Who This Is For: Candidates Preparing for Product Manager (PM) Roles at North American Tech Companies — This Guide Solve

Week One Content Strategy: Establishing Thought Authority

Monday/Tuesday/Thursday: Pure Insight Posts | No Product Links

Goal: Position yourself as a forward-thinking, opinionated expert

Wednesday: Focus on Interview Pain Points | Naturally Introduce the PM Interview Guide

Goal: Reach job seekers during high-intent periods and convert trust into action

Friday: Practical Resume Tips | Drive Toward Resume Optimization Services

Goal: Solve frequent, urgent needs and foster private community growth and conversion

Recommended Posting Time: 10:00 PM Beijing Time (7:00 AM Pacific Time), strategically timed to capture peak engagement from both Chinese and U.S. audiences.

Week One – In-Depth Content Breakdown

#1 | Tech Trend Analysis: The 3 Most Overvalued AI Companies in 2026

Technical Real ≠ Valuation Justified

Artificial intelligence is undoubtedly the core driver of the next decade — but that doesn’t mean today’s valuations of AI companies are rational. As during the 2000 dot-com bubble, groundbreaking technology existed, yet capital frenzy inflated prices far beyond fundamentals.

Today, we’re not debating whether AI matters. We’re taking a sober look at three AI firms currently valued extremely high, yet still lacking robust commercial validation: OpenAI, xAI, and Perplexity.

OpenAI — Model Leadership ≠ Durable Moat

• Valuation: $500 billion
• Projected 2025 Revenue: $13 billion
• Projected Loss: Over $100 billion

While ChatGPT boasts 800 million monthly active users, its paid conversion rate remains below 5%. The vast majority are casual users who haven't integrated the tool into daily workflows. If Anthropic, Google Gemini, or Meta Llama close the technical gap, user switching costs approach zero.

More importantly, OpenAI lacks a true entry point. Google owns search. Meta owns social graphs. Amazon owns e-commerce. OpenAI’s primary assets? An API and a chat interface. When technological lead shrinks month by month, first-mover advantage alone can’t sustain monopoly.

Its funding model also raises red flags. NVIDIA invests in OpenAI, then sells it GPUs. AMD grants warrants; Oracle provides infrastructure in exchange for visibility. This cross-promotional capital loop feels less like independent business viability and more like a coalition building a shared narrative.

Remember: Real moats aren’t built on supplier dependency — they’re built on user addiction.

xAI — Musk’s Narrative Outpaces Product Validation

Musk’s xAI recently hit a $50 billion valuation, yet has only two public deliverables: the Grok chatbot and the Colossus supercomputing cluster.

• Grok’s daily active user metrics remain undisclosed
• Colossus is indeed one of the world’s largest GPU clusters (~100,000 H100s)

But let’s be clear: Infrastructure scale ≠ product success. SpaceX succeeded because of reusable rockets, consistent launches, and revenue generation — clear proof of product-market fit (PMF). xAI has yet to demonstrate PMF for any product.

xAI’s $50B valuation rests not on quantifiable results, but on a collective belief that "Musk will pull off another miracle." Investors should be cautious: storytelling talent doesn’t compensate for missing financials.

Perplexity — Great Product ≠ Sustainable Business

As an AI-native search engine, Perplexity offers a superior user experience over traditional search. Its latest valuation: $9 billion.

But competitive threats loom:

• Google can do AI search — it just hasn’t fully switched
• Once Google transitions to AI-native search, Perplexity's key differentiator will vanish overnight

Search is fundamentally about traffic access and ad monetization. Google controls Chrome, Android, Gmail, and YouTube — forming a closed-loop ecosystem. Perplexity only controls a website and an app.

A great product doesn’t mean a sustainable business. A viable business isn’t guaranteed investment at premium multiples. Perplexity’s $9B price tag assumes enduring market dominance — expectations, not verified growth pathways.

Conclusion: Right Trend ≠ Right Timing

These three companies share a trait: they’re advancing technology, but their valuations are built on collective belief.

History reminds us — the internet transformed the world, but most who bought internet stocks in 2000 didn’t break even for a decade. AI will likely reshape global industries, but investors entering at faith-driven prices may not survive long enough to collect returns.

The hardest part of investing isn’t identifying trends — it’s determining whether the price is rational.

As Duan Yongping said: “Don’t invest in what you don’t understand.”
I’ll add: “Even

if you do understand it, don't overpay just because the hype is loud. In the context of your PM interview preparation, this translates directly to solution design: the hardest part isn't generating feature ideas, but determining whether a proposed solution is rational given the company's specific constraints, stage, and user reality. Don't advocate for a complex AI rollout if the core data infrastructure is broken; understand the fundamental business mechanics before prescribing a cure.

To apply this mindset during your upcoming interviews, keep these principles in mind:

• Validate Before Scaling: Always question the underlying assumptions of a feature before discussing its implementation details.
• Context Over Complexity: A simple solution that fits the company's current maturity is infinitely more valuable than a "perfect" one that requires resources you don't have.
• First Principles Thinking: Break problems down to their core truths rather than copying trends from other tech giants blindly.

Your unique perspective is your greatest asset, so trust your ability to reason through chaos. Go into that interview room with confidence, knowing you are ready to build products that truly matter.