John Coghlan

Family, surfing, community at @gitlab. Order varies depending on the waves | he/him

[John Coghlan @john_cogs]

For community, DevRel, and tech content follow me on LinkedIn: https://t.co/cRBT9YRjqd

[Bill Staples @bstaples]

Anthropic models have been the Duo default since inception and we’re happy to share Opus 4.8 is now available, same day release. https://t.co/NG7D1L5fko

[🦊 GitLab @gitlab]

AI coding tools are great at writing code, but shipping it securely is a different problem.

This tutorial shows how Claude Code + GitLab Duo Agent Platform closes the gap, from bug fixes to production, with CI/CD, security scanning, and code review built in.

1️⃣ Fix a bug with Claude Code and let GitLab CI/CD, security scanning, and GitLab Duo Code Review do the rest.

2️⃣ Add GitLab MCP context so Claude works from the context saved within the GitLab issue, and not just local files.

3️⃣ Use a Claude-powered external agent in GitLab Duo Agent Platform to address review feedback directly in the MR.

See how they work together in our blog: https://t.co/z032VuyWPp

[John Coghlan @john_cogs]

New from @dnsmichi: learn how to leverage Claude Code and GitLab to ship things faster. At the end of the day, it's about delivering value to customers and this tutorial shows you a few different ways to do it. Enjoy. https://t.co/izojqaYyZx

[John Coghlan @john_cogs]

We’ve heard from teams who want to understand the path for moving from GitHub to GitLab, so my team put together a simple migration guide.

It’s an early version, and we’ll continue polishing it, but hopefully it gives folks more clarity on the process and what to expect.

Feedback welcome:
https://t.co/4d07HeDrli

[John Coghlan @john_cogs]

@mitchellh Would love to discuss how GitLab can be part of Ghostty’s future.

[John Coghlan @john_cogs]

@RyanRodemoyer2 @bstaples Got it.

If your instance is self hosted, you'll need to be on version 18.1 or later and enable the feature flag. Details on how to turn on the flag are on the docs page I linked to in my last message.

[John Coghlan @john_cogs]

@rawkode @bstaples OSI-licensed projects can get Ultimate via the GitLab for Open Source program: https://t.co/6WXuvYKsVw

[Bill Staples @bstaples]

Devs teams: I noticed other providers are hitting walls, @gitlab is happy to serve you. Start free, receive $24/month in free promo AI credits with every Ultimate user, enjoy CLI/IDE/UX access to built in full SDLC agents, Claude and Codex, and your own custom agents, and use your choice of models and model providers so you never get stuck without service.

[John Coghlan @john_cogs]

The truth about enterprise AI:

The best AI experiences require context.

And the richest context lives inside the systems where teams plan, write, build, ship, and support software.

If your vendors are using your data to train shared AI systems, your data could be making the tools your competitors use smarter too.

AI governance is no longer just a security concern.

It’s a competitive strategy.

[kepano @kepano]

New policy from @Atlassian:

Unless you opt out by August 17th 2026, data from Jira and Confluence will automatically be used for AI training. Some data cannot be opted out at all on some plans.

https://t.co/cJfra1rtj3

[John Coghlan @john_cogs]

Big day on the announcements front. For those following at home, here's what GitLab shipped today.

GitLab 18.11 dropped today. This marks 174 consecutive months with a new release. The highlights are:

• Agentic SAST Vulnerability Resolution is now GA
• Budget guardrails for GitLab Credits are now available
• Two new foundational agents in DAP: CI Expert and Data Analyst

We continue to build out AI capabilities for the entire SDLC with the governance our customers need and expect.

Agentic SAST Vulnerability Resolution reaching GA is yuge.

Because if AI is helping teams create more code, then the pressure on security and remediation only goes up. Enabling teams to move faster from finding to remediation is where things start to get operationally useful.

I also think the budget guardrails matter more than they may seem at first glance.

They’re not flashy but EVERYONE wants this. For AI adoption to expand inside engineering organizations, you need predictability and control. And now you have it with DAP.

In addition to the release, we also added Claude Opus 4.7 to DAP. Part of the growing list of models we support.

And of course, you can bring your own if you prefer.

Oh, and one final note for the GitLab heads: release posts can now be found in our docs.

[John Coghlan @john_cogs]

Yes, when subsidized tools push toward profitability, costs will rise. That's why context is more critical than ever.

Agents with better context (pipeline logs, repo histories, security scans) waste fewer tokens. They get to the right answer faster with less exploration and fewer retries.

As you build your AI stack, think carefully about where and how you'll use context in your workflow. That's what will keep you delivering results even as the price of inference goes up.

[Gergely Orosz @GergelyOrosz]

There is massive irony in how AI coding tools are starting to become TOO expensive for many enterprises - after eg Anthropic removed subsidizing AI subscriptions.

We might go from "everyone use AI for everything!" to "you have $300/month AI budget; use your brain for the rest."

[John Coghlan @john_cogs]

I feel this but I know I can be guilty of this too. I do sense improvement in my use of AI over time.

When I'm using AI for work will be shared with my team, a few steps I've taken to make things better for everyone:
1. be more critical of the output, the first pass from AI (like a human's first draft) is usually not very good
2. ensure that it represents my thinking absolutely, a close enough approximation is actually detrimental to everyone involved
3. put in the effort to make the output as succinct as possible. this saves time and improves retention.

It's also okay to ignore the AI's suggestions when you're happy with something. You don't have to do everything it says...yet.

[Polymarket @Polymarket]

JUST IN: Use of AI in the office is reportedly creating a flood of “workslop” that takes longer to fix than do from scratch.

[John Coghlan @john_cogs]

Thinking back to the early days of AI-assisted coding. Latency and suggestion acceptance rates were considered key metrics at the time. Amazing how quickly things have progressed in just a few short years.

What metrics are you tracking now to measure the impact of agents inside your team? How long will they last?

[John Coghlan @john_cogs]

And we're all lined up and prepping for the 18.11 launch on Thursday.

Big ups to the entire Dev Advocacy team for making my vacation a very productive week. 🤙

[John Coghlan @john_cogs]

Always rad to come back from PTO and see your team kept cooking the whole time you were gone. Sharing this thread so next time I go on PTO, I don't worry so much about work. 🧵

[John Coghlan @john_cogs]

We also shipped a new microsite for devs who want to switch to GitLab, including helpful guidance on how to make the case to your manager. this one is awesome. https://t.co/5j64WscQTl

[Bill Staples @bstaples]

The bar for platform reliability has never been higher, and recent headlines have reminded us why. One of the unique aspects of @gitlab is the cloud neutral, deploy anywhere approach we offer, including our fast growing GitLab Dedicated option, which provides high scale, isolated infrastructure for customers who don't want to manage their own infrastructure but need their software factory to run at cloud scale. I recently sat down with @EricHulser from @rvtechnologies (the software team behind Rivian and Volkswagen Technologies) who is one of our top dedicated customers. Eric shares how his team thinks about the partnership and the critical nature of their software pipelines. Their dedicated instance is scaled up and out and represents one of the single largest deployments of Gitaly in the world. Thanks, Eric, for the partnership and for sharing what your team is building!