One of our big findings in our study at Procter and Gamble was that AI blurred the lines between jobs. Now OpenAI has a similar finding.
Organizational boundaries are becoming porous, the walls thinning. Companies are going to need to think about division of labor in a new way.
Yet another study shows a 24% reduced risk of dementia after the Shingles vaccine. This one in over 500,000 participants with a recent skilled nursing facility stay, adding to 4 huge natural experiments in 4 countries (US, Canada, Wales, and Australia)
https://t.co/TmYqwTB7IT @AnnalsofIM
Each month, we will update it with new data, and periodically, we'll add new metrics and dashboards.
Check out the website: https://t.co/Mw2kg7Gm8p
And let me know what you think!
6/6
On prem open source starts making more sense here.
And really dialed harnesses. Defined workflows, optimized token usage, measurable costs and outcomes.
Demand for frontier models will continue to grow regardless
Our Anthropic bill is about to jump from $400K → $1.4M/yr.
Not because usage exploded, but because we're about to cross 150 seats.
Past 150 seats you're forced into Enterprise tier. Seats stop including any usage, every token bills at standard API rates. At our current run rate that's 3.5x overnight.
Unfiltered thoughts on AI spend:
1. We should spend tokens to grow as aggressively as possible. But most people (me included) aren't conscious of what they're spending.
2. Visibility comes first. People see their personal number and they're shocked. I accidentally spent $4,000 in 3 days in Claude Code.
3. For engineering the spend is clearly worth it. Pay for the best model, it saves more than it costs.
4. For a lot of other roles it's questionable. Apps nobody uses, skills someone already built. No ROI.
5. Spend limits are coming. We already require approval for more tokens on our support team.
The era of token-maxxing is coming to an end.
our OpenAI traffic 3x'd.
the cause: ChatGPT added branded links inside answers instead of burying them in citations.¹
but that's the small story.
Codex went from 600k to 5m weekly users.²
agents are choosing the stack now.
SaaS that can actually increase revenue by selling tokens have potential. The business still has great margins, recurring cash flow, buybacks, and a credible path to paid AI upsell (and enterprise distribution baked in).
at ~11x forward earnings/FCF its pretty low bar for a good company. my bet is we see some positive news in next earnings (like we saw with FIG). New CEO too.
@midmarketPEguy@SMB_Attorney@grok That was my assumption but doesn’t look that way so far. Anecdotally, every lawyer i know is crazy busy while using LLMs more frequently.
This is a big deal. If the billable hour slowly dies but legal revenue continues to grow...AI must be expanding the market. At least for K&E (PE and M&A biz).
https://t.co/UN1cnRLYfP
Legal Services PPI keeps growing as well. More AI use in legal services was supposed to be deflationary.
Also bullish $DELL as they don't f%^k around with data privacy
https://t.co/QfZ0Io3cSU
This is a big deal. If the billable hour slowly dies but legal revenue continues to grow...AI must be expanding the market. At least for K&E (PE and M&A biz).
https://t.co/UN1cnRLYfP