๐บ๐ธ ๋ฏธ๊ตญ ยท IT/๊ธฐ์ ยท "CODING" ยท ์ด 41๊ฑด
ํํฐ ๋ณด๊ธฐํ์ฌ ์ง์
50.0
0 = ๋ถ์ ์ฐ์ธ
50 = ์ค๋ฆฝ
100 = ๊ธ์ ์ฐ์ธ
์ต๊ทผ 7์ผ ๊ธฐ์ค 12,058๊ฑด์ ๋ถ์ํ ๊ฒฐ๊ณผ, ๋ด์ค ์ฌ๋ฆฌ์ง์๋ 50.0(๊ท ํ)์ ๋๋ค. ๊ธ์ 1๊ฑด(0.0%)ยท์ค๋ฆฝ 12,056๊ฑด(100.0%)ยท๋ถ์ 1๊ฑด(0.0%)์ด๋ฉฐ, ์ค๋ฆฝ ๋น์ค์ด ๋๋ ทํ๊ฒ ๋์ต๋๋ค. ์ฑํฅ ์ง์๋ ์ข ํฉ 19.0(์ค๋ ๊ท ํ)์ ๋๋ค.
Supabase, an example of an open source project becoming a fast-growing company, has greatly benefited from AI tools like Claude, Codex, and other vibe-coding platforms.
Samuel Colvin, CEO of Pydantic, sees the top AI frontier labs creating databases of coding intent.
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Database startup Supabase announced a $500 million funding round that values the company at $10.5 billion, including the fresh capital.
Walmart placed a token limit on its internal vibe coding tool, Code Puppy, reflecting the retailer's cost-conscious approach to AI.
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Gemma 4 12B uses a new encoding scheme and token prediction to punch above its weight.
New graduatesโ careers are unfolding in an era when AI is not optional. The most successful engineers treat artificial intelligence as leverