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AI & TECH

Nathaniel Whittemore declares Q2 the onset of AI’s second moment

Monday, June 1, 2026 · from 2 podcasts
  • Legacy security cannot parse AI agent intent, treating accidental data wipes as legitimate commands.
  • Anthropic seized 70% of new enterprise buyers in Q1 as firms aggressively deploy autonomous workers.
  • The Pentagon blacklisted Anthropic over military use, triggering a user exodus to OpenAI.

Nathaniel Whittemore on The AI Daily Brief declares the second quarter of 2026 the start of AI’s ‘second moment’ - the pivot from assistants to autonomous, workable agents. The evidence is in the revenue. Claude Code’s annualized run rate jumped from $1 billion to $2.5 billion in just two months.

Enterprises are buying agents to replace people, not just software seats. Block cut 40% of its staff as a portent, and Pulsia, a fully agentic company, hit $6 million in revenue with one founder. According to Ramp data cited by Whittemore, Anthropic now captures 70% of new enterprise AI buyers, leaving OpenAI with 25%.

"AI’s first moment was the chatbot. The second is the workable agent."

- Nathaniel Whittemore, The AI Daily Brief

This aggressive deployment creates a novel security crisis that legacy tools cannot solve. On No Priors, Onyx Security CEO Maxim Bar Kogan explains the context gap. If an AI agent is authorized to manage a database, a traditional security tool sees a ‘delete’ command as legitimate. It cannot distinguish between a requested cleanup and a hallucinated catastrophe, leaving companies one reasoning loop from a total data wipe.

The structural solution isn't another frontier model. Supervising a $1 task with a $2 guardian model is a financial non-starter. Bar Kogan’s architecture uses small, specialized ‘not smart’ models to flag anomalies in real-time, only invoking a powerful guardian for high-stakes decisions - a blitz chess approach to security.

A deeper trust barrier locks out the model labs themselves from providing security. Enterprises fear handing historical interaction data back to OpenAI or Anthropic for auditing, worried it will fuel future model training. Bar Kogan compares labs to car dealers - you don’t ask the seller to be the sole safety inspector.

"Structural independence is the primary hurdle for labs like OpenAI or Anthropic in the security space."

- Maxim Bar Kogan, No Priors

The national security rift has shattered any remaining neutrality. After Anthropic refused Pentagon demands to allow Claude’s use in autonomous weaponry, the Defense Secretary designated the U.S. firm a supply chain risk. OpenAI immediately signed a deal with the Department of War. The public reaction was tribal: ChatGPT saw a 775% surge in one-star reviews, while Claude hit number one in the App Store.

The enterprise AI stack is now bifurcating: agents from one set of vendors, security from another, all under the shadow of a geopolitical standoff.

Source Intelligence

- Deep dive into what was said in the episodes

The Case for an AI Token TaxMay 28

  • Nathaniel Whittemore declares Q2 2026 as the onset of AI's 'second moment', shifting from viable AI assistants to workable agentic systems, with higher stakes across capabilities, economics, and corporate strategy.
  • Cloud Code's annualized revenue grew from $1 billion to $2.5 billion in just a couple of months during Q1 2026. Cloud Co-Work, launched in January, triggered emergency meetings at Microsoft.
  • Hyperscalers plan to spend $650 billion on capex in 2026, tripling their spending from a couple years prior and exceeding the inflation-adjusted cost of the US interstate highway buildout.
  • Cursor doubled its annualized revenue to $2 billion this quarter. Lovable reached $400 million ARR with a $100 million jump in one month. Replit projects $1 billion ARR by end of 2026.
  • Anthropic's share of first-time enterprise AI buyers jumped to 70%, with OpenAI at 25%. Anthropic hit a $19 billion run rate, closing the gap on OpenAI's approx. $25 billion.
  • Gartner bets 40% of enterprises will have working agents in production by end of 2026. Pulseia, a platform for building agentic companies, reached $6 million ARR with zero employees.
  • The dominant AI value shifted from time savings to increased output and new capabilities. Time savings use cases dropped from 19.9% of surveyed use cases in January to 13.6% in February.
  • Anthropic research found an 80% capability gap in legal work, where AI could handle tasks but only 15% saw adoption. Finance firms reported low AI impact with 91% citing data quality as the biggest obstacle.
  • HR deployment of AI grew 320% in 12 months, from 19% to 61% adoption. Seven US states now have AI employment regulations.
  • The Pentagon designated Anthropic a supply chain risk after a dispute over Claude's use in military operations, leading to a lawsuit. OpenAI's subsequent deal with the Department of War triggered a 775% surge in one-star reviews for ChatGPT.
Also from this episode: (5)

AI & Tech (3)

  • Nine major frontier AI models shipped in Q1 2026, including GPT 5.2 Codex, Genie 3, Opus 4.6, GPT 5.3 Codex, and Sonnet 4.6. Benchmarks show constant jockeying with no single winner across all use cases.
  • Agent platform Open Claw became the most starred open-source project on GitHub ever. Nvidia CEO Jensen Huang called it potentially the most important software release ever.
  • The market for Generative Engine Optimization (GEO) was under $1 billion in 2025 but is projected to reach nearly $34 billion by 2034.

Business (1)

  • The 'SaaS Apocalypse' narrative took hold as investors feared AI was 'too good', leading to market carnage. Block cut 40% of its staff, cited as a portent for aggressive AI-era recalibration.

Coding (1)

  • 71% of surveyed practitioners 'vibe coded' in the past month. 62% had automation or agentic use cases. The average respondent uses 3.5 different AI models.

Building an AI Guardian for Enterprise with Onyx Security CEO Maxim Bar KoganMay 28

  • Onyx Security trains models and builds agents to oversee other AI agents, aiming to detect illegitimate actions as enterprise AI adoption grows exponentially.
  • Maxim Bar Kogan states autonomous agents like coding assistants are the fastest-growing category in enterprises, outpacing low-code automation platforms.
  • Kogan argues existing security tools like identity management and API monitoring lack the context to understand the intent of flexible AI agents, creating new control gaps.
  • Onyx's approach uses small, specialized models to efficiently flag high-risk AI actions, reserving more powerful analysis only for critical moments to manage cost and latency.
  • Kogan sees Mithril-level AI models dramatically lowering the cost of vulnerability discovery, forcing security teams to implement foundational controls quickly.
  • He believes independent oversight is crucial because enterprises distrust vendors auditing their own products and need solutions adaptable to multiple AI providers.
  • Kogan notes enterprises are unwilling to share historical agent behavior data with Anthropic or OpenAI due to those companies' data-hungry training practices.
  • Auto-GPT's early demonstration of autonomous agents ignited market imagination, highlighting the potential and risks of AI performing complex computer tasks.
  • Kogan asserts the core challenge of AI oversight is interpreting agent intent, not just proxying data, which requires understanding what AI systems 'think'.
  • Onyx's founding insight was the need to control increasingly smart AI agents, especially as they begin managing critical infrastructure like power grids.
Also from this episode: (4)

Startups (1)

  • The Israeli tech ecosystem excels at understanding security team workflows and building products tailored to their daily operational needs, according to Kogan.

AI & Tech (3)

  • He predicts mechanistic interpretability of AI models will advance significantly as smarter AI systems emerge, aiding in understanding and controlling intelligence.
  • Financial institutions like JP Morgan adopt AI cautiously due to high risk profiles, contrasting with startups that aggressively deploy agents to gain competitive edge.
  • Kogan advocates for gradual, controlled release of Mithril-level AI models to allow enterprise security teams time to develop defenses and prevent catastrophic failures.