About Me
I'm Adrien Laurent, CEO of IntuitionLabs, an AI software company focused on life sciences. I'm an experienced entrepreneur with a track record of founding and successfully exiting companies, including Modulis, which I ran for 14 years before its acquisition by ClearlyIP in 2019.
My educational background includes Computer Software Engineering from Université Laval and completion of EO's Entrepreneurial Masters Program (class of 2024). I've also completed machine learning certifications from Stanford Online.
At IntuitionLabs, I've led projects including implementing data warehousing solutions, creating mobile-optimized dashboards for pharmaceutical sales teams, and developing commercial analytics platforms for pharmaceutical companies. I'm also the creator of LLM Proxy, an open-source LLM router.
I'm active in the tech community, hosting the AI Wednesdays meetup in the South Bay (1000+ members). I previously served on the board of the Entrepreneurs' Organization - Silicon Valley chapter. I maintain an active presence on LinkedIn where I share insights about AI and software development.
Based in Mountain View, California, I'm passionate about the intersection of AI and life sciences, and I believe in using technology to make complex information more accessible while maintaining complete transparency about how that technology is used.
Content Creation Transparency
Most of the content on this website is created with the assistance of Large Language Models (LLMs). I believe in complete transparency about this process because readers deserve to know how the information they're consuming is produced.
Each article begins with a topic I'm curious about or want to explore more deeply in the pharmaceutical software space. I've built a sophisticated workflow using Temporal.io that orchestrates background research, link enrichment, image generation, and metadata creation. This process leverages multiple AI models from OpenAI, Anthropic, and Google Gemini to ensure comprehensive, well-researched content.
While AI handles the heavy lifting of research and initial drafting, I provide the editorial direction, quality control, and ensure all content meets accuracy standards. This hybrid approach allows me to cover more topics in greater depth while maintaining transparency about the role of AI in content creation.
Frequently Asked Questions
How are the articles on this website created?
Each article follows a structured workflow built with Temporal.io:
- Topic selection based on curiosity or identified knowledge gaps
- Automated background research using multiple LLM models
- Link enrichment to ensure proper citations
- AI-assisted image generation where appropriate
- Metadata generation for SEO and categorization
- Human review and quality control
What AI models power the content?
I use a blend of leading LLM providers including OpenAI (GPT models), Anthropic (Claude), and Google (Gemini). This multi-model approach helps cross-verify information and leverage each model's unique strengths.
How much computational resources go into each article?
On average, each article requires approximately 1h of LLM processing time. This represents significant computational investment to ensure thorough research and comprehensive content generation.
Where does the information come from?
All articles are generated exclusively from publicly available information that can be found online. No proprietary or confidential data sources are used. Every piece of information is backed by sources accessible to anyone conducting similar research.
How do you handle AI hallucinations?
Hallucinations are mitigated through:
- Extensive use of citations and source attribution
- Cross-referencing information across multiple LLM models
- Implementing validation steps in the Temporal workflow
- Human review of generated content
- Community feedback and rapid corrections
What value does this add beyond existing internet content?
While the source information exists online, these articles provide value by:
- Compilation: Bringing together dispersed information into cohesive narratives
- Synthesis: Creating connections between related concepts
- Time-saving: Delivering comprehensive information instantly, eliminating hours of manual research
- Structure: Organizing complex pharmaceutical software topics in digestible formats
- Currency: Regularly updating content with the latest publicly available information
Doesn't this contribute to the "dead internet theory"?
This is a valid concern. The value proposition isn't in creating new information but in making existing information more accessible and useful. Rather than waiting for an LLM to gather and process information on demand, readers get instant access to pre-compiled, verified, and structured content on specific topics. It's about efficiency and accessibility, not replacing human knowledge creation.
How do you handle errors and corrections?
Despite quality control measures, mistakes can occur. When readers identify errors:
- Corrections are implemented promptly upon verification
- All verified errors are fixed immediately
- Significant updates are logged for transparency
- Community feedback is actively encouraged and valued
Why be transparent about using AI?
Transparency builds trust. Readers deserve to know how content is created, especially in technical fields like pharmaceutical software. By being open about the process, readers can make informed decisions about how they use and cite the content. This honesty also helps advance the conversation about AI's role in content creation.
Can I verify the information in your articles?
Absolutely. Readers are encouraged to:
- Check the provided citations and sources
- Cross-reference with other authoritative sources
- Report any discrepancies found
- Use the content as a starting point for deeper research
Is this content as reliable as traditionally written articles?
The reliability comes from the sources cited, not the method of compilation. Each article draws from the same publicly available information a human researcher would access. The multi-model validation and extensive citations actually provide more transparency than many traditional articles. However, readers should always verify critical information independently.
Can you create content for other companies?
Yes, I can create similar AI-powered content workflows for other companies. If you're interested in implementing this type of content creation system for your organization, please inquire through our contact page.