The trillion-dollar LLM race is over. The true disruption will be Agentic AI—autonomous, goal-driven systems—a trend set to dominate TechCrunch Disrupt 2025.

When OpenAI’s massive multimodal models were released in the early 2020s, the entire tech world reset. It felt like a gold rush, where the only currency that mattered was GPU access, trillions of tokens, and a parameter count with enough zeroes to humble a Fortune 500 CFO. For years, the narrative has been monolithic: bigger models, better results. The global market for Large Language Models (LLMs) and LLM-powered tools is projected to be worth billions, with worldwide spending on generative AI technologies forecast to hit $644 billion in 2025 alone.

This single-minded pursuit has created a natural monopoly of scale, dominated by the five leading vendors who collectively capture over 88% of the global market revenue. But I’m here to tell you, as an investor on the ground floor of the next wave, that the era of the monolithic LLM is over. It has peaked. The next great platform shift is already here, and it will be confirmed, amplified, and debated on the hallowed stage of TechCrunch Disrupt 2025.

The future of intelligence is not about the model’s size; it’s about its autonomy. The next billion-dollar companies won’t be those building the biggest brains, but those engineering the most competent AI Agents.

🛑 The Unspoken Truth of the Current LLM Market

The current obsession with ever-larger LLMs—models with hundreds of billions or even trillions of parameters—has led to an industrial-scale, yet fragile, ecosystem. While adoption is surging, with 67% of organisations worldwide reportedly using LLMs in some capacity in 2025, the limitations are becoming a structural constraint on true enterprise transformation.

We are seeing a paradox of power: models are capable of generating fluent prose, perfect code snippets, and dazzling synthetic media, yet they fail at the most basic tenets of real-world problem-solving. This is the difference between a hyper-literate savant and a true executive.

Here is the diagnosis, informed by the latest ai news and deep-drives:

• The Cost Cliff is Untenable: Training a state-of-the-art frontier model still requires a multi-billion-dollar fixed investment. For smaller firms, the barrier is staggering; approximately 37% of SMEs are reportedly unable to afford full-scale LLM deployment. Furthermore, the operational (inference) costs, while dramatically lower than before, remain a significant drag on gross margins for any scaled application.
• The Reliability Crisis: A significant portion of users, specifically 35% of LLM users in one survey, identify “reliability and inaccurate output” as their primary concerns. This is the well-known “hallucination problem.” When an LLM optimizes for the most probable next word, it does not optimise for the most successful outcome. This fundamentally limits its utility in high-stakes fields like finance, healthcare, and engineering.
• The Prompt Ceiling: LLMs are intrinsically reactive. They are stunningly sophisticated calculators that require a human to input a clear, perfect equation to get a useful answer. They cannot set their own goals, adapt to failure, or execute a multi-step project without continuous, micro-managed human prompting. This dependence on the prompt limits their scalability in true automation.

We have reached the point of diminishing returns. The incremental performance gain of going from 1.5 trillion parameters to 2.5 trillion parameters is not worth the 27% increase in data center emissions and the billions in training costs. The game is shifting.

🔮 The TechCrunch Disrupt 2025 Crystal Ball: The Agentic Pivot

My definitive prediction for TechCrunch Disrupt 2025 is this: The main stage will not be dominated by the unveiling of a new, larger foundation model. It will be dominated by startups focused entirely on Agentic AI.

What is Agentic AI?

Agentic AI systems don’t just generate text; they act. They are LLMs augmented with a planning module, an execution engine (tool use), persistent memory, and a self-correction loop. They optimise for a long-term goal, not just the next token. They are not merely sophisticated chatbots; they are autonomous problem-solvers. This is the difference between a highly-trained analyst who writes a report and a CEO who executes a multi-quarter strategy.

Here are three fictional, yet highly plausible, startup concepts poised to launch this narrative at TechCrunch Disrupt’s Startup Battlefield:

1. Stratagem

• The Pitch: “We are the first fully autonomous, goal-seeking sales development agent (SDA) for B2B SaaS.”
• The Agentic Hook: Stratagem doesn’t just write cold emails. A human simply inputs the goal: “Close five $50k+ contracts in the FinTech vertical this quarter.” The Agentic AI then autonomously:
  • Reasons: Breaks the goal into steps (Targeting $\rightarrow$ Outreach $\rightarrow$ Qualification $\rightarrow$ Hand-off).
  • Acts: Scrapes real-time financial data to identify companies with specific growth signals (a tool-use capability).
  • Self-Corrects: Sends initial emails, tracks engagement, automatically revises its messaging vector (tone, length, value prop) for non-responders, and books a qualified meeting directly into the human sales rep’s calendar.
  • The LLM is now a component, not the core product.

