The all-you-can-eat era of AI is ending. Compute constraints, heavier models, and a fully hooked user base are pushing providers toward pay-as-you-go. That shift will force better choices, smaller models, and fiercer competition between tools.
We smile at the 18th-century crowd for being swept up by a box with a man inside, yet today it's easy to hand ChatGPT a vague idea and treat the PRD it returns as gospel. Generative AI is genuinely powerful. We get the best from it when we bring both enthusiasm and a critical eye.
Managing multiple Claude Code accounts across machines gets messy fast. Jean-Claude keeps the useful parts in sync, separates account-specific config, and makes switching between personal, team, and client setups far less painful.
Software development's feedback loop has compressed from years to minutes, but QA remains the last bottleneck, the one place still dependent on human judgment. AI is rapidly closing that gap, and before the year is out, that final human checkpoint may no longer be necessary.
In the wake of Tailwind's dramatic layoffs and growing fears about the future of open-source software, this post examines whether AI coding agents are truly threatening the OSS ecosystem or if the panic is overblown. And it's a reaction to Andreas' idea that open source will no longer exist.
By 2030, nobody will write code anymore and here is why. The difference between agent-powered engineers and those who handcraft code is huge. Here's our prediction on software engineering.
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.
What will the state of AI be like in a year's time? Here are Mike Veerman's predictions of what major things will happen next in AI
When selecting AI tools, companies must go beyond productivity and consider compliance, community support, and team management. Discover madewithlove’s pragmatic approach to responsible, scalable AI adoption.
When product teams obsess over perfect quality, they risk standing still, but by embracing a 'fit for purpose' mindset and planning for instability, they can move faster and smarter.
Investing without technical due diligence is like buying a used car without opening the bonnet. This article demystifies the audit process, shares what red flags we look for, and explains why investors should care deeply about code, processes and product.
Startups without a technical co-founder can still build great products, but only if they avoid the usual traps of overengineering, needless infrastructure, and late developer involvement.
AI tools are changing how agencies work and how they should bill. Fewer hours, faster results, and ballooning token costs are reshaping agency economics. We dive into what comes next, and why value pricing might be the way forward.
When customer support becomes a blocker for engineering progress, it’s time to build more than just your product—you need to build your support infrastructure. This article explains how to scale support before chaos kills your velocity.
Many SaaS startups over-engineer their architecture with microservices. Here's why that's usually a costly mistake—and what to do instead.
