Article URL: https://paulgraham.com/greatwork.html Comments URL: https://news.ycombinator.com/item?id=49132289 Points: 3 # Comments: 0
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Kontigo, a startup that participated in Y Combinator's Summer 2024 batch, has posted an open position for a Founding Engineer. The job listing was shared on Hacker News, Y Combinator's associated tech community platform. The role is listed directly on Y Combinator's company directory under Kontigo's profile. No further details about the company's focus or compensation were provided in the listing.
Data professionals frequently struggle to consolidate specific sheets from large numbers of Excel files into a single unified table. The task grows more complex when sheet names vary across files and data structures are inconsistent, with mismatched headers, column orders, and data types. Manual copy-paste methods are error-prone and unscalable, while VBA macros offer automation but require coding knowledge. Power Query provides a more accessible middle ground for structured consolidation workflows. Modern AI-assisted tools are also emerging as potential solutions to handle inconsistencies and reduce manual intervention in data merging tasks.
A developer tutorial on DEV Community outlines how freelancers and studios can create maintainable WhatsApp landing page templates for clients. The guide recommends defining the page's purpose and editable elements — such as headline, services, colors, and phone number — before writing any code. It emphasizes centralizing the WhatsApp number and pre-filled message in a single, clearly commented constant to minimize handover errors. Placeholder text like [Business Name] and [Service Area] should be used throughout demos instead of fabricated testimonials or metrics. The author also provides a pre-launch checklist and links to a public CodePen demo, with paid licensing options starting at USD 20 per project.
A developer has released Vaniq-Edge, a lightweight, end-to-end text-to-speech engine with approximately 8.5 million parameters and a file size of just 34.3 MB. The model converts text directly to 24kHz mono audio without relying on external vocoders or secondary models. It achieves a Word Error Rate of 2.94% and a predicted audio quality score of 4.35 out of 5, while running faster than real-time on both GPU and single-core CPU. The model is available as open weights on Hugging Face and can be tested locally using Python. Key limitations include support for English only, a single fixed voice, and occasional high-frequency audio artifacts on certain consonants.
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