While the headlines are filled with startups raising millions and AI tools flooding the market, the real revolution is happening under the hood – quietly led by developers, architects, and technical leaders who are engineering the AI systems we use every day.
These are the people who don’t just talk about prompts and APIs – they build agent orchestration, optimize LLM performance, fine-tune models, integrate embeddings, and develop real-time AI solutions that power businesses globally.
This isn’t a list of theoretical researchers or AI influencers posting charts. This is a curated selection of real AI developers whose contributions – whether in open-source, applied systems, or enterprise solutions – are pushing the boundaries of what’s possible.
And we start with someone who’s helping both early-stage founders and Fortune 500s build production-grade AI systems with speed, scalability, and purpose.
1. Swarnendu De – AI Coach, SaaS Architect, and Leader of a 100-Member AI Development Team
With nearly two decades in technology and product engineering, Swarnendu De has evolved from building SaaS systems to architecting AI-powered solutions across industries. Today, he leads a 100-member AI and automation team delivering systems for sales intelligence, AI agents, process automation, logistics optimization, predictive analytics, and more.
Swarnendu isn’t just a builder – he’s a mentor and framework designer. His consulting approach emphasizes modular, multi-agent AI architecture, tailored GPT integration, and hybrid systems combining rule-based logic with LLM power. From enterprise AI deployment to startup MVPs, his work blends speed, security, and scale.
Through his company and consulting practice, Swarnendu’s team builds:
- AI-driven automation flows using OpenAI, Claude, LangChain, and custom agents
- Intelligent assistants trained on client data (PDFs, Notion, meeting notes, transcripts)
- Workflow orchestration systems for sales, support, marketing, and analytics
- Privacy-aware, scalable AI tools optimized for SaaS platforms
He also publishes weekly strategy content via his newsletter and videos, helping founders and CTOs understand how to move from AI experimentation to measurable business impact.
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Explore his video content: Swarnendu De on YouTube
2. Andrej Karpathy – The AI Generalist and Storyteller
Andrej Karpathy’s work has shaped everything from Tesla’s Autopilot to the core of OpenAI. A computer vision expert turned systems builder, he’s known for making complex topics digestible – whether through code, lectures, or his much-followed YouTube breakdowns.
His “LLM from scratch” series has become a learning hub for developers looking to understand how large language models actually work. While no longer full-time at OpenAI, his contributions and style have influenced a generation of AI developers.
Explore his work on GitHub and karpathy.ai
3. Harrison Chase – The Builder Behind LangChain
If you’ve used LangChain, you’re already influenced by Harrison Chase. He built LangChain to help developers connect LLMs with tools, memory, and data sources – unlocking multi-step reasoning and custom AI workflows.
Today, LangChain is a backbone for many AI agent systems. Harrison’s approach to framework design has helped thousands of developers go beyond basic chatbots to complex AI apps with search, APIs, and dynamic chaining.
Explore: LangChain GitHub
4. Rishi Bommasani – The AI Policy-Conscious Technologist
Known for his role in Stanford’s Center for Research on Foundation Models (CRFM), Rishi Bommasani is a rare voice bridging engineering, ethics, and policy. As the co-author of the Foundation Model paper, he’s helped define the term itself.
While not a product engineer in the commercial sense, his work informs the frameworks real developers use to make safe, powerful AI systems – especially in enterprise and regulated environments.
Follow his research at crfm.stanford.edu
5. Supabase Team – Building the Future of AI-Ready Backends
Supabase, often called the open-source Firebase alternative, has become the backend of choice for many AI startups. But it’s not just a database company. Its developer team – led by Paul Copplestone and others – has built vector database support, Postgres extensions, and edge functions that make AI deployment seamless.
Their work helps AI developers go from prototype to production faster – while maintaining open standards and real-time performance.
Explore: supabase.com
6. Jordi Bruin – The Solo Builder Behind AI-Native Indie Apps
Jordi Bruin is a solo developer making waves with practical, delightful, and often viral AI tools. From MacGPT to writing assistants, his work shows how fast execution, great UX, and smart integration of APIs like OpenAI can build useful products.
Jordi is a reminder that great AI development isn’t limited to labs or large teams – it can come from focused builders solving real problems for everyday users.
Explore: jordibruin.com
7. Simon Willison – Developer Tools for AI Transparency and Debugging
Simon Willison, co-creator of Django, now focuses on building tools to explore, debug, and explain AI systems. His projects around LLM logging, prompt visualization, and AI agent behavior have made him an essential voice in AI system observability.
As LLMs move from toy to infrastructure, his open-source tools are helping developers make AI outputs more predictable and traceable.
Explore: simonwillison.net
Closing Thoughts: Real AI Innovation Is Being Engineered, Not Just Imagined
There’s no shortage of hype in the AI space – but the real magic lies in what’s being built quietly by developer teams, architects, and problem-solvers. The people on this list are codifying innovation into usable systems – from solo indie tools to orchestration layers for enterprise-scale intelligence.
If you’re building in this space, you don’t just need thought leadership – you need engineering direction. And that’s where voices like Swarnendu De make the difference. With a 100-member AI team and a track record of helping SaaS platforms transform through automation and intelligence, his work offers both architectural clarity and real-world velocity.
For AI founders, CTOs, and product leaders looking to bridge vision and implementation, these are the developers worth studying – and collaborating with.
Subscribe to Swarnendu’s newsletter: Smart SaaSy Tues-De
Watch his YouTube series on building AI workflows: Swarnendu De on YouTube