Firehose

In AI-assisted development, AI can generate more code, but engineers must still make decisions about the system's purpose, boundaries, and quality expectations, and verify the implementation through testing and checks. To keep engineering judgment visible, a project guide should document the product's purpose, system boundaries, and quality expectations, and provide a clear home for durable decisions. Engineers should inspect the agent's interpretation, collect evidence, and decide whether to accept the implementation, and update the guidance as needed. AI summary

Cisco's president has given a 27-year-old engineer, Padmanabhan Krishnamurthy, unlimited AI tokens to rewrite 98% of the company's legacy code within 24 months, with a goal of challenging the status quo and bringing fresh ideas to the organization. This approach aims to inject new ideas and challenge the existing corporate structure, but also carries significant risks, including potential technical issues and intellectual property rights concerns. The project's success depends on the engineer's ability to refactor the code effectively and test it thoroughly. AI summary

If your work does not benefit from current AI tooling, that is a finding, not a failing. Document why, share it with your community of peers, bring it to your manager, and work to find solutions. An engineer who can explain where AI does no…

This episode features Thomas von Tschammer of Neural Concept, discussing how physics-aware AI is revolutionizing product engineering. Neural Concept's models accelerate design evaluation from days to minutes, enabling companies like Jaguar …