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Google Cloud Tech

@GoogleCloudTech · joined 11 Aug 2008

Follow along for how-tos, demos, product news, and more. For company updates, check out @GoogleCloud. Watch #GoogleCloudNext on demand ⬇️

1 313 574Followers
1 597Following
26 401Posts total
189.1KViews on collected posts

Latest posts

@GoogleCloudTech plugins for coding agents now huh 1 views · 0 likes · 0 reposts · 0 replies Open on X →
@GoogleCloudTech Plugins make sense when they remove setup work. The real test is whether the first install feels boring. 56 views · 0 likes · 0 reposts · 0 replies Open on X →
Introducing Google Cloud plugins for AI coding agents. Designed as installable bundles, agent plugins equip the AI agent of your choice with skills and tools to be more effective on Google Cloud. Learn more and start building → https://t.co/xndsKuzsuq https://t.co/YecRL2875k
35.2K views · 276 likes · 39 reposts · 11 replies Open on X →
https://t.co/S75IujZbgi 28.2K views · 201 likes · 33 reposts · 8 replies Open on X →
On this week’s livestream you’ll learn how Gemini Enterprise provides a single front door to company data, securely connecting SaaS apps to deploy grounded AI agents. https://t.co/wOaYKMRcgU 14.2K views · 69 likes · 9 reposts · 3 replies Open on X →
https://t.co/Oe5CiXdzvq 24.1K views · 129 likes · 23 reposts · 19 replies Open on X →
@GoogleCloudTech the missing fifth pattern is idempotency across side effects. once agents react in parallel, every write needs a dedupe key and a durable receipt. otherwise you've built a very fast machine for sending the same email twice. 1.1K views · 6 likes · 0 reposts · 2 replies Open on X →
Find the code path that runs after your fallback fires. If it skips a validation step, you're shipping two different products, while only testing one. 3.6K views · 7 likes · 0 reposts · 0 replies Open on X →
Pattern 4: Tiered routing before the expensive call Look at your own traffic distribution before assuming you need a bigger model. A cheaper first pass usually gets you further. 3.2K views · 15 likes · 0 reposts · 1 replies Open on X →
Read the full article ⬇️ https://t.co/Jr4pWXwmMO 4.5K views · 31 likes · 7 reposts · 3 replies Open on X →
Pattern 2: Let agents react to the same event in parallel Check whether two of your agents will need to react to the same signal. If your architecture makes one wait behind the other to do it, that's a single-threaded system wearing a multi-agent label. 4.2K views · 22 likes · 0 reposts · 1 replies Open on X →
Pattern 3: A fallback model still has to clear your bar Find the code path that runs after your fallback fires. If it skips a validation step, you're shipping two different products, while only testing one. 3.6K views · 14 likes · 0 reposts · 1 replies Open on X →
Pattern 1: The tools you built for yourself can serve other agents too If your agent talks to its own data over MCP internally, check how much extra work it'd take to expose those same tools externally. Do this before you build a second, human-only API that does the same job. 4.4K views · 31 likes · 4 reposts · 1 replies Open on X →
We just wrapped the Google for Startups AI Agents Challenge. Here are 4 production-grade patterns that you should steal for your next build ⬇️ 62.9K views · 540 likes · 47 reposts · 12 replies Open on X →

Against accounts of the same size

14 posts from the last 90 days, next to the 1M–10M follower range. below its peers on both reach and engagement.

Median views4 303this account14 569median for 1M–10M
Reach, %0.33%this account0.68%median for 1M–10M
Engagement, %0.64%this account0.92%median for 1M–10M
MetricThis accountMedian for 1M–10MRatio
Median views per post4 30314 5690.30×
Reach (views ÷ followers)0.33%0.68%0.48×
Engagement rate0.64%0.92%0.70×

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

62.9K9 Sep
4.4K
3.6K
4.2K
4.5K
3.2K
3.6K
1.1K
24.1K
14.2K
28.2K10 Sep
35.2K
56
112 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

0.95%9 Sep
0.82%
0.42%
0.55%
0.92%
0.50%
0.20%
0.74%
0.71%
0.57%
0.86%10 Sep
0.93%
0.00%
0.00%12 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 1M–10M accounts is 0.92%.

What the audience does

Likes46.2%1 341 in total
Reposts5.6%162 in total
Replies2.1%62 in total
Bookmarks46.1%1 337 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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