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Mike Taylor

@hammer_mt · Hoboken, NJ · joined 18 Feb 2009

🧪 Head of Evals @Every 📕 O'Reilly author: Prompt Engineering & DSPy 🎓 400k students on AI Udemy course 🤖 AI engineer since 2020 📈 Built a 50 person agency

10 275Followers
3 836Following
35 179Posts total
63.6KViews on collected posts

Postingan terbaru

Every services business is to some degree an insurance company because you get fired by all your clients if you mess up badly enough. 336 views · 3 likes · 1 reposts · 0 replies Open on X →
My thesis statement published on @every for our upcoming conference: Soon the company that hires you will expect your work to amount to nothing. We currently measure a career by the value of the work it produces. But AI is about to make execution almost free. And when execution
1.9K views · 18 likes · 2 reposts · 2 replies Open on X →
One interesting thing about robotics is that it'll turn non-tradeable services into commodity products and so will equilize this effect. Hair dressing, taxi services, restaurants, childcare, cleaning, plumbing, hotels, construction etc will all be globally vs regionally priced. 493 views · 0 likes · 0 reposts · 0 replies Open on X →
So funny that the same FSD software that's capable of driving entirely autonomously in Austin isn't even approved for use with a driver behind the wheel in most of Europe. 1.7K views · 14 likes · 0 reposts · 1 replies Open on X →
@stefanoscalia Wow, groundbreaking. https://t.co/mM7eguOQIn 15.8K views · 216 likes · 1 reposts · 2 replies Open on X →
@hammer_mt @every Congrats 38 views · 3 likes · 0 reposts · 0 replies Open on X →
@hammer_mt @every Congrats! Would love to see some content on creating evals for non-product use cases. (Such as skills that are shared within a company.) 582 views · 3 likes · 0 reposts · 1 replies Open on X →
@hammer_mt @every Let's gooo 🚀 701 views · 6 likes · 0 reposts · 2 replies Open on X →
I guess this is as good a way as any to announce that I'm now the Head of Evals at @every https://t.co/gPWYBoNrBY
42K views · 125 likes · 3 reposts · 12 replies Open on X →

Dibandingkan akun berukuran sama

9 postingan dari 90 hari terakhir, dibandingkan dengan rentang 10K–100K pengikut. tampil luas, tetapi sedikit penonton yang merespons.

Median tayangan701akun ini989median untuk 10K–100K
Jangkauan, %6.82%akun ini3.56%median untuk 10K–100K
Interaksi, %1.14%akun ini1.92%median untuk 10K–100K
MetrikAkun iniMedian untuk 10K–100KRasio
Median tayangan per postingan7019890.71×
Jangkauan (tayangan ÷ pengikut)6.82%3.56%1.92×
Tingkat interaksi1.14%1.92%0.59×

Akun lain pada rentang ini →   Bandingkan dengan akun lain →   Bagaimana tolok ukur ini disusun →

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

42K28 Aug
701
582
3829 Aug
15.8K7 Sep
1.7K
4938 Sep
1.9K
3369 Sep

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.35%28 Aug
1.14%
0.69%
7.89%29 Aug
1.40%7 Sep
0.86%
0.00%8 Sep
1.26%
1.19%9 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.92%.

What the audience does

Likes81.3%388 in total
Reposts1.5%7 in total
Replies4.2%20 in total
Quotes2.3%11 in total
Bookmarks10.7%51 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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