Current agentic tooling lends itself well to those who have embraced a paradigm that has been frowned upon in the Software Engineering space for decades. Short-term gains will allow more rapid adoption of AI-code generation but agentic must learn to scale to meet the demands of larger enterprises.

AI makes "vibe coding" internal tools deceptively easy, but is the "death of SaaS" actually imminent? While simple tools may vanish, the hidden costs of maintenance and the risk of business distraction remain. Discover why building a tool is the easy part, but owning it—and the technical debt that follows—is a long-term commitment most won't make.

For someone who thought Redis was merely a session cache, or a key-value database, here are some highlights for why Redis might actually be the best open source tool you've never explored.

Generative AI accelerates development, but how do we prevent AI slop and make sure good engineering practices are kept at the fore-front? This proposed Engineering-First approach prioritizes architectural context, deep code comprehension, and personal accountability. By treating AI as a high-speed apprentice rather than an oracle, true engineers ensure they can explain and defend every commit. In an automated world, human judgment and ownership remain the ultimate engineering standards.