GPT-6 Astra turned $240 into $2,860. Then it locked most of that money away from its own trading agents.
Four sessions in, I opened the trading wallet. $895. The report said $2,860. I refreshed both screens, sure something had broken.
Then I opened the transfers.
$1,965 had moved into a separate reserve wallet. Every transfer had a receipt. The numbers matched to the cent.
The desk had four jobs. Three agents handled discovery, contract checks, and execution. The fourth was called CASHIER.
CASHIER watched settled results. After each profitable session, it moved 75% of the net gain into reserve. The trading agents could see that balance. Their permissions gave them no way to pull it back.
That detail suddenly became interesting.
I started calculating what the next position could look like with the full $2,860. Opened the settings. Hovered over the allocation.
Then closed them.
The next session was ugly. Two positions closed red. Working capital dropped from $895 to $731.40. I watched the desk shrink its next order and keep scanning.
The reserve still read $1,965.
That was the first time the setup made sense emotionally. A bad session had a smaller pile of money available to damage.
I spent another hour in the logs. The least exciting agent on the desk had done the thing I was most likely to postpone.
It had actually taken the money off the table.
CASHIER never found a single winning token. It was the first agent I decided to keep.
How does GPT‑Live‑1 perform on the benchmarks that matter most for production voice agents?
We focused on task completion, back-and-forth conversation and turn-taking, how quickly the model responds, and tool use.
Here are the results:
Upcoming mint on robinhood chain🟩
✦ 5 FCFS spots up for grabs
How to join:
- follow: @RoyalMechanica and @Trung_Anh_01
- join wl: https://t.co/QQnWe4JtgV
- Like, share this post
- Send EVM wallet below
- End in 6h
always DYOR
The premium-model business is looking more fragile than the leaderboard charts imply.
On Vercel’s AI gateway, open-weight models already processed ~29% of production token volume for less than 4% of the total spend. Anthropic captured ~61% of that spend while handling roughly the same share of tokens. That gap is likely to widen.
Open models continue to get better, cheaper, and small enough that meaningful workloads can run locally. Frontier APIs don’t need to lose outright for the economics to shift. They only need to become the escalation layer and reserved for the shrinking set of tasks where the extra intelligence still justifies the premium.
That’s the dynamic worth watching with Anthropic and OpenAI
Interesting comparison:
Fable 5 and Ox Alpha both used the same ink-brush action brief + Seedance 2.5 pipeline. Fable holds the style and action well.
Ox Alpha pushes it further with stronger compositions, dramatic transitions and shots that feel intentionally directed.
Same stack, different results.
Got 15 Spots Whitelist Giveaway!
@Trung_Anh_01 x @rekthoodnft
THE STICKMEN GOT REKT.
Now they’re coming for the Robinhood Chain
Early access starts here
How to join:
- Follow @rekthoodnft and @Trung_Anh_01
- Like, share this post
- Send EVM wallet below
- End in 24h
Be active and early! Don't fade this
2025 was the year of LLMs.
2026 is becoming the year of AI agents.
DeepSeek's latest release is another reminder that the competition is shifting from models to systems.
🚀 Who's leading the AI agent race right now?
🚀 DeepSeek-V4-Flash Official API is now LIVE in public beta!
🔷 We’ve massively upgraded its Agent capabilities—benchmark scores are now far surpassing the V4-Pro-Preview. Check out the massive performance leap below! 👇
🔷 The official V4-Flash now natively supports the Responses API format and is fully adapted for Codex!
Check out the configuration details in our official API docs: https://t.co/smCwQZMeiq