Raffi Krikorian ✓

@raffi · Bay Area · joined 19 Aug 2007

CTO @mozilla. board: @tumocenter & @medic. fmr CTO @EmCollective & director @uber ATC (🤖 🚗)

22 191Followers

1 373Following

10 365Posts total

7.7KViews on collected posts

Postingan terbaru

Raffi Krikorian ✓@raffi18 Sep

join us as we dig into personal data protections in the age of AI. tuesday, september 22nd, 11am ET. save the date. https://t.co/kdcgkDhVes 207 views · 2 likes · 0 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi17 Sep

79% of developers reach for open models. only 53% of teams ever get one into production. today @Mila_Quebec & @mozilla announced an open source AI foundation layer at ALL IN to help close that gap. this is local ownership, local control, no landlord. a layer that belongs to the 527 views · 3 likes · 2 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi17 Sep

Do you actually own your data when AI is the one reading it? Join Mozilla’s CTO @raffi and @Jad_AE, co-founder and CEO of Koodos (the company behind Shelf) for episode 4 of the Owners not Renters livestream and a conversation about the intersection of personal data protections h

2.7K views · 10 likes · 5 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi15 Sep

"a closed model earns its premium in a few places: expert professional work, high-intensity retrieval, and long context. we see the decision to pay for closed models as workload-specific rather than organization-specific." Ars Technica got an early look at v1.1 of Mozilla's 634 views · 5 likes · 2 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi9 Sep

going to be on @AI_in_the_AM this morning at 9:30 AM PT. see you there! https://t.co/jCEuwlPYE4 466 views · 1 likes · 0 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi3 Sep

@raffi @Marcus_Rein_ Can't wait for this one! What a blast to get to put faces and voices to the usernames I see on GitHub 31 views · 2 likes · 0 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi3 Sep

subscribe to ONR: https://t.co/SSXnCHT5ZH 127 views · 0 likes · 0 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi3 Sep

episode three, september 9 at 11am ET. @Marcus_Rein_ hosts Jeremy Schoemaker and Luca Pinchetti. you can’t build in open source alone. you build it with the people who show up, ask questions, and share their experiences. so, join us. subscribe today — live link goes out htt

688 views · 3 likes · 0 reposts · 2 replies Open on X →

Raffi Krikorian ✓@raffi2 Sep

should you trust an AI to keep your secrets? depends on the type of model you're using and how much you’re paying for access. https://t.co/KRwovWRWuV 414 views · 2 likes · 1 reposts · 1 replies Open on X →

Raffi Krikorian ✓@raffi28 Aug

round two, in the books. big thanks to @natebrake, Richard Tweed and our host @Marcus_Rein_ for leading a great conversation about architecture and the future of open. clip below: balancing user autonomy and safety to build a better interaction model. full video on mozilla's h

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491 views · 2 likes · 0 reposts · 1 replies Open on X →

Raffi Krikorian ✓@raffi26 Aug

model providers change, token prices are in flux, and privacy terms can just disappear. what’s your plan for products you build when your AI vendor changes the terms? join me on sept. 2 for an interview with Matheus Pagani, founder of Vibe Space. we’ll be discussing open AI 360 views · 2 likes · 1 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi25 Aug

Ramp says it’ll pick “the lowest-cost model that makes the required performance level.” time to ask who gets to make that decision. once a broker decides how traffic flows, price stops being the only deciding factor. with no rule forcing anyone to show their work, we need 82 views · 0 likes · 0 reposts · 0 replies Open on X →

Raffi Krikorian ✓@raffi25 Aug

a router sits between a user and model and decides which provider serves your tokens, how fast, and what you’ll pay. it was built to serve as insurance against a constantly changing model. the companies that move the world's money just bought the insurance provider. 140 views · 1 likes · 0 reposts · 1 replies Open on X →

Raffi Krikorian ✓@raffi25 Aug

this summer i ran an experiment testing the same coding stack, harness, and model across different servers. there was an 18-point gap between the best and worst serving of the same model. “neutral” routing is a nice promise, but it’s not a guarantee if ownership changes. 155 views · 2 likes · 0 reposts · 1 replies Open on X →

Raffi Krikorian ✓@raffi25 Aug

two of the best-known payment companies are pointing their skills at AI. last week, Stripe purchased OpenRouter for close to $8B and Ramp bought https://t.co/77GvbOcNzC the router is no longer something engineers argue about. it’s becoming the most valuable part of the AI 742 views · 3 likes · 0 reposts · 2 replies Open on X →

Dibandingkan akun berukuran sama

15 postingan dari 90 hari terakhir, dibandingkan dengan rentang 10K–100K pengikut. di bawah akun sekelasnya baik pada jangkauan maupun interaksi.

Median tayangan414akun ini924median untuk 10K–100K

Jangkauan, %1.87%akun ini3.62%median untuk 10K–100K

Interaksi, %0.87%akun ini1.52%median untuk 10K–100K

Metrik	Akun ini	Median untuk 10K–100K	Rasio
Median tayangan per postingan	414	924	0.45×
Jangkauan (tayangan ÷ pengikut)	1.87%	3.62%	0.52×
Tingkat interaksi	0.87%	1.52%	0.57×

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

15525 Aug

140

36026 Aug

49128 Aug

4142 Sep

6883 Sep

127

4669 Sep

63415 Sep

2.7K17 Sep

527

20718 Sep

Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.94%25 Aug

1.43%

0.00%

0.83%26 Aug

0.61%28 Aug

0.97%2 Sep

0.87%3 Sep

0.00%

6.45%

0.21%9 Sep

1.10%15 Sep

0.64%17 Sep

0.95%

0.97%18 Sep

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

What the audience does

Likes61.3%38 in total

Reposts17.7%11 in total

Replies12.9%8 in total

Quotes4.8%3 in total

Bookmarks3.2%2 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.

Postingan terbaru

Dibandingkan akun berukuran sama

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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