: 4.1%TechCrunch: 2.0%Ambiguity (Equivocation)13.4%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Marina Temkin: 0.4%TechCrunch: 0.2%Middle Ground0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.0%Personal Incredulity0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%Special Pleading0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%Genetic Fallacy0.0%This article: 0.0%Marina Temkin: 4.7%TechCrunch: 2.0%Unattributed Quote0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.7%Quote-first Misdirection0.0%This article: 0.0%Marina Temkin: 5.2%TechCrunch: 4.6%Biased Writer Voice0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.8%Indoctrination0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%Politically Left Leaning Bias0.0%This article: 0.0%Marina Temkin: 0.0%TechCrunch: 0.1%Politically Right Leaning Bias0.0%This article: 17.4%Marina Temkin: 6.5%TechCrunch: 4.6%Attempt to Sell a Product or S…17.4%

328 words analyzed.

Speakers

2speakers9.8%attributed speech296writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 10 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageGetty Images • 9 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageMenlo Ventures • 23 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 15 words • 100.0% coverageWriter's voice • 24 words • 0.0% coverageWriter's voice • 33 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 11 words • 100.0% coverageWriter's voice • 18 words • 100.0% coverageWriter's voice • 6 words • 100.0% coverageWriter's voice • 2 words • 0.0% coverageWriter's voice • 7 words • 100.0% coverageWriter's voice • 15 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverage
Selected voice

Menlo Ventures

100%flagged-word coverage
23 attributed words72% of attributed speech80% writer coverage
0%10.0%20.0%Attempt to Sell a Product -19.3 ptsWriter: 19.3%Menlo Ventures: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.