AI is the new electricity—but the infrastructure isn't ready. Model deployment is expensive. Fine-tuning is a dark art. Evaluation is broken. The picks-and-shovels opportunities in AI are as large as the applications themselves. We're looking for the platforms, tools, and infrastructure that will power the next decade of AI development.
Video generation models now produce photorealistic 8-second clips indistinguishable from reality. Soon, generating video will cost nearly nothing. Treat video as a new computing primitive—not output—and build apps, tools, and infrastructure for this unlimited-video world.
AI agents are evolving from single chatbots into distributed systems with thousands of sub-agents running in parallel. This is the Hadoop/Spark moment for AI. Build the infrastructure that makes orchestrating agent fleets as routine as deploying a web service.
Salesforce and ServiceNow were founded 25 years ago and rode cloud to $200B+ market caps. AI presents the same once-in-a-generation platform shift. Build the enterprise software where AI isn't a feature—it's the foundation. Think Cursor for sales, HR, and finance.
The federal government spends $100B+ annually on consultants from Deloitte, Accenture, and Booz Allen. Most of this work—research, analysis, report writing, process documentation—can now be done by AI. Build software that makes consultants obsolete.
Phone calls are a $100B+ market that hasn't fundamentally changed in a century. Voice AI can now hold real conversations—scheduling, selling, supporting—with latency and quality indistinguishable from humans. Build the future of voice.
CEOs have chiefs of staff. Everyone else has overflowing inboxes and chaotic calendars. Build the AI assistant that actually handles your email, schedules your meetings, and executes your tasks—without creating more work than it saves.
The $20B home security market is stuck on motion sensors and grainy cameras. Commercial buildings have AI that distinguishes threats from false alarms. Bring that intelligence to every home—security that recognizes faces, detects anomalies, and actually protects.
Tech is under regulatory siege from every direction—AI licensing, teen safety laws, crypto enforcement, hardware restrictions. Every new regulation creates mandatory adoption of compliance tools. Build the infrastructure that helps companies survive the regulatory onslaught.
ChatGPT reached 100M users in two months. Enterprise adoption is crawling. Why? Enterprises lack the privacy, security, compliance, data integration, and governance tooling required to deploy AI responsibly. Build the infrastructure that unlocks AI for the Fortune 500.
Every decade, technology replaces a human-powered process with software. Postcards → texts. Blockbuster → Netflix. The next wave: synthetic humans—software that replicates human behavior with the scalability of bits. Deliver what only humans could do at 100x speed and 1% cost.
AGI is increasingly an operational challenge of bringing tasks under distribution. Build AI applications that scale complex work across domains using reasoning models and tool access.
Agents trained on games and simulations lack real-world enterprise complexity. Build multi-agent simulations reflecting actual office communication (Slack, video calls, file sharing) for training domain-generalist work agents.
Large enterprises lack unified reasoning systems and integration hubs for AI actions. Build a live enterprise ontology mapping plus centralized action registry for AI execution across legacy systems.
Consumer no-code tools lack enterprise features like access control, integrations, and compliance. Build an enterprise-specific application builder with business-oriented templates and security features.
Manual metadata collection is painful and incomplete; legacy catalogs poorly support unstructured data. Build AI-driven classification, policy application, quality detection, and lineage understanding for modern data stacks.
Millions of deployed cameras lack rich indexing and semantic understanding. Build full-stack security services using on-device models for sophisticated computer vision analysis.
Mainframe apps (COBOL, Assembler) are difficult to migrate due to language, complexity, tight coupling, and compliance risk. Use code generation to systematically extract logic, translate to modern languages, and generate documentation.
AI models need live data access but existing APIs lack page content, outlinks, and edit history. Bootstrap comprehensive, vertically-focused web indexes with parsed content and real-time updates.
Businesses miss approximately 50% of inbound calls, which is critical for lead generation. Build voice-based transactional systems handling qualification, reservations, appointments, and order tracking.
Large HR teams handle high-volume repetitive events like hiring, exits, and role changes with manual processing. Build conversational search interfacing with HRIS systems for access-controlled answers and automated record updates.
AI-managed ads are expected to capture 54% of the $1.1 trillion digital ad market by 2030. That's $594B in AI-mediated advertising spend.
