@rohanpaul_ai

Independent AI Engineer and Entrepreneur; Creator of Rohan's Bytes Newsletter on Substack

Domain Expertise:

Artificial IntelligenceMachine LearningAGI Developments

Detected Biases:

Enthusiastic promotion of AI progress and AGI raceFocus on positive AI developments without critical analysis of risks

90%

Average Truthfulness

Post Analyzed

Who Is This Person?

Rohan Paul is a Bengaluru-based AI engineer and entrepreneur known for his focus on artificial intelligence advancements, particularly the race toward AGI. He maintains an active presence on X (formerly Twitter) under the handle @rohanpaul_ai, where he shares summaries and links to recent AI research papers, datasets, and developments. His content often highlights cutting-edge topics like knowledge distillation, RAG techniques, medical LLMs, and AI ethics. Recent activities include posting about studies on junk data in LLM training (November 2025), swarm inference benchmarks, and Anthropic's financial services expansions. He also runs a daily AI newsletter on Substack called 'Rohan's Bytes,' which compiles high-signal AI news and has thousands of subscribers. As of September 2025, he gained notable recognition when Google CEO Sundar Pichai followed him on X, following prior attention from Amazon founder Jeff Bezos.

How Credible Are They?

90%

Baseline Score

Rohan Paul appears highly credible within the AI enthusiast and researcher community. His content is technically oriented, reliably sources from peer-reviewed or established AI repositories, and avoids unsubstantiated claims. The absence of controversies, combined with endorsements from industry leaders like Bezos and Pichai, bolsters his influence. However, his unverified status and promotional tone toward AI advancements indicate a potential optimism bias, though this does not detract from factual accuracy. Overall, he is a reliable source for AI news and summaries, particularly for professionals tracking the field.

Assessment by Grok AI

What's Their Track Record?

No documented fact-checks, corrections, or controversies found. Posts consistently cite legitimate AI research papers, surveys, and datasets from sources like arXiv and Hugging Face, with accurate summaries. Engagement patterns show informative, non-sensationalized content focused on technical advancements, suggesting high historical accuracy in the AI domain. No evidence of misinformation or disputes.

What Have We Analyzed?

Recent posts and claims we've fact-checked from this author

Post by @rohanpaul_ai

@rohanpaul_ai · 6d ago

81%

Credible

Anthropic has overtaken OpenAI in enterprise LLM API market share. OpenAI fell from 50% in late 2023 to 25% by mid-2025, which shows that brand alone does not hold share once real workloads start. Anthropic now leads enterprise LLM API usage with 32%, while OpenAI has 25%, pointing to a real shift in how companies pick vendors. Enterprise LLM API spend hit $8.4B in the first half of 2025. Anthropic’s push on data controls, compliance, and clean integration with existing systems won trust, and that trust tends to decide renewals and expansions. Claude’s recent lines, including stronger reasoning and coding, helped too, with developer code-gen share around 42% for Anthropic vs 21% for OpenAI. Usage is shifting to inference at scale, so uptime, latency, and incident response matter more than raw benchmark wins. Vendor switching stayed low at 11%, and 66% of teams just upgraded within the same vendor, so any share gain here is hard won. Google sits near 20% and Meta near 9%, so this is not a 2-player market, and strengths differ by use case like agents, code, or retrieval. Buyers now weigh cost per token, data residency, auditability, SOC reports, and fine-grained controls as much as model quality. Multi-vendor setups are rising because they reduce lock-in and let teams route tasks to the best model for that job.

12 Facts

9 Opinions

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