2. Phage Labs

• The Pitch: “We have decoupled molecular synthesis from human-led R&D, leveraging multi-agent systems to discover novel materials.”
• The Agentic Hook: This startup brings the “Agent Swarm” model to material science. A scientist inputs the desired material properties (e.g., “A polymer with a tensile strength 15% higher than Kevlar and 50% lighter”). A swarm of specialised AI Agents then coordinates:
  • The Generator Agent proposes millions of novel molecular structures.
  • The Simulator Agent runs millions of physics-based tests concurrently in a cloud environment.
  • The Refiner Agent identifies the 100 most promising candidates, and most crucially, writes the robotics instructions to synthesise and test the top five in a wet lab.
  • The system operates 24/7, with zero human intervention until a successful material is confirmed.

3. The Data-Moat Architectures (DMA)

• The Pitch: “We eliminate the infrastructure cost of LLMs by orchestrating open-source models with proprietary data moats.”
• The Agentic Hook: This addresses the cost problem head-on. The core technology is an intelligent Orchestrator Agent. Instead of relying on a single, expensive, trillion-parameter model, the Orchestrator intelligently routes complex queries to a highly efficient network of smaller, specialized, open-source models (e.g., one for code, one for summarization, one for RAG queries). This dramatically reduces latency and inference costs while achieving a higher reliability score than any single black-box LLM. By routing a question to the most appropriate, fine-tuned, and low-cost model, they are fundamentally destroying the Big Tech LLM moat.

🏆 Why TechCrunch is the Bellwether

The shift from the LLM race to Agentic AI is a classic platform disruption—and a debut at Tech Crunch is still the unparalleled launchpad. Why? Because the conference isn’t just about technology; it’s about market validation.

History is our guide. Companies that launched at TechCrunch Disrupt didn’t just have clever tech; they had a credible narrative for how they would fundamentally change human behaviour, capture mindshare, and dominate a market. The intensity of the Startup Battlefield 200, where over 200 hand-selected, early-stage entrepreneurs compete, forces founders to distil their vision into a five-minute pitch that is laser-focused on value.

This focus is the very thing that the venture capital community is desperate for right now. Investors are no longer underwriting the risk of building a foundational LLM—that race is lost to a handful of giants. They are now hunting for the applications that will generate massive ROI on top of that infrastructure. When a respected publication like techcrunch.com reports on a debut, it signals to the world’s most influential VCs—who are all in attendance—that this isn’t science fiction; it’s a Series A waiting to happen.

The successful TechCrunch Disrupt 2025 startup will not have a “better model.” It will have a better system—a goal-driven Agent that can execute, self-correct, and deliver measurable business outcomes without constant human hand-holding. This is the transition from AI as a fancy word processor to AI as a hyper-competent, autonomous employee.

Conclusion: The Era of Doing

For years, the LLM kings have commanded us with the promise of intelligence. We’ve been wowed by their ability to write sonnets, simulate conversations, and generate images. But a truly disruptive technology doesn’t just talk about solving a problem; it solves it.

The Agentic AI revolution marks the transition from the Era of Talking to the Era of Doing.

The biggest LLM is now just a powerful but inert, brain—a resource to be leveraged. The true innovation is in the nervous system, the memory, and the self-correction loop that transforms that raw intelligence into measurable, scalable, and autonomous value.

Will this new era, defined by goal-driven, Agentic AI, be the one that finally breaks the LLM monopoly and truly disrupts Silicon Valley? Let us know your thoughts below.

The data points are no longer scattered anomalies; they are coalescing into a bleak, unmistakable pattern. A thousand stores here, three hundred there—the cumulative count of recent hamburger chain restaurant closures across the American landscape now resembles the casualty tally of a protracted, ill-advised war. This is not the typical cyclical contraction of the casual dining sector, nor can it be dismissed as a mere post-pandemic hangover. What we are witnessing is a seismic cultural shift, a profound and perhaps permanent re-evaluation of the entire fast-food premise by a newly discerning, financially strained, and digitally native public. The golden arches are dimming, the King’s castle is crumbling, and the clown is packing his oversized shoes. The foundational promise of speed, ubiquity, and uniform cheapness that powered this industry for seventy years is now the very liability driving its demise. This is not an economic adjustment; it is a cultural reckoning, signalling nothing less than the End of fast food as We Know It.