Build security tools designed for MSPs to deploy and manage across their SMB client portfolios.
Salesforce and ServiceNow were founded 25 years ago and rode cloud to $200B+ market caps. AI presents the same once-in-a-generation platform shift. Build the enterprise software where AI isn't a feature—it's the foundation. Think Cursor for sales, HR, and finance.
The federal government spends $100B+ annually on consultants from Deloitte, Accenture, and Booz Allen. Most of this work—research, analysis, report writing, process documentation—can now be done by AI. Build software that makes consultants obsolete.
The internet's core architecture lacks a robust identity layer, leading to widespread issues in verification, security, and trust. This fundamental flaw creates a massive market opportunity for solutions that can securely and reliably manage digital identities.
The AI alignment problem poses an existential risk, as current AI development outpaces our ability to ensure advanced systems act ethically and safely. A robust solution is critical for harnessing AI's potential responsibly.
As AI coding agents handle implementation, the bottleneck shifts to deciding what to build. Create the intelligent product management tool that analyzes customer data, proposes features, and generates specs that coding agents can execute.
Government processes millions of forms annually but still prints digital submissions for manual review. AI can process applications, detect fraud, and clear backlogs—if you can navigate the sales cycle. Once you're in, you're in for decades.
50% of CMDB data is unreliable, contributing to over 60% of IT incidents caused by misconfigurations. Build agentless discovery, graph construction, and AI reasoning for robust enterprise IT visibility.
On-call engineers spend hours debugging without systematic incident analysis. Build lightweight agents that access logs and metrics to retrieve context and suggest fixes based on runbooks and prior incidents.
There's no Copilot-like experience for general computing (email, browsing, authoring). Build a browser extension that learns personal writing style, handles multimodal input (screenshots, voice), and provides second-brain functionality.
AI software could boost global productivity by $22-117 trillion by 2030. OpenAI is projected to surpass $10B revenue in 2025. Build the next wave of AI productivity tools.
Build AI-powered automation for enterprise back-office processes—finance, HR, procurement—that still rely heavily on manual work.
As AI-generated deepfakes become indistinguishable from reality, the internet's foundational trust is collapsing. We need solutions to verify digital content authenticity before misinformation and fraud become uncontrollable.
As AI coding agents handle implementation, the bottleneck shifts to deciding what to build. Create the intelligent product management tool that analyzes customer data, proposes features, and generates specs that coding agents can execute.
Tech is under regulatory siege from every direction—AI licensing, teen safety laws, crypto enforcement, hardware restrictions. Every new regulation creates mandatory adoption of compliance tools. Build the infrastructure that helps companies survive the regulatory onslaught.
Government processes millions of forms annually but still prints digital submissions for manual review. AI can process applications, detect fraud, and clear backlogs—if you can navigate the sales cycle. Once you're in, you're in for decades.
Video generation models now produce photorealistic 8-second clips indistinguishable from reality. Soon, generating video will cost nearly nothing. Treat video as a new computing primitive—not output—and build apps, tools, and infrastructure for this unlimited-video world.
AI agents are evolving from single chatbots into distributed systems with thousands of sub-agents running in parallel. This is the Hadoop/Spark moment for AI. Build the infrastructure that makes orchestrating agent fleets as routine as deploying a web service.
Phone calls are a $100B+ market that hasn't fundamentally changed in a century. Voice AI can now hold real conversations—scheduling, selling, supporting—with latency and quality indistinguishable from humans. Build the future of voice.
CEOs have chiefs of staff. Everyone else has overflowing inboxes and chaotic calendars. Build the AI assistant that actually handles your email, schedules your meetings, and executes your tasks—without creating more work than it saves.
The $20B home security market is stuck on motion sensors and grainy cameras. Commercial buildings have AI that distinguishes threats from false alarms. Bring that intelligence to every home—security that recognizes faces, detects anomalies, and actually protects.
ChatGPT reached 100M users in two months. Enterprise adoption is crawling. Why? Enterprises lack the privacy, security, compliance, data integration, and governance tooling required to deploy AI responsibly. Build the infrastructure that unlocks AI for the Fortune 500.
