All AI News

External (via Citation)June 19

http://training.besuper.ai/

The Superintelligent Training Hub offers two AI programs for executives: Executive Catch Up, a 4-week sprint at 3–5 hours per week, and Executive Agent Leadership, a 6-week program at 5–7 hours per week. Executive Catch Up builds a personal AI team including a research analyst, communications lead, and chief of staff agent; Agent Leadership goes further, producing multi-agent systems, MCP integrations, and a 7-artifact governance and adoption playbook. Both programs are tool-agnostic, work within existing enterprise security environments, and emphasize durable architecture over prompt tricks. The platform reports 400+ organizations and 5,600+ individual participants, including Fortune 100 companies. It is built by Superintelligent, Nathaniel Whittemore of The AI Daily Brief, and lead facilitator Nufar Gaspar, who has trained 14,000+ engineers and executives across 30 countries.

3 minRead

The AI Daily Brief (Nathaniel Whittemore)June 12

https://aidailybrief.ai/

Anthropic's Fable 5 launch triggered the AI industry's most significant public backlash to date, forcing the company to reverse a core policy within 24 hours. Beyond the specific policy dispute, critics flagged a 30-day data retention clause affecting even zero-retention enterprise customers, with Anthropic retaining discretion to review flagged prompts — prompting at least one legal professional to recommend blocking Claude entirely. The deeper concern is structural: commentators argue Anthropic's market position gives a single private company unprecedented control over developers, enterprise customers, and AI access broadly. Separately, OpenAI filed for an IPO and declared a new phase of AI development, while Texas moved to establish data center infrastructure standards that could serve as a national model. Altimeter's Brad Gerstner warned that AI companies may need to address growing public skepticism directly, noting the instability of generating trillions in private value while 80% of Americans view the technology with suspicion.

3 minRead

External (via Citation)May 25

After Automation

Every, a 30-person AI-native company, reports that aggressive AI automation has produced more human work, not less, contradicting the dominant narrative of job elimination. The company uses Codex, Claude Code, and multiple internal agents across all functions, with AI handling 95% of the CEO's email, yet headcount has grown and human roles remain essential. The author's thesis is structural: AI commoditizes explicit, trainable knowledge, which collapses the value of generic output and simultaneously increases demand for differentiated human expertise. Benchmark data is dramatic—frontier models now score 85% on real-world economic tasks and 80% on 4-hour expert assignments—but practical deployment reveals that both delegation-style agent workflows and deep human-AI collaboration tools still require skilled human judgment to function effectively. The conclusion is that approaching AGI does not trigger a tipping point eliminating jobs; it intensifies the market for expert human work that produces non-default output.

3 minRead

External (via Citation)May 24

Codex Maxxing

Jason Liu describes how OpenAI's Codex app has shifted his workflow beyond coding into broader knowledge work, with the key innovation being persistent, durable threads that accumulate context over months rather than resetting with each session. He maintains pinned megathreads for specific workstreams tied to an Obsidian vault structured as a GitHub repo, allowing the agent to write durable, diffable memory files that survive thread expiration or compaction. Voice input via tools like Wispr Flow lets him feed raw, unpolished thinking to the agent, while a steering feature enables queuing sequential instructions during active tool calls without waiting for each step to complete. The system distinguishes between browser, Chrome, and computer-use modes depending on whether tasks require local inspection, authenticated sessions, or GUI interaction. The net result is a personal operating loop where AI agents read from shared memory, act on live systems, and write structured outputs rather than generating isolated chat responses.

3 minRead

External (via Citation)May 18

Cut Off

Frontier AI access is splitting into a privileged tier for select U.S.-based partners and a restricted tier for everyone else, driven by three compounding forces: security concerns, government intervention, and compute scarcity. Anthropic's Mythos cybersecurity model and OpenAI's Daybreak initiative both launched with limited partner lists, signaling this is structural rather than incidental. Distillation by fast followers like DeepSeek — reportedly a key factor in closing a 6-9 month capability gap — is accelerating developer and government pressure for tighter API access controls, stricter KYC, and geopolitically conditioned availability. Unlike software, frontier AI inference carries high marginal compute costs, making universal access economically nonviable during periods of chip scarcity. Middle powers and non-U.S. firms banking on broad frontier access as a strategic equalizer need to revise that assumption now.

3 minRead