NVIDIA’s latest GPU rental prices on the Ornn Compute Price Index hit $4.95 per hour this week, up from $2.31 in early March : a 114% surge in six weeks.1
The price spread over prior-generation chips doubled from $0.28 to $1.80 per hour. The new chip is NVIDIA’s B200 (Blackwell); the prior generation is the H200 (Hopper).
Email Operations - Fragmented Approach:
┌─────────────────────────────────────────────────────────────┐
│ Claude Decision Tree │
├─────────────────────────────────────────────────────────────┤
│ Email Task → Should I...? │
│ ├─ draft_email.rb (2 params) │
│ ├─ send_email.rb (3 params) │
│ ├─ forward_email.rb (2 params) │
│ ├─ find_and_draft_reply.rb (3 params) │
│ ├─ read_email.rb (2 params) │
│ ├─ archive_emails.rb (1 param) │
│ └─ safe_send_email.rb (4 params) │
│ │
│ Result: Decision paralysis, multiple API calls │
│ Token Usage: ~150 tokens per operation │
│ Success Rate: 87% (context lost between calls) │
└─────────────────────────────────────────────────────────────┘
↓
CRM Operations - Scattered Functions:
┌─────────────────────────────────────────────────────────────┐
│ Company Research → Which tool? │
│ ├─ find_attio_company.rb │
│ ├─ create_attio_company.rb │
│ ├─ update_attio_deal.rb │
│ ├─ enrich_company.rb │
│ └─ validate_company.rb │
│ │
│ Problem: Context switching between 5+ tools │
│ Average: 3.2 tool calls per task │
└─────────────────────────────────────────────────────────────┘
Unified Email Tool - Comprehensive Context:
┌─────────────────────────────────────────────────────────────┐
│ unified_email_tool.rb │
├─────────────────────────────────────────────────────────────┤
│ Actions: [draft, send, reply, read, search, archive] │
│ │
│ Parameters: │
│ ├─ --action (6 options) │
│ ├─ --to, --cc, --bcc (recipients) │
│ ├─ --subject, --body, --body-stdin │
│ ├─ --from, --query, --folder (search) │
│ ├─ --sender, --in-reply-to (threading) │
│ ├─ --format [concise|detailed|ids_only] │
│ └─ --save-draft, --senders (batch ops) │
│ │
│ Result: Single confident decision │
│ Token Usage: ~45 tokens (70% reduction) │
│ Success Rate: 94% (full context maintained) │
└─────────────────────────────────────────────────────────────┘
↓
Unified CRM Operations - Complete Workflow:
┌─────────────────────────────────────────────────────────────┐
│ attio_operations.rb │
├─────────────────────────────────────────────────────────────┤
│ Actions: [find, create, update, search, enrich, │
│ validate_and_add, get_deals, update_deal] │
│ │
│ Intelligence Features: │
│ ├─ Auto-enrichment (--enrich flag) │
│ ├─ Format optimization (concise/detailed/ids_only) │
│ ├─ Source field management │
│ ├─ Deal pipeline integration │
│ └─ Notion page creation timing │
│ │
│ Result: End-to-end workflow in single call │
│ Average: 1.1 tool calls per task (89% reduction) │
└─────────────────────────────────────────────────────────────┘
Metric Improvements:
┌─────────────────────┬─────────────┬─────────────┬─────────────┐
│ Measurement │ Before │ After │ Improvement │
├─────────────────────┼─────────────┼─────────────┼─────────────┤
│ Token Usage │ 150/op │ 45/op │ 70% ↓ │
│ Tool Calls │ 3.2/task │ 1.1/task │ 66% ↓ │
│ Success Rate │ 87% │ 94% │ 7% ↑ │
│ Decision Time │ 2.3s │ 0.8s │ 65% ↓ │
│ Context Retention │ Fragmented │ Complete │ Qualitative │
└─────────────────────┴─────────────┴─────────────┴─────────────┘
Implementation Principles:
1. Parameter-rich interfaces > Simple function calls
2. Comprehensive context > Modular operations
3. AI ergonomics ≠ Human ergonomics
4. Batch operations > Sequential calls
Human Perspective (Intimidating):
┌─────────────────────────────────────────────────────────────┐
│ ffmpeg -i input.mp4 \ │
│ -vf "scale=1920:1080,fps=30" \ │
│ -c:v libx264 -preset medium -crf 23 \ │
│ -c:a aac -b:a 128k \ │
│ -movflags +faststart \ │
│ output.mp4 │
│ │
│ Human Preference: Separate commands for each operation │
│ ├─ scale_video.sh │
│ ├─ set_framerate.sh │
│ ├─ encode_video.sh │
│ └─ optimize_audio.sh │
└─────────────────────────────────────────────────────────────┘
↓
AI Perspective (Perfect):
┌─────────────────────────────────────────────────────────────┐
│ Single command with complete transformation context │
│ │
│ Benefits for AI: │
│ ├─ Understands full workflow intent │
│ ├─ Can optimize across all parameters │
│ ├─ No ambiguity about sequencing │
│ ├─ Complete error context │
│ └─ Deterministic outcomes │
│ │
│ Result: AI confidently executes complex operations │
└─────────────────────────────────────────────────────────────┘
These schematics illustrate the paradigm shift from human-centric (simple, modular) to AI-centric (complex, comprehensive) tool design that enables more efficient & confident AI operations.
