Beyond the Billion-Dollar Hype: Junagal's Decadal View of AI Value
The valuation game in venture is rigged, pushing for exits over enduring value. At Junagal, we reject this short-termism, focusing instead on permanent capital and building for a decade, not a fund cycle.
Beyond the Billion-Dollar Hype: Junagal's Decadal View of AI Value
The valuation game in venture is rigged, pushing for exits over enduring value. At Junagal, we reject this short-termism, focusing instead on permanent capital and building for a decade, not a fund cycle.
The Decisive Edge: Building Only When the Four Pillars Align
Junagal's permanent capital approach demands a meticulous focus on build timing. We've learned that market readiness isn't a feeling; it's the confluence of four critical, measurable capabilities.
The Decades-Long Horizon: Why We Walked Away From Acquisition Offers
Conventional wisdom dictates that acquisition is the ultimate validation for a tech startup. We challenge this, arguing that for truly foundational AI companies, selling early can be a catastrophic miscalculation, especially with permanent
The $3 Million Mistake We Fixed: Why Killing a 'Winning' Product Was Our Best Bet
Conventional wisdom says never kill a growing product. We challenged this dogma with permanent capital and found that sometimes, your best-performing product is the one silently draining your future. This isn't about failure; it's a
Your AI Project Isn't Expensive Until It Ships: The Inference Reality
The true cost of AI isn't in training, but in production inference. We expose the hidden operational, data, and infrastructure costs that blindside founders and execs, turning promising models into budget black holes.
The AI Agent Gold Rush Is Breaking Founders – And We're Barely Talking About It
The frenzy around AI agents is creating an unprecedented burnout epidemic among founders. Despite the hype, the reality of deploying robust AI agents is a relentless, unsustainable grind that demands a fundamental rethink of venture buildin
The Decade of Deliberation: Why 'Move Fast and Break Things' Breaks AI Companies in 2026
In 2026, the 'move fast and break things' mantra is not just outdated; it's a liability, particularly for AI-native companies. Anil Junagal argues for deliberate agility and foundational trust in an era of complex, agentic syste
The Illusion of the AI Specialist: Why Your AI-Native Company Needs Architects, Not Just Algorithm Whisperers
Conventional wisdom says AI-native companies hire for deep ML expertise. As Anil Junagal, I argue this is a dangerous oversimplification. True AI-native success demands system architects and integrators with a decade-scale mindset.
Own Your Inference: Why Decoupling From Cloud LLM APIs Is Your Decade-Defining AI Decision
Relying on generic cloud LLM APIs for core AI inference will silently erode your margins and cripple your long-term innovation. The most critical infrastructure decision for AI profitability over the next decade isn't which model, but w
Autonomous Retail: Why 'Moving Fast and Breaking Things' Will Break Your Store, and How to Fix It
Agentic AI is poised to revolutionize retail beyond chatbots. We explore a four-layer framework for true autonomy, its multi-trillion dollar opportunity, and the critical failure modes.
The Invisible Tax: How Junagal Reclaimed 60% of Our AI Infrastructure Spend
At Junagal, we slashed AI infrastructure costs by 60% without capability loss. This deep dive reveals our framework for building AI systems with decade-long horizons, optimizing compute, models, and data pipelines for permanent value.
NVIDIA's Full Stack: Why the Vera CPU Isn't the Moat You Think It Is for AI's Edge
NVIDIA's expansion into full-stack compute, exemplified by the Vera CPU, is widely seen as an unassailable moat. But this ambition paradoxically creates vulnerabilities, particularly for next-gen AI and robotics at the edge.