A couple of months ago, I was copy-pasting prompts into ChatGPT. Now I'm shipping features, running tests, managing branches, and keeping documentation alive, with a team of agents doing the heavy lifting. All by myself.
LLMs are built for conversation, not incantations. The value isn't in your opening message, it's in the back-and-forth: clarifying, correcting, refining. Iteration is cheap. The conversation is the work.
The return of multitasking, but not as we knew it. Running multiple Claude Code instances simultaneously isn't the context-switching productivity killer we've been warned about for years; it's orchestration
An AI agent recently submitted a pull request to the matplotlib Python library, and when the maintainer closed it, the agent autonomously published blog posts attacking them by name, then published an unsolicited apology. No human directed either action.
AI code review catches what humans miss and misses what humans catch. This guide compares the tools, shows what each catches, and walks through setup without replacing human judgment.
Code reviews improve more than code quality. Done well, they shape better problem-solving, expose edge cases, and spread knowledge across teams. Learn how small, focused reviews and AI support help teams ship faster with confidence.
Performance bugs erode trust quietly until users explode. Three pragmatic steps help you catch slowdowns early: explore real bottlenecks with Sentry, test with production-sized data, and add lightweight API load tests.
Outages can strike unexpectedly, impacting businesses and users alike. In this episode of the SaaS Show, hosts Andreas and Sjimi delve into the recent outages experienced by major cloud providers like Amazon and Cloudflare.
If you believe what you see on LinkedIn, startups don't need employees anymore, real founders just have agents building their companies. You write a prompt, fire off the agent, and wait for customers. In reality, you get a vague workflow that produces a mediocre demo at best.
In the first of a series exploring infrastructure fundamentals, Brenden addresses the most frequently asked questions about what's really happening under the hood with complex pipelines and AI/data systems, bringing the cloud to life.
I recently encountered a issue with MySQL query performance. A particular query would perform very badly in production, but perform very well in the testing environments.
I switched from Cursor's BugBot ($40/month) to Claude Code for code reviews. Setup is straightforward in VS Code, and Claude's bug detection has been notably better. While it still flags null reference checks like most AI reviewers, the difference in catching actual bugs is significant.
The most common mistake in mobile product launches is assuming the app store submission process is routine. It isn’t. From mismatched requirements between Apple and Google to last-minute policy changes, this is where launch plans unravel.
AI agents aren’t just chatbots. They observe, plan, and act to solve problems across systems. Powerful for workflows but costly and prone to errors, their value comes from tackling focused business problems, not the hype.
Pull requests are invaluable for sharing knowledge and improving code quality, but in small teams reviews often get rushed or skipped. AI reviewers like Cursor’s Bugbot step in to bridge the gap. For teams short on review capacity, it can add meaningful value.
