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Nzisa Kiilu ✓

@nzisakiilu · San Francisco, CA · joined 04 Dec 2008

Building AI Infrastructure & Hyperscale Orchestration @googlecloud || opinions = mine

11 315Followers
2 251Following
1 438Posts total
6.1MViews on collected posts

Derniers posts

At the intersection of AI and physical infrastructure, loss of optionality may be one of the biggest opportunity costs. By the time something is late, the interesting decisions are usually gone. Understanding lead times, dependencies and constraints early preserves the 352 views · 3 likes · 0 reposts · 0 replies Open on X →
This. The doom and gloom option was not the best strategy. 369 views · 6 likes · 0 reposts · 0 replies Open on X →
if i were openai or anthropic, i’d absolutely flood the world with emotional optimistic ads about what ai can actually do for ordinary ppl. e.g. show the teacher who gets her evenings back. the scientist who finds something sooner. the small business owner who can suddenly do 186.3K views · 4.2K likes · 239 reposts · 259 replies Open on X →
Plan for what is yours to influence. Pray for what isn’t. And build enough resilience that reality doesn’t have to follow the exact plan for life to remain good. 358 views · 4 likes · 0 reposts · 0 replies Open on X →
Are agents lazy or efficient or both? Lol 372 views · 0 likes · 0 reposts · 0 replies Open on X →
I was the main person doing transcript analysis for this investigation of the Hugging Face incident. My main takeaway: We don't have good approaches for understanding/overseeing the activity and aims of AI 'swarms'. I semi-jokingly called our efforts a "slop-vestigation" because 1.9M views · 6.6K likes · 1.1K reposts · 297 replies Open on X →
From launching @ClutchFoundry to having a baby girl, what a whirlwind year! The Nairobi AI and deeptech startup house was a passion project. We did good work and even though we closed after a year, I still deeply believe in the mission. What I learned is building an ecosystem h
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3.2K views · 79 likes · 3 reposts · 6 replies Open on X →
@nzisakiilu The amount of derision from low level coders and engineers on this app is just WOW. Congrats to you and your team on an amazing product! 48.8K views · 374 likes · 7 reposts · 3 replies Open on X →
Last comment, thanks I appreciate the love… and the critics. We take the good and the bad. I and we are both applicable to the work we did to accelerate datacenters. For those thinking about getting into Tech, please do… for those thinking about programming go for it. 127.8K views · 1.2K likes · 56 reposts · 16 replies Open on X →
Well, ummm this wasn’t supposed to blow up… for those asking back in 2019 I joined Google to drive sub-linear scale for our AI and infrastructure org. I led architecture and implementation of the execution engine that orchestrates standard and ML server supply chain, but it took 152.7K views · 2K likes · 116 reposts · 34 replies Open on X →
Humble brag…They won’t believe a little girl from Kenya built the orchestration engine for this, but I did! 3.6M views · 72.8K likes · 10.7K reposts · 1K replies Open on X →

Face aux comptes de taille comparable

7 posts des 90 derniers jours, à côté de la tranche de 10K–100K abonnés. portée ordinaire pour sa taille, réaction plus faible que la moyenne.

Vues médianes372ce compte924médiane pour 10K–100K
Portée, %3.29%ce compte3.62%médiane pour 10K–100K
Engagement, %1.12%ce compte1.52%médiane pour 10K–100K
IndicateurCe compteMédiane pour 10K–100KRapport
Vues médianes par post3729240.40×
Portée (vues ÷ abonnés)3.29%3.62%0.91×
Taux d'engagement1.12%1.52%0.73×

Autres comptes de cette tranche →   Comparer avec un autre compte →   Comment ces repères sont établis →

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

3.6M25 Jul
152.7K
127.8K
48.8K26 Jul
3.2K27 Jul
1.9M26 Aug
37227 Aug
35828 Aug
186.3K2 Sep
3693 Sep
35211 Sep

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

2.35%25 Jul
1.40%
1.02%
0.79%26 Jul
2.71%27 Jul
0.43%26 Aug
0.00%27 Aug
1.12%28 Aug
2.55%2 Sep
1.63%3 Sep
0.85%11 Sep

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

What the audience does

Likes77.0%87 264 in total
Reposts10.7%12 153 in total
Replies1.4%1 642 in total
Quotes0.7%828 in total
Bookmarks10.0%11 371 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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