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In defense of not understanding your codebase
Fable extended until 19 July
Migrating a production AI agent to GPT-5.6: 2.2x faster, 27% cheaper
How Ukraine Built a War Fighting State
Apple's failed self-driving car program left a legacy of powerful AI chips
The Trade in Looted Antiquities Endures for One Reason: Demand
Show HN: Shirei, cross-platform GUI framework in native Go
Automation Without Understanding
Noto: A Typeface for the World
'This was a righteous case. A holy war': the lawyer who took on Meta and Google
Integrating .NET GC in your C++ application
.NET appears as large monolith where everything is working like a magic. But it is not, and even GC can be used outside of .NET runtime (obviously with caveat). When I was a kid, I always love disassemble things, to see how they works. Not always toys survive that exercise. But thanks to source control, .NET GC is safe from my hands. Hopefully lot of people like me, and will enjoy tearing down large system into pieces. submitted by /u/kant2002 [link] [留言]
Show HN: VectorSim Tool for Visualizing DSP
Dan Boschen developed this tool for visualizing frequency-domain content of filters using a sum-of-phasors approach.
TechCrunch Mobility: A robotaxi ultimatum
Welcome back to TechCrunch Mobility, your hub for the future of transportation and now, more than ever, how AI is playing a part.
Theo de Raadt: "You've been smoking something mind altering" (2007)
An explanation of our search results
Samsung is pushing users to train AI with their personal health data or lose it
TK, or the secret to effortless writing (2024)
Passion Edition
Submission: Edu-Insight Assistant What I build I built the Edu-Insight Assistant, a tool designed for educators to bridge the gap between complex school management data and actionable insights. It allows teachers to query students performance data using natural language, turning educational evaluation into a conversation rather than a manual data-processing task. Demo 🔗 Link: Passion-challenge How I Built It I utilized Next.js for a responsive, performant frontend and hooked it up to Google Gemini 3.5 API. The core logic involves a server-side API route that takes a teacher's natural language questions, prompt Gemini to generate the necessary SQL, and execute that query against a database. This architecture makes data exploration accessible to non-technical educators. Prize Categories: - Best Use of Google AI : Leveraged Gemini 3.5 Flash for natural language-to-SQL translation and result interpretation. - Best Use of Snowflake: Designed with an extensible data layer ready for production-scale analytical workloads in Snowflake.