Tech Needs BEST: BEtter and faST

There has always been a Management dichotomy between Fast and Better.

What route should an organization take?

Being Fast

The first to strike the market, strikes twice. This idea echoes Sun Tzu’s Art of War:

"Whoever is first in the field and awaits the coming of the enemy will be fresh for the fight; whoever is second in the field and has to hasten to battle will arrive exhausted."

A perfect example is ChatGPT. OpenAI’s LLM wasn’t the first of its kind, but it was the first to open a user-friendly chat platform that actively incorporated human feedback. This innovative move fast-tracked model improvement, creating a seismic market shift. ChatGPT became one of the fastest-adopted technologies in history, gaining 1 million users in just five days post-launch in November 2022.

Today, ChatGPT's website attracts approximately 3.5 billion visits monthly (October 2024), as per Similarweb data. For context, Google garners 85 billion, YouTube 29 billion, and Wikipedia 4 billion monthly visits. Despite lacking a clear business model, OpenAI’s rapid success has redefined tech adoption and set a precedent for future innovations.

Fast forward to now, and the LLM market is growing at breakneck speed. In late 2022, the market revolved around a single product—ChatGPT. Today, platforms like Hugging Face catalog nearly one million LLMs, although many remain experimental. ChatGPT’s first-mover advantage secures its leadership position, at least for now.

Being Better

In December 2024, Amazon has entered the LLM arena with Amazon Nova. While its name might raise eyebrows (especially in Spanish-speaking markets), Nova introduces notable advancements:

1. Segmentation: Nova segments its offerings based on specific use cases—Nova Micro, Lite, Pro, Premier, Canvas, and Reel. This product-oriented segmentation is an improvement over OpenAI’s approach, which can seem more engineering-driven than customer-focused. OpenAI’s product names, such as "GPT-3.5 Turbo," "4.0 Mini," and "DALL·E 3," may resonate with developers but often confuse end-users. In contrast, Amazon's categorization feels more accessible, prioritizing clarity for customers.
2. B2B-Focused Delivery: Rather than offering a public-facing chat interface, Amazon embeds Nova into Amazon Web Services (AWS), targeting businesses directly. This aligns with the current trend where enterprise solutions represent the most significant revenue opportunities. While Google (via Google Cloud Gemini) and Microsoft (through Azure OpenAI) are also B2B-oriented, their strategies reflect their broader corporate cultures. Google, primarily driven by ad revenue, lacks a mature B2B focus. Microsoft, with its legacy of aggressive software sales, is still transitioning to a more consultative model. Conversely, Amazon’s e-commerce roots emphasize adapting to customer needs—making AWS particularly adept at tailoring solutions for businesses.
3. Competitive Pricing: Scaling LLMs for enterprise use can be prohibitively expensive. Usage is measured in "tokens," and costs can skyrocket when applying LLMs to large datasets, such as customer interactions at scale. Amazon’s pricing strategy is explicitly designed to undercut competitors, promising costs 3-4 times lower than OpenAI, while committing to continuous performance improvements. By embedding Nova into AWS's Amazon Bedrock platform, Amazon exclusively serves B2B clients, offering favorable terms for enterprises over consumer-grade products.

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The Strategic Imperative: BE-ST (BEtter and faST)

In today’s hyper-competitive LLM landscape, striking the right balance between speed and quality is critical. While Amazon, META (with LlAmA), Anthophic (with Claude) and OpenAI dominate the conversation, quieter players like Apple, Samsung, Sony, Oracle, Adobe, SAP, and Cisco may soon make impactful moves. Even non-tech giants like Tesla, Visa, Netflix, Disney, and Walmart have potential roles to play.

The winning formula? The company that better fulfills a customer need, faster than anyone else will take the lead.

When ChatGPT reached 1 million users in five days, it wasn’t just because of technological brilliance. The real insight lies in how quickly technology is commoditized. Over the past two decades, tech companies enjoyed longer cycles to refine and dominate markets. Today, that window has shrunk dramatically—often to mere days.

As tech evolves into a mature market, its management must shift from supply-side innovation to demand-driven strategy. Leaders with marketing backgrounds—like Microsoft’s Satya Nadella—understand this shift and build offerings based on customer needs, working backward from there.

Always "market listening on" culture is an must to take the lead in such a market.

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Conclusion

LLMs are no longer a novel innovation; they’re in a competitive market. Success will come to those who adapt to the market speed and demands. This isn’t new in business, but the pace of change is unprecedented for tech.

Now more than ever, tech needs BEST—BEtter and faST.

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KEY TAKEAWAYS:

• The adoption of Large Language Models (LLMs) is accelerating rapidly, with consumer technology adoption outpacing previous trends.
• New market entrants are enhancing and refining their offerings to gain a competitive edge.
• Consumer segmentation, (needs identification and attribute quantification) and Marketing Mix Modeling have become integral to the tech industry's strategic landscape.

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* I’ve written this text myself, but I have improve it with the help of a temporary chatGPT session as I am not a native English speaker.

** all the images come from unsplash where human creativity still lives. (Thanks to Astrid Schaffner, Harley-Davidson, Skye Studios, feey and Trac Vu)

*** What to understand AI? Take 7 slots of 2 hours and see this Harvard Playlist: https://www.youtube.com/playlist?list=PLhQjrBD2T381PopUTYtMSstgk-hsTGkVm