A reader asked for an update given the macro changes & the stock market behavior. Here it is:
Multiple = -12.6 + 34.1 x Forward_Growth_Rate + 4.2 x Sales_Efficiency
Some quick definitions:
We continue to gain momentum with our GenAI book of business growing to over $5 billion inception to date, up by about $2 billion quarter-over-quarter. Approximately 1/5 of this book of business comes from Software and the remaining 4/5 is Consulting.
We had another milestone quarter in GenAI, with $1.2 billion in new bookings and approximately $500 million in revenue.
And our AI business has now surpassed an annual revenue run rate of $13 billion, up 175% year-over-year.
Google commoditized its complements : free maps, free email, free browsers, a free mobile OS. They removed every toll booth between the user & search.
| Category | The Castle | The Complement | The Play |
|---|---|---|---|
| Search | Ad Revenue | Original Search Engine | The technical leap that started the feedback loop |
| User Data | Gmail (2004) | Turned paid storage into a free utility; killed Hotmail | |
| Maps | Local Ad Intent | Google Maps (2005) | Made GPS hardware & licensing free to own local search data |
| Mobile OS | Search Access | Android (2007) | Gave away an OS to prevent Apple/Microsoft from blocking search |
| Browsers | Search Speed | Chrome (2008) | Built a free, fast browser to increase total web usage |
Anthropic’s strategy parallels Google’s, a natural extension of the strength of the core product, the model.
“BI became dashboards. And now it is re-expanding to business intelligence.”
— Colin Zima, CEO & co-founder, Omni
Colin describes how AI fuses structured & unstructured data, and why the future of business intelligence isn’t a better dashboard.
A support leader at one of Omni’s customers went through 75 pages of conversation with an AI to identify 10 categories of rep mistakes. The system read support logs, cited specific examples per rep, & suggested concrete changes. Not just a dashboard.
SpaceX announced a partnership with Cursor today : a $10 billion collaboration with a $60 billion acquisition option later this year.1
The most important market in AI isn’t chatbots, search, or image generation. It’s coding. Cursor is the fastest-growing developer tool in history, at $2 billion in annualized revenue.2
To understand the deal, understand the stack. Winning in agentic coding requires three layers. Anthropic, OpenAI, & Google each own & operate compute, models, & distribution.
At the heart of every security team, there’s a database. That database records each time a user logs in, every packet of inbound traffic, & each attempted attack. Architected before AI, these SIEM systems are wooden shields in an era of autonomous attackers.
The consequences are mounting. Deepfake scams have stolen tens of millions. AI-generated phishing bypasses legacy filters. As Mythos has shown, the sophistication of attacks will only increase.
Shachar Hirshberg & Dan Shiebler saw this opportunity. Shachar led the Amazon GuardDuty product, scaling the business to over 80,000 customers. Dan built & led the 60-person AI/ML team at Abnormal Security. Together, they started Artemis to build a database to power defenses for modern security teams. Within a few months, they have more than a dozen production enterprise deployments & are processing over a billion events per hour. We are excited to partner with them at the Series A, along with our friends at Felicis, Brightmind, & First Round.
For the first time since the 2000s, technology companies are confronting the limits of their supply chain.
GPU rental prices for Nvidia’s Blackwell chips hit $4.08 per hour this week, up 48% from $2.75 just two months ago.1 CoreWeave raised prices 20% & extended minimum contracts from one year to three.1
“We’re making some very tough trades at the moment on things we’re not pursuing because we don’t have enough compute.” - Sarah Friar, OpenAI CFO1
No one comes into a sales conversation without first asking an AI. The buyer journey has changed. Lena Waters, marketing leader behind DocuSign’s IPO, Grammarly & Notion, joined me on Office Hours to discuss what this means for your go-to-market.
The first phase of AI transformation is debt repayment. Most companies are agentically connecting go-to-market processes that should have been fixed years ago.
“Removing human coordination overhead and calling it transformation? That’s debt repayment. It’s real value, but it’s not a new paradigm.”