Vibe coding and the junior developer dilemma
AI tools are transforming how we code, but they're not replacing the experience needed to build real software. Let’s talk about what vibe coding gets right—and what it gets very wrong.
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So you messed up
Everyone breaks production eventually. This guide walks through how to take responsibility, communicate with your team, and make real improvements after something goes wrong. A must-watch for engineering managers and developers.
When don't you need a fractional CTO
Does every startup need an interim CTO? Fractional CTOs can accelerate growth and solve complex challenges—when brought in at the right time. Learn when it’s too early, too risky, or simply not the right fit for your business.
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AI overdose: When developers stop thinking and start prompting
AI tools are reshaping how junior engineers approach problems, often replacing simple solutions with overly complex ones. Here’s why foundational thinking still matters. A real-life case of AI over-engineering gone wrong highlights why understanding problem domains still beats prompting.
Eliminating SPOFs: the importance of documentation
Single points of failure (SPOF) in startups lead to lost revenue, delays, and investor concerns. Building a documentation culture early reduces risk and ensures scalability.
These small dopamine hits
Some tasks are a slow grind, like simmering a big meal that takes hours to come together. Others are quick and satisfying—tiny fixes that deliver an instant hit of progress, like a little dopamine boost to keep you going.
Why engineers need a voice in the roadmap
A great product roadmap balances business goals with technical sustainability. Ignoring engineering input leads to technical debt and bottlenecks that slow growth. In this video, we discuss how SaaS teams can integrate engineering priorities into the roadmap for long-term success.
Why you shouldn't let customers pay for features
Selling bespoke features to customers might seem profitable, but it changes your SaaS business model. Instead of a scalable product, you become a service provider, stuck maintaining one-off features. Learn why this approach is risky and how to build for long-term success.
Tech stack decisions for AI startups: what you need to know
Selecting the right tech stack is critical for AI startups. Python is essential for data science, but the backend, frontend, and infrastructure choices determine scalability and efficiency. Explore the best tech stack combinations, hosting tools, and ETL solutions to future-proof your AI startup.
