Secrets refer to any and all sensitive information that protects and authorizes access to systems—think: passwords, encryption keys, API keys, and more. And Infisical is a secrets management platform for developers and companies, offering the tech to securely store, change, and retrieve vital credentials. Founded in 2022 by Matsiiako with Tony Dang and Maidul Islam, Infisical’s now raised a $16 million Series A, led by Elad Gil. Y Combinator, Gradient, and Dynamic Fund participated, plus angels like Datadog CEO Olivier Pomel, Samsara CEO, and Valor CEO Antonio Gracias.

Key takeaways for each layer:

Infrastructure layer:
- AI infra buildout remains robust with no signs of slowing. Specialized AI clouds like CoreWeave are gaining momentum (the stock is up ~400% since IPO)
- "Chip-level" bottlenecks are giving way to "system-level" bottlenecks. These include areas like data center infrastructure, power transmission, and electricity generation itself. The US will need to add 10% to grid capacity in the next 5 years after 15 years of flat growth. This will be a key bottleneck.
- Infra players are moving up the stack. Historically, value migrates from the infra layer to app layer over time, much like what happened in the telecom and internet buildouts.

Model and Tooling layer:
- The model layer is becoming increasingly fragmented. OpenAI no longer has a monopoly; players like Anthropic, Google, xAI, Meta, DeepSeek are all vying for a piece of the pie
- Today’s SOTA models require ~100x more training compute than the original GPT-3.5. But the marginal returns to pure scaling are diminishing. RL will drive the next wave of improvements in AI.
- Innovation is moving beyond language models into other modalities such as physical world models and the sciences (e.g., drug discovery, material science, engineering design, etc.).
- Agent infrastructure is emerging with protocols like MCP and ACA. However, the ecosystem remains early-stage, with further development in agent infra needed before large-scale agent deployment.
- Edge AI is gaining traction as SLMs continue to improve. A 3B parameter model today can outperform the original 175B ChatGPT model.

Application layer:
- Enterprise budgets for GenAI continue to expand, shifting from one-off innovation spending to recurring functional line-item budgets.
- Software development remains the killer use case. “Vibe coding” was the hottest term in AI this year, with tools like Cursor, Loveable, and Bolt gaining significant adoption.

Financing/Others:
- AI companies now account for roughly half of all venture funding year-to-date, up from only ~15–20% in 2021/22.
- Valuations remain elevated, with many AI companies trading at 20–50x revenue. However, many of these companies are growing into their valuations. Cursor, for e.g.,, was the fastest company ever to scale to $500M ARR (in ~2 years) and now trades at a reasonable ~18x revenue.
- M&A activity has accelerated, with over $30B in transactions in first half alone, led by Meta/Scale, OpenAI/IO, and OpenAI/Windsurf.
- China is catching up across the stack with credible challengers in the model and application layer (DeepSeek, Manus AI). China’s abundant energy production give it an edge in system-level scaling but its biggest bottleneck remains advanced chip production.

The numbers on AI market concentration are staggering—and raise important questions about market structure and capital allocation.

Apollo's latest analysis reveals concentration across four key dimensions:

Market Cap: The Mag 7 commands 32% of S&P 500 market cap. Nvidia alone represents 7.4%—the highest single-stock weight since the 1980s. Tech's overall share matches dot-com peak levels.

Returns: Just 10 companies drove 55% of the index's total market cap gains since January 2021. The Mag 7 has outperformed the remaining 493 stocks by ~30 percentage points since April 2025.

Earnings: Mag 7 earnings growth hit 37% in 2024 but is projected to decelerate to 19% in 2025, while the rest of the S&P 500 shows anemic 6-8% growth. The divergence is widening, not narrowing.

Capex: Perhaps most striking—the Mag 7 now accounts for 31% of S&P 500 capex, up from 12% in 2019. Hyperscalers are spending nearly 60% of operating cash flow and 19% of revenue on capex, more than double the rate during the telecom bubble.

The concentration creates a paradox: slowing earnings growth coinciding with record capital intensity. Either we're in the early innings of a massive AI-driven transformation that will justify these investments, or we're witnessing capital misallocation at historic scale.