Every decade, technology replaces a human-powered process with software. Postcards → texts. Blockbuster → Netflix. The next wave: synthetic humans—software that replicates human behavior with the scalability of bits. Deliver what only humans could do at 100x speed and 1% cost.
AGI is increasingly an operational challenge of bringing tasks under distribution. Build AI applications that scale complex work across domains using reasoning models and tool access.
Agents trained on games and simulations lack real-world enterprise complexity. Build multi-agent simulations reflecting actual office communication (Slack, video calls, file sharing) for training domain-generalist work agents.
Large enterprises lack unified reasoning systems and integration hubs for AI actions. Build a live enterprise ontology mapping plus centralized action registry for AI execution across legacy systems.
Consumer no-code tools lack enterprise features like access control, integrations, and compliance. Build an enterprise-specific application builder with business-oriented templates and security features.
50% of CMDB data is unreliable, contributing to over 60% of IT incidents caused by misconfigurations. Build agentless discovery, graph construction, and AI reasoning for robust enterprise IT visibility.
Manual metadata collection is painful and incomplete; legacy catalogs poorly support unstructured data. Build AI-driven classification, policy application, quality detection, and lineage understanding for modern data stacks.
On-call engineers spend hours debugging without systematic incident analysis. Build lightweight agents that access logs and metrics to retrieve context and suggest fixes based on runbooks and prior incidents.
There's no Copilot-like experience for general computing (email, browsing, authoring). Build a browser extension that learns personal writing style, handles multimodal input (screenshots, voice), and provides second-brain functionality.
Millions of deployed cameras lack rich indexing and semantic understanding. Build full-stack security services using on-device models for sophisticated computer vision analysis.
Mainframe apps (COBOL, Assembler) are difficult to migrate due to language, complexity, tight coupling, and compliance risk. Use code generation to systematically extract logic, translate to modern languages, and generate documentation.
AI models need live data access but existing APIs lack page content, outlinks, and edit history. Bootstrap comprehensive, vertically-focused web indexes with parsed content and real-time updates.
Businesses miss approximately 50% of inbound calls, which is critical for lead generation. Build voice-based transactional systems handling qualification, reservations, appointments, and order tracking.
Large HR teams handle high-volume repetitive events like hiring, exits, and role changes with manual processing. Build conversational search interfacing with HRIS systems for access-controlled answers and automated record updates.
AI software could boost global productivity by $22-117 trillion by 2030. OpenAI is projected to surpass $10B revenue in 2025. Build the next wave of AI productivity tools.
AI-managed ads are expected to capture 54% of the $1.1 trillion digital ad market by 2030. That's $594B in AI-mediated advertising spend.
Build security tools designed for MSPs to deploy and manage across their SMB client portfolios.
Build AI-powered automation for enterprise back-office processes—finance, HR, procurement—that still rely heavily on manual work.
Some problems are so large that solving them changes everything. Fusion energy. Brain-computer interfaces. Reversing aging. These aren't incremental improvements—they're civilizational shifts. We're looking for the technical breakthroughs and bold bets that seem impossible until they're inevitable.
The best businesses often start in markets that look too small. Vertical SaaS for dry cleaners. Tools for independent truckers. Software for yacht brokers. These niches are ignored by big companies but represent real pain for real people. Dominate a niche, then expand.
Work is being rebuilt from scratch. Remote collaboration. AI-augmented productivity. The death of the 9-to-5. The rise of the portfolio career. The companies that define how we work in 2035 are being built now. We're looking for the tools, platforms, and systems that will shape the next era of human productivity.
50 million people now consider themselves creators. Most make less than $500/year. The infrastructure is broken—discovery is algorithmic roulette, monetization favors platforms over people, and burnout is the norm. We need better tools for creators to build sustainable businesses around their work.
The science of aging is accelerating. Senolytics. Gene therapy. Epigenetic reprogramming. For the first time, extending healthy human lifespan is a serious engineering challenge, not science fiction. The companies solving these problems won't just build billion-dollar businesses—they'll change what it means to be human.
Financial infrastructure was built for a different era. Cross-border payments take days. 2 billion people are unbanked. Small businesses can't access capital. Crypto promised a revolution but mostly delivered speculation. We're looking for practical solutions that make money work better for everyone.