Ryan Lopopolo ✓

@_lopopolo · joined 24 Jan 2022

Principal Engineer, Agentic GCP @googlecloud • prev @OpenAI • Building the future of work. Harness engineering. As an agent influencer, • opinions mine

10 250Followers

1 221Following

1 312Posts total

231.4KViews on collected posts

Against accounts of the same size

10 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views3 944this account1 756median for 10K–100K

Reach, %38.48%this account5.38%median for 10K–100K

Engagement, %0.85%this account1.75%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	3 944	1 756	2.25×
Reach (views ÷ followers)	38.48%	5.38%	7.15×
Engagement rate	0.85%	1.75%	0.48×

Others in this range → Compare with another account → How these benchmarks are built →

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

63K19 Nov

58.2K21 Apr

11.9K31 Aug

35.1K

230

3.3K

133

42.4K2 Sep

4.6K

2.1K3 Sep

7.4K

Last 12 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.10%19 Nov

0.23%21 Apr

1.01%31 Aug

0.21%

3.04%

2.48%

0.75%

0.16%2 Sep

0.26%

0.94%3 Sep

0.30%

1.05%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.75%.

What the audience does

Likes71.2%560 in total

Reposts2.7%21 in total

Replies9.2%72 in total

Quotes1.7%13 in total

Bookmarks15.3%120 in total

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

Followers by day

4 Sep

Daily snapshots since 04 Sep 2026; the dashed line is the starting count.

Latest posts

Every doc, code change, review comment, and email I've produced at Google has been AI generated. My favorite technique for doing this has been best of N. Every time I need a thing, I roll the same prompt 4 times, each agent produces a doc, I pick the best parts, and battle them. 7.4K views · 58 likes · 2 reposts · 15 replies 03 Sep 2026 I think I am able to run inference in all of these layers and I have no idea what to do with this knowledge but you can be assured I will find a way 3K views · 8 likes · 0 reposts · 1 replies 03 Sep 2026 ok fam mise en place may we begin to cook 2.1K views · 18 likes · 0 reposts · 2 replies 03 Sep 2026 As we all know, there are four networking layers: L2, L3, L4, and L7. I think this is obvious to everybody. 4.6K views · 8 likes · 2 reposts · 1 replies 02 Sep 2026 the Antigravity dev rel folks have found me, expect a pod soon 42.4K views · 58 likes · 0 reposts · 6 replies 02 Sep 2026 @_lopopolo @heatdeathdrone deterministic systems are good actually 133 views · 1 likes · 0 reposts · 0 replies 31 Aug 2026 @_lopopolo They way that you empower agents to be more autonomous is through this thing called skills. Skills can be invoked autonomously and in chain reactions with each other. It let's even cheap agents punch above their weight because they have all the right answers already. 3.3K views · 77 likes · 0 reposts · 5 replies 31 Aug 2026 @_lopopolo @heatdeathdrone how do you empower them to figure it out on their own?my answer to that would be "skills"! 230 views · 7 likes · 0 reposts · 0 replies 31 Aug 2026 @heatdeathdrone I do not aspire to need to invoke things for the agents. If I have to do this, I have failed to empower them to figure it out on their own. 35.1K views · 57 likes · 1 reposts · 14 replies 31 Aug 2026 @_lopopolo Skills are just pre canned prompts you can invoke to save yourself time re explaining the same thing over and over. It's like saying your code only used one function, not really a flex, just strange behavior. 11.9K views · 118 likes · 0 reposts · 2 replies 31 Aug 2026 So why haven’t you all done this yet? 58.2K views · 100 likes · 9 reposts · 22 replies 21 Apr 2026 Every company should have a full stack team of 5 building a product who are banned from directly writing code; they must force the agents to do it. In 2 months they will be your most productive team. 63K views · 50 likes · 7 reposts · 4 replies 19 Nov 2025