NVIDIA falls as investors trim tech exposure ahead of earnings

2 min read     Updated on 13 Jul 2026, 07:35 PM
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AI Summary

NVIDIA Corp. shares declined over 1% in premarket trading as investors reduced exposure to high-growth tech stocks and equity futures weakened. Tech strategist Dan Ives noted a rotation into memory stocks but affirmed NVIDIA's critical role in AI infrastructure. The stock is navigating key technical levels ahead of its Aug. 26, 2026 earnings release, where revenue is projected to nearly double year-over-year.

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NVIDIA Corp. stock fell more than 1% in Monday's premarket session as investors trimmed exposure to high-growth technology stocks. Nasdaq futures dropped 1.12%, while S&P 500 futures declined 0.39%, applying pressure to semiconductor names. The stock is trading near a critical technical area, leaving short-term traders divided between buying recent weakness and taking profits following a strong rally.

Tech strategist Dan Ives told CNBC on Monday that investors have rotated toward memory stocks, viewing them as the "shiny new toy." This shift has placed NVIDIA and some hyperscalers under pressure despite their central role in artificial intelligence. Ives stated that NVIDIA remains the company powering the AI revolution, led by CEO Jensen Huang. He questioned the sustainability of the memory trade without NVIDIA and hyperscalers driving AI infrastructure spending. The upcoming second-quarter tech earnings season will be crucial for demonstrating AI monetization, with demand still sharply exceeding supply.

Technical Analysis

NVIDIA traded at $208.25 in premarket action. The stock remained 2.9% above its 20-day simple moving average of $201.95 but slipped 0.6% below its 50-day simple moving average of $209.20. The longer-term trend is constructive, with NVIDIA trading 5.1% above its 100-day simple moving average of $197.71 and 8.4% above its 200-day simple moving average of $191.67. The 20-day moving average is below the 50-day moving average, a bearish crossover signaling potential choppy trading. However, the 50-day moving average stays above the 200-day moving average, indicating the broader uptrend remains intact.

Momentum indicators are encouraging, with the moving average convergence divergence (MACD) holding above its signal line and a positive histogram suggesting easing downside momentum. Key technical levels include resistance near $214 and support around $199.50. NVIDIA reached a 52-week high of $236.54 in May before forming a swing low in June and slipping below a support level in July.

Earnings And Analyst Outlook

The next major catalyst is NVIDIA's estimated earnings release on Aug. 26, 2026. Wall Street expects earnings of $2.07 per share, up from $1.04 a year earlier. Revenue is projected to reach $91.70 billion, compared with $46.74 billion in the prior-year period. The stock trades at about 32.3 times earnings. Analysts maintain a consensus Buy rating with an average price forecast of $323.83.

Firm Action Date Price Forecast
China Renaissance Initiated Coverage June 5 $319
Needham Maintained June 2 $270
DA Davidson Maintained June 1 $300

Market Metrics

According to Benzinga Edge, NVIDIA scores strongly on momentum, quality, and growth, while its value score remains weak due to premium valuation. The momentum score is 74.81, quality is 98.13, and growth is 98.62. The value score stands at 6.92.

NVIDIA is among the largest holdings in several exchange-traded funds, including the Global X NASDAQ 100 Covered Call ETF (QYLD) with a 9.66% weighting, the Sapient Quality Select ETF (SQS) with a 9.95% weighting, and the REX AI Equity Premium Income ETF (AIPI) with a 9.71% weighting. Significant ETF inflows or outflows can influence demand for the stock due to these large weightings.

How will NVIDIA's upcoming earnings report on Aug. 26, 2026, impact investor sentiment toward AI-related stocks?

What are the potential risks if the current rotation into memory stocks persists without NVIDIA and hyperscalers driving AI infrastructure spending?

Could NVIDIA's stock break below the key support level of $199.50 if the broader tech sector continues to face selling pressure?

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Nvidia engineers prefer building AI agents over coding

1 min read     Updated on 09 Jul 2026, 04:33 PM
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AI Summary

Nvidia CEO Jensen Huang announced a shift in software engineering where engineers now prefer building AI agents over writing Python code. This move reduces manual coding and allows focus on system design and safety. Industry peers like Marvell, AWS, and Microsoft are also investing heavily in agentic AI to drive infrastructure growth and productivity.

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Nvidia Corp. CEO Jensen Huang stated that artificial intelligence (AI) is reshaping software engineering by shifting developers away from repetitive coding tasks and toward building AI agents, systems, and tools designed to automate complex work. This transition signifies a fundamental change in technical skills required within the industry, as engineers prioritize the creation of autonomous systems over traditional programming.

Huang explained that the rise of "agentic systems" is creating a new category of technical skills. "These agentic systems are new skills and now we have a lot of software engineers building agents," Huang said. He added, "If you ask me, every one of my software engineers prefers to be building agents than to be writing Python code."

The Nvidia CEO emphasized that AI is reducing the amount of manual coding engineers perform. This shift allows professionals to focus on higher-level tasks such as designing AI systems, creating benchmarks, and developing safety measures known as guardrails. "You’re taking all the mundane work, and you’re trying to get this agent to do it," Huang said. "That requires imagination, that requires creativity, a lot of technology. I think that’s spot on."

Industry Leaders Embrace Agentic AI

The trend toward agentic AI is not limited to Nvidia. Marvell Technology Inc. CEO Matt Murphy previously indicated that AI agents could fuel increased spending on networking, optical connectivity, and custom silicon. As AI systems become more interconnected, they generate greater data traffic across clusters, driving infrastructure demand. Marvell cited stronger-than-expected AI infrastructure demand and raised its long-term growth outlook.

Amazon.com Inc. Web Services CEO Matt Garman also highlighted that agentic AI was reshaping software development. He noted that AI-powered tools are transforming productivity and business applications. AWS introduced new AI products and expanded partnerships, including access to OpenAI models. Garman predicted that "everything is going to be remade" by AI.

Microsoft Corp. CEO Satya Nadella reinforced the shift toward "agentic computing," stating that AI agents were becoming a central part of the technology ecosystem. Microsoft focused on expanding its AI infrastructure and developing AI systems for productivity, coding, and cybersecurity. The company reported that its AI business surpassed $37 billion in annual recurring revenue.

How will the transition to agentic AI impact the demand for traditional software engineering roles over the next decade?

What specific cybersecurity risks will arise as autonomous AI agents take over more complex decision-making processes?

Will the shift toward agentic systems accelerate the consolidation of market share among the largest cloud providers?

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