The Economic Cracks: A Debt-Ridden Colossus Topples

To understand the industry’s fall, one must first appreciate the inherent, almost hubristic, flaws in its architecture. The financial crisis unfolding now has its roots in decades of aggressive, often reckless, expansion fueled by an unsustainable debt model. Major fast-food corporations—often structured as heavily franchised entities—encouraged, if not mandated, an ever-increasing physical footprint. This strategy was predicated on perpetually cheap capital and a perpetually compliant consumer base. As a result, the industry became a stretched rubber band that finally snapped under the weight of modern economic reality.

Rising operating costs have intensified this pressure to an intolerable degree. The price of essential ingredients—meat, produce, oil—has become volatile and persistently high, squeezing margins already razor-thin at the traditional $5 meal mark. Simultaneously, the unavoidable necessity of raising labour wages, even marginally, has chipped away at the core economic logic of the model, which was built on the premise of low-skill, low-cost human labor. The simple math of 1970 no longer computes in 2025.

Adding insult to this financial injury is the self-inflicted wound of menu fatigue. In a desperate, often nonsensical, bid to recapture declining traffic, chains have introduced a dizzying, often contradictory array of limited-time offers and peripheral items. From specialty dipping sauces to bizarre international collaborations, the relentless pursuit of novelty has diluted the core value proposition. Does the consumer truly want a spicy barbecue bacon sourdough melt from a place famous for a simple patty and bun? This constant churn of inventory and preparation complexity strains kitchen operations, slows service, and ultimately confuses the customer, eroding the reliable, comforting simplicity that was once the industry’s hallmark. The debt is no longer serviceable, the product is no longer essential, and the operating environment is actively hostile. The system is structurally compromised.

The Cultural Reckoning: Premiumisation and the Liability of the Storefront

The most significant accelerant for these sweeping closures is the profound shift in consumer priorities. The modern diner, regardless of income bracket, is increasingly hostile to the industrial, factory-line approach to food preparation. The days when convenience and rock-bottom price trumped all other considerations are drawing to a close. Consumers are now demanding premiumization: better quality ingredients, transparency in sourcing, and, crucially, a product that feels crafted rather than assembled. This preference has empowered the “better burger” movement—local, regional, and speciality chains that charge two or three times the price of the legacy product but deliver a demonstrably superior experience. Why settle for a machine-pressed patty when, for a few dollars more, one can have hand-smashed beef on a brioche bun?

This cultural pivot has rendered the traditional fast-food dining experience—or the stark absence of one—a major liability. The plastic booths, the glaring fluorescent lights, the perfunctory service—it all screams of an anachronism. The act of eating a quick meal in a brightly lit box has lost its relevance. If the food is merely fuel, the environment is irrelevant. But if the food is an experience, the environment is everything. As a result, the vast, expensive real estate holdings of these chains—the drive-thrus, the ample parking lots, the indoor seating—are no longer assets generating return. They are millstones, dragging down balance sheets.

The true revolutionary factor is the digital migration. The pandemic accelerated the adoption of delivery and takeaway to such an extent that the physical shopfront’s primary function shifted from being a destination to a preparation hub. This shift has given rise to the phenomenon of ghost kitchens and virtual brands. These highly efficient, low-overhead operations—unburdened by real estate taxes, dining room staffing, or exterior aesthetics—can compete aggressively on price and speed, specialising in delivery-only models. Are the traditional chains not, in essence, just expensive, inefficient ghost kitchens with customer seating? The rise of the virtual kitchen exposes the exorbitant cost and redundancy of the legacy, brick-and-mortar operation. The market is teaching us that the most valuable part of a hamburger chain is the recipe and the logistics, not the building on the corner.

Conclusion and Future Forecast: The End of Fast Food’s Monolithic Era

The current wave of hamburger chain restaurant closures is a powerful, undeniable sign that the old covenant between corporate America and the casual diner has been broken. The illusion that a mediocre product, sold ubiquitously, could sustain an ever-expanding, debt-laden empire has finally shattered. The seismic cultural shift away from cheapness at all costs is permanent, driven by a simultaneous desire for better food and a better consumer experience, be that at a local artisanal spot or through a frictionless, digital transaction.

The chains that survive this reckoning will bear little resemblance to the monolithic empires of their heyday. They must confront their unsustainable debt model and radically shrink their physical presence. The future of the successful ‘fast-food’ entity will be defined by hyper-efficiency and hyper-specialisation. We are likely to see a proliferation of small-format, highly automated, delivery-focused outlets—essentially converting the existing brand into a sophisticated, national network of ghost kitchens and drive-thru-only express lanes. Technology, once a tool for convenience, will become a survival imperative, minimising the expensive human element while maximising delivery logistics.

The future of the hamburger is binary: either it is a high-craft, local indulgence defined by premiumization and a genuine dining experience, or it is a highly standardised, algorithmically managed virtual product delivered to your door. The comfortable, middle-ground mediocrity that sustained the giants is now a zone of extinction. The era of the giant, identical fast-food box on every highway exit is fading. The market has spoken: the consumer values quality and convenience delivered on their terms, not on the terms dictated by the corporations’ quarterly earnings reports. The fast-food industry, as we have always known it—a symbol of mid-century industrial efficiency and mass-market uniformity—is over. Its legacy is now merely a cautionary tale about the perils of believing that perpetual growth is an entitlement, rather than an achievement.

Discover how Arby’s Steak Nuggets highlight consumer trends, branding strategies, and lessons every startup can apply to disrupt their market.

When Arby’s unveiled its Steak Nuggets, it wasn’t simply adding another protein option to the menu. It was making a strategic move into a space long dominated by chicken nuggets. By offering bite-sized, seared steak pieces—without breading—Arby’s positioned itself as the disruptor of a familiar format.

This is a classic example of category innovation: taking a product consumers already love and reimagining it in a way that feels fresh, premium, and aligned with evolving tastes. In an era where protein-rich diets and “better-for-you” indulgences are trending, Arby’s tapped into a cultural moment that values both convenience and quality.

📈 Market Relevance and Consumer Behavior

The launch of Arby’s Steak Nuggets reflects several broader consumer and market trends:

• Protein as a Lifestyle Choice: With fitness culture and high-protein diets on the rise, consumers are seeking alternatives to carb-heavy fast food. Steak Nuggets deliver on that demand.
• Premiumization of Fast Food: By using steak instead of chicken, Arby’s elevates the nugget into a more indulgent, higher-value product. This aligns with the “affordable luxury” trend, where consumers treat themselves without breaking the bank.
• Convenience Meets Quality: Arby’s recognized that steak, while beloved, is often inconvenient to eat on the go. Steak Nuggets solve that problem, making premium protein portable.

For startups, the lesson is clear: find the friction in consumer behavior and design a product that removes it.

💡 Business and Marketing Insights for Entrepreneurs

So, what can founders and marketers learn from Arby’s Steak Nuggets?

1. Reframe the Familiar
   • Innovation doesn’t always mean inventing something entirely new. Sometimes, it’s about taking a familiar product and reframing it for a new audience or occasion.
2. Leverage Cultural Shifts
   • Arby’s capitalized on the cultural obsession with protein and wellness. Startups that align their offerings with lifestyle trends can ride the wave of consumer demand.
3. Brand Consistency with Evolution
   • Arby’s tagline, “We have the meats,” has long positioned the brand as the protein authority. Steak Nuggets are a natural extension of that promise, showing how to evolve without losing brand identity.
4. Create Buzz Through Differentiation
   • By boldly challenging the chicken nugget monopoly, Arby’s sparked conversation. For startups, differentiation isn’t just about product—it’s about narrative.

🚀 Takeaway for Startup Leaders

The story of Arby’s Steak Nuggets is a reminder that innovation often lies at the intersection of consumer desire and brand authenticity. Entrepreneurs don’t need to reinvent the wheel—they need to reimagine it in a way that feels timely, relevant, and irresistible.

For founders looking to make their mark, the question isn’t just “What can we create?” but “How can we reframe what already exists to meet today’s cultural and consumer needs?”

Final Thought: Arby’s Steak Nuggets may be bite-sized, but the business lessons they offer are anything but small. For startups, they’re proof that with the right mix of timing, branding, and consumer insight, even the most familiar product can become a market disruptor.