🦊 GitLab ✓

@gitlab · All Remote 🌏 · joined 13 Oct 2011

Build software faster. The DevSecOps Platform enables your entire organization to collaborate around your code.

172 277Followers

625Following

42 112Posts total

480.3KViews on collected posts

Latest posts

🦊 GitLab ✓@gitlab3 Sep

The GitLab UI has been getting quieter all year. Here's why. https://t.co/qTtdKcJHut Reduced color, neutral controls, updated theming, and a new bloom effect that draws your eye to GitLab Duo when it needs you. 1.4K views · 6 likes · 0 reposts · 0 replies Open on X →

🦊 GitLab ✓@gitlab3 Sep

@gitlab The first guardrail is alignment on the outcome, which is why Molt’s Oracle flow is: post the work → agree on done → start Oracle and pursue it to completion. https://t.co/MEUQDDKQFu 56 views · 0 likes · 0 reposts · 0 replies Open on X →

🦊 GitLab ✓@gitlab3 Sep

After many different trial and errors, build this simplistic goal pursuing oracle. No complicated logic here. Simple, Just works. Suitable for pursuing completion of an implementation after research https://t.co/QiANt2QgeW 699 views · 2 likes · 0 reposts · 3 replies Open on X →

🦊 GitLab ✓@gitlab3 Sep

@gitlab nobody gives a sh*t about this garbage 30 views · 0 likes · 0 reposts · 0 replies Open on X →

🦊 GitLab ✓@gitlab2 Sep

Gemini 3.8 Flash from Google DeepMind is now live on GitLab Duo Agent Platform, across all tiers and deployment models. https://t.co/l8ImyOs23y 4.9K views · 18 likes · 2 reposts · 1 replies Open on X →

🦊 GitLab ✓@gitlab2 Sep

@gitlab Agent speed shifts the bottleneck toward context quality and verification. A shared control plane matters when it can show what the agent saw, changed, tested, and handed off across repositories—not merely that a workflow completed. 28 views · 0 likes · 0 reposts · 0 replies Open on X →

🦊 GitLab ✓@gitlab2 Sep

AI tool access ≠ AI fluency. Our CIO and Chief People Officer share how they partner so GitLab builds AI-fluent engineering teams and internal AI use drives the right business outcomes. https://t.co/PGaNz4Xzw1 5.4K views · 10 likes · 0 reposts · 2 replies Open on X →

🦊 GitLab ✓@gitlab2 Sep

Your AI agent writes code in seconds, then you spend the night fixing a bug you didn't write. It's not the AI's fault, it's the tools: built for one human and one repo, not for how agents actually move. GitLab brings the context, guardrails, and visibility agents need to ship h 453.5K views · 108 likes · 2 reposts · 3 replies Open on X →

🦊 GitLab ✓@gitlab12 Jul

@gitlab GitLab Orbit sounds like a game changer 🔥 A live context graph spanning code, issues, pipelines, deployments & production signals is exactly what AI agents need to move from 'impressive demos' to actually reliable collaborators. This could be huge for reducing hallucinati 24 views · 0 likes · 0 reposts · 0 replies Open on X →

🦊 GitLab ✓@gitlab5 Jul

@gitlab AI OOS https://t.co/ZuntruIlug 24 views · 0 likes · 0 reposts · 0 replies Open on X →

🦊 GitLab ✓@gitlab21 Jun

@gitlab Don't miss the big rise!🔥🔥🔥Gitbank🚀🚀🚀 Gitbank 0xc21dd0ee043930711c2a3e55f39c7d3144d09b07 38 views · 0 likes · 0 reposts · 0 replies Open on X →

🦊 GitLab ✓@gitlab11 Jun

GitLab Orbit, now in public beta, is the context graph for the entire software lifecycle. https://t.co/VKEVuYCFYS It continuously maps code, work items, pipelines, deployments, and production signals into a single live graph, so agents reason from first-party context instead of 14.1K views · 66 likes · 9 reposts · 7 replies Open on X →

Against accounts of the same size

8 posts from the last 90 days, next to the 100K–1M follower range. below its peers on both reach and engagement.

Median views1 042this account5 983median for 100K–1M

Reach, %0.61%this account1.49%median for 100K–1M

Engagement, %0.13%this account0.93%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	1 042	5 983	0.17×
Reach (views ÷ followers)	0.61%	1.49%	0.41×
Engagement rate	0.13%	0.93%	0.14×

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

14.1K11 Jun

3821 Jun

245 Jul

2412 Jul

453.5K2 Sep

5.4K

4.9K

303 Sep

699

1.4K

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

0.62%11 Jun

0.00%21 Jun

0.00%5 Jul

0.00%12 Jul

0.02%2 Sep

0.24%

0.00%

0.42%

0.00%3 Sep

1.00%

0.00%

0.43%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.93%.

What the audience does

Likes70.5%210 in total

Reposts4.4%13 in total

Replies5.4%16 in total

Quotes2.7%8 in total

Bookmarks17.1%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.

Similar accounts

Frequently asked questions about @gitlab

How many followers does @gitlab have?

172 277 followers.

How many posts has @gitlab published?

42 112 posts.

How do posts by @gitlab perform?

Collected posts: 12. Views: 480 257. Likes: 210.