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Robotics investments just hit a new all-time high of $16B.
Here's how I think the average person can get exposure to this emerging sector (nfa - just where I'd start looking):
1. Fund exposure
If you don't want to pick winners, ETFs let you bet on the whole sector at once.
A few worth knowing:
→ $BOTZ (Global X Robotics & AI ETF): industrial robotics + AI heavy
→ $ROBO (Robo Global Robotics & Automation): broadest, most diversified
→ $ARKQ (ARK Autonomous Tech & Robotics): higher risk, higher upside, leans into autonomy and EVs
These spread your risk across dozens of companies instead of betti

Everyone should have an alert on their phone that forces them to revisit this chart every month.
If you've never actually stopped and sat with it, do it now.
Let this be your reminder that time is precious, and you don't have nearly as much left as you think.
Start that business. Travel the world. Take that risk.

This is the most powerful way to use Hermes.
Spinning up multiple subagents to complete work.
Rather than working sequentially, Hermes fans out across multiple agents at once - then cross-verifies and merges the results.
It's like having an entire team from a single prompt:

Anthropic's internal loop engineering playbook just got leaked.
And it's the most valuable AI guide I've read all year.
This guide is packed with info, and there are five things you need to know if you want to maximize your AI productivity with loops (save this):
1. You should structure every loop around these 5 principles:
• Discovery → Let the agent find its own work (CI fails, issues, commits)
• Handoff → Give every task its own isolated git worktree
• Verification → Never let the generator grade its own work
• Persistence → Always write state to disk (markdown or board)
• Scheduling → Run

Pit stop.
Then back to building the world's biggest AI empire.

The robotics trade could be the most asymmetric bet of the next decade.
Robotics company investments just smashed a new all-time high (~$16B and climbing).
These are the top robotics companies/tickers I'm watching for a 10x (nfa):

It's hard to fathom that in ~12 months, we'll likely have access to a model 2x more powerful than Fable 5.
And that might be the conservative estimate, & model costs will likely be way cheaper at that point, too.
Here's why:
The best single measure of AI capability is Epoch's Capabilities Index (ECI)
(a composite score across 40+ benchmarks - math, coding,
science, reasoning).
Think of it like an IQ test for frontier models.
When Fable was released, it hit a new high of 161 on the ECI.
Now here's the part that matters:
The rate of frontier improvement nearly doubled around April 2024, from abo

The future of AI is undoubtedly open-sourced.
For 99% of people, the top open-weight models can already handle all your daily needs.
Imo, the best thing you can do right now is run a "barbell" approach for your AI usage:
Intial 10% and planning phase: Use frontier intelligence (Opus/GPT)
Gruntwork and the middle 80%: Switch to open-weight model (GLM, Kimi)
Final 10% and review: Switch back to froniter intelligence to verify
Best of both worlds - cost efficiency + intelligence.

My best investment of 2026:

You're closer to a completely different life than you'd ever think.
All it takes is 6 months.
By the end of THIS year, you could literally be living the life of your dreams.
Go get your slice.