For engineering leaders building resilient, efficient systems

Thomas Ptacek's viral essay explains why dismissing AI coding assistants is becoming professionally dangerous. He shows how LLMs automate the 'schlep work' that consumes 60% of developer time, arguing that teams not adopting these tools will be outpaced by those who do.

Using AI for performance reviews and 1-on-1s might seem efficient, but this analysis shows it stunts managerial growth. Management skills develop through human interaction and judgment calls—outsourcing these to AI creates leaders who can't lead when it matters.

This viral thread exposes the hidden costs of rushed AI adoption: developer frustration, context switching, and productivity loss. Your team's morale and velocity depend on thoughtful tool integration, not following every AI trend.

AI agents are becoming the new API consumers. This provocative take argues that if AI can't navigate your API, you have bigger problems than documentation, your architecture might be fundamentally broken.

The rise of 'vibe coding'—building without understanding—is creating unmaintainable systems. This piece distinguishes between using AI for productivity versus dependency, offering a framework for healthy AI tool adoption on your team.

Great stuff is on its way

Run privacy-first SWE agents entirely inside your VPC—your code, keys, and logs never cross the firewall. Each Ona agent spins up a sandboxed, disposable environment in your cloud, tackling hundreds of tasks in parallel and handing changes back to you in your IDE with a single click. Join the waitlist for early access (Gitpod enterprise users receive access sooner!).

We’re launching a fully-hosted SaaS this summer through our new Core tier, complementing existing deployment options of running locally via Gitpod Desktop or self-hosting in your cloud. Start instantly with pre-configured dev environments on high-spec CPUs/GPUs, without any infrastructure setup. Join the waitlist to get early access.

You asked, we delivered

Gitpod’s Enterprise SWE agent, Ona, now automatically analyzes repositories and generates Dev Container and automations configurations, helping you discover the value of Gitpod much faster.

Gitpod now supports Windsurf as an editor option for your development environments. Another AI-powered editor your developers will demand support for—we got you covered before the tickets pile up.

Development environment starts are now faster for organizations using AWS Runners with the addition of a new Dev Container build cache. Your 5-minute environment starts just became 30-second starts with zero configuration required.

Organization policies give administrators centralized controls to manage security, developer experience, and resource costs. Finally stop that developer spinning up 4XLarge environments for their ‘hello world’ projects.

Gitpod Insights helps enterprise organizations understand and optimize their Gitpod usage and cloud cost. Actual metrics to show leadership when they ask ‘what value does the platform team provide?’

Your developers are no longer just using AI to autocomplete code – they're deploying autonomous agents that clone repos and push entire PRs while you sleep. These agents need compute and network access, but most run on sketchy third-party clouds that ship your source code who-knows-where and bypass your security controls. Platform teams are about to get blindsided by shadow AI infrastructure already running in your org – here's why you need to act before your CISO finds out.

Cursor, Windsurf, GitHub Copilot, they all send your code to remote servers. Your proprietary algorithms hit external APIs with every autocomplete. The fix? Isolated development environments that enforce boundaries. Gitpod provides the execution layer where AI operates within policy controls, not on unmanaged laptops. Check out our guides for Cursor, Windsurf, and GitHub Copilot.

A regulated financial services company saw their security scanners consume nearly a quarter of available computing resources in traditional VDIs. After implementing thin VDI + Gitpod, developer onboarding dropped from a full day to a single click.

When you're working with production code on a local machine, it's easy to let Cline run wild. Agents are able to access and download files, run code on your machine, and even with the typical prompted guardrails can often break things in your codebase or worse.Your developers are running AI agents locally right now, here’s how to contain the blast radius when agents go rogue.

A recent study showed 36% of code suggestions from GitHub Copilot had vulnerabilities ranging from SQL injection to hard-coded secrets. Your developers are merging AI-generated security holes at machine speed. AI has quietly turned development environments into the riskiest, least-governed part of the software supply chain. Here’s how to protect your org while preserving AI productivity.

Happy reading!

Talia