{{first_name | Hey}}, welcome back.
Today’s issue is about a16z building a new path for teen entrepreneurs, Anthropic and OpenAI kicking off an AI price war, and cybersecurity stocks racing ahead.
These are today's updates.
Give your AI agents just-in-time access with Opal Zero*
a16z launches a school for teen entrepreneurs
Anthropic and OpenAI cut AI prices within 1 hour
Cybersecurity stocks are climbing high on an AI payoff that hasn’t arrived
Tools, jobs, resources, and last issue’s winning prompt ⬇️
Together with Opal Zero
More AI agents means more access requests. Humans can’t review them all, and access can remain open long after it’s needed.
Opal Zero uses Paladin to evaluate access requests against policy and context, automating routine decisions while keeping humans in the loop for sensitive ones. With Opal Zero, you can:
Automate routine approvals at agent speed.
Scope and time-limit permissions to what agents actually need.
Escalate sensitive requests to humans when needed.
Enforce access through the gateway you already run.
Developed with Databricks, Faire, Elastic, and Superhuman.
Top News
The Horowitz Andreessen Academy (HAA) opens in 2028 as a for-profit school for high school graduates, blending trade school, Y Combinator, and Peter Thiel's Fellowship. It's raised $42 million and will charge elite-university tuition eventually. Its first cohort of roughly 50 students gets free tuition plus 200 mentors from founding partners including Anthropic, Google, Meta, OpenAI, and Nvidia.
CEO Gagan Biyani says the goal is teaching students to build, calling it “the most important skill in the AI era.” The school has listed a bunch of hiring partners that looks like a shortcut straight into companies like Anduril, Anthropic, Coinbase, Google, Meta, Nvidia, OpenAI, Palantir, Replit, and Stripe. The full list of founding partners, and what a year at the academy actually looks like, is laid out at theacademysf.com.
Anthropic released Claude Opus 5.5, priced 20% below Opus 5 and 40% cheaper on typical workloads, matching Fable 5.1's performance on most tasks. Anthropic's full benchmark breakdown shows exactly where those gains come from.
OpenAI answered within the hour with GPT-6 Sol and Luna, both 50% cheaper than their predecessors. Sol beat Opus 5 on automation benchmarks at a fraction of the cost, though that comparison was already outdated by the time it published. OpenAI has laid out the full pricing and performance numbers here.
GPT-6 API pricing comparison
Both launches came days after both companies called for a pause in frontier AI development. Slowing down, it turns out, doesn't apply to price wars, especially with Chinese open-weight models undercutting both labs.
The S&P Kensho cybersecurity index is up 41% this year against an 11% gain for the S&P 500, with CrowdStrike and Okta leading the charge on bets that AI-era threats will force bigger security budgets.
Okta jumped 27% and CrowdStrike 17% after their last earnings beat. Both climbed again last week on Anthropic and OpenAI's safety warnings alone. But the catch here is that revenue hasn't shown up yet. It's a valuation built on the expectation that AI risk turns into enterprise spending, without any evidence showing it already has.
Signals
Tools
Resources
Poll
Choose the prompt you want us to publish next
Market
Funding
Ridgeline raised $250M to build AI-native investment management software
Heidi raised $340M to build an AI care partner for clinicians
Roles in AI
Android Software Engineer at BJAK
Senior Applied ML Engineer - ML4Sys at Databricks
Think Tank
The video breaks down a shift that five major AI CEOs are independently pointing toward: the move from AI models and chatbots to autonomous systems and agents. For marketers, this could fundamentally change how people discover brands, how content gets surfaced, and even which metrics matter. Neil Patel explains what’s changing, why AI citations are becoming more important than Google rankings, and what marketers should start doing now.
Prompt of the Day
AI Pilot Evaluation Assistant
When to use this?
Use this while running an AI pilot to assess performance, uncover gaps, measure business impact, and determine what needs to happen before scaling.
You are an AI Pilot Evaluation Assistant.
Help users evaluate whether an AI pilot is worth scaling, needs refinement, or should be stopped. Turn messy pilot data, stakeholder feedback, and business context into a clear, decision-ready assessment.
When the user provides information about an AI pilot, assess it across:
Business impact: measurable outcomes, ROI, cost savings, revenue impact, or productivity gains
Adoption: usage, engagement, workflow integration, and user feedback
Technical performance: accuracy, reliability, latency, integration requirements, and scalability
Risk: security, privacy, compliance, governance, and operational risks
Economics: implementation costs, ongoing costs, resource requirements, and expected value at scale
Scalability: what would need to change to move from pilot to enterprise deployment
Ask only the most important follow-up questions when critical information is missing. Clearly distinguish known facts, assumptions, and estimates. Where possible, quantify impact and show the calculations or assumptions behind your conclusions.
Produce a concise executive-ready output with:
Pilot snapshot
What’s working
What isn’t
Key evidence and metrics
Risks and open questions
Scale-readiness assessment
Recommended next steps
Do not make decisions for the user. Instead, surface the evidence, trade-offs, and decision criteria they need to make a well-informed call. Tailor recommendations to the user's stated business goals, constraints, and risk tolerance.Get more such prompts in the Prompting Playbook (free for you)
Stay curious, {{first_name | reader}}
PS. If you missed yesterday’s issue, you can find it here.
