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Brett Harrison ✓

@BrettHarrison · joined 12 May 2021

Founder & CEO @Architect_Fi | Derivatives exchange group for AI commodities and perpetual futures. Offering the American Innovation Exchange and AX.

70 505Followers
3 337Following
5 290Posts total
150.8KViews on collected posts

Posts recentes

Comparing AI-based Trading Latencies LLMs aren’t fast enough for online inference in algorithmic trading except for longer-horizon stat arb trades. For the lowest latency trades, many non-LLM machine learning methods are viable. A latency comparison of high- and mid-frequency 10.1K views · 142 likes · 15 reposts · 5 replies Open on X →
@BrettHarrison Why LLMs are so bad at trading ideas? It’s the lack of creativity and abstraction? 143 views · 3 likes · 0 reposts · 1 replies Open on X →
@BrettHarrison When you probe an LLM’s knowledge of trading, it’s actually not that bad, so agent ensembling looks promising for alpha research But sample efficiency is not there yet: an agent gets lost quickly once it starts working with the data. When you put a single agent to 71 views · 2 likes · 0 reposts · 0 replies Open on X →
@BrettHarrison Has there been any expert analysis describing the proof as 'creative'? Or is it just that a bigger agent set is more resources thrown at the search? 317 views · 3 likes · 0 reposts · 1 replies Open on X →
Navier-Stokes and other frontier math discoveries have shown that multi-agent ensembles are required to escape the typical creativity constraints of LLMs. Is this also applicable to algorithmic trading research, which similarly lacks direct answers in LLM training data? The 16.8K views · 179 likes · 15 reposts · 26 replies Open on X →
At the current rate of compute financialization, CDOs on GPU-backed leases are likely coming to market. Non-investment-grade neocloud operators with 8-9 figure budgets are struggling to secure financing for under double-digit interest rates, and bundling is a short-term solution 9.7K views · 127 likes · 14 reposts · 16 replies Open on X →
I’m looking forward to discussing compute markets with this excellent panel at Bloomberg Derivatives Market Structure 2026. NYC evening of 9/30, also focusing on prediction markets and US perps, not to be missed. https://t.co/cL9o8Abn8o
7.8K views · 122 likes · 15 reposts · 8 replies Open on X →
@BrettHarrison Congrats Brett! You love to see it 1.7K views · 9 likes · 0 reposts · 1 replies Open on X →
Compute has emerged as the most important commodity in the 21-century global economy. The American Innovation Exchange will ensure that its financialization begins here in the U.S. and develops with the agility and speed the artificial intelligence industry requires. 2K views · 25 likes · 2 reposts · 1 replies Open on X →
Introducing the American Innovation Exchange, the first U.S. derivatives exchange designed for trading the AI economy. Trade futures and options on compute, metals, energy, and other critical instruments in the AI supply chain. Coming soon from Architect. https://t.co/5uIAnTvEQR
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102.2K views · 426 likes · 53 reposts · 38 replies Open on X →

Em comparação com contas do mesmo porte

7 posts dos últimos 90 dias, ao lado da faixa de 10K–100K seguidores. aparece para mais gente do que contas do mesmo porte.

Mediana de visualizações7 785esta conta924mediana para 10K–100K
Alcance, %11.04%esta conta3.62%mediana para 10K–100K
Engajamento, %1.63%esta conta1.52%mediana para 10K–100K
MétricaEsta contaMediana para 10K–100KProporção
Mediana de visualizações por post7 7859248.43×
Alcance (visualizações ÷ seguidores)11.04%3.62%3.05×
Taxa de engajamento1.63%1.52%1.07×

Outras contas desta faixa →   Comparar com outra conta →   Como estas referências são construídas →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

102.2K28 May
2K
1.7K
7.8K4 Sep
9.7K8 Sep
16.8K10 Sep
317
71
143
10.1K14 Sep

Last 10 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.51%28 May
1.40%
0.57%
1.86%4 Sep
1.63%8 Sep
1.31%10 Sep
1.26%
2.82%
2.80%
1.61%14 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes59.1%1 038 in total
Reposts6.5%114 in total
Replies5.5%97 in total
Bookmarks28.9%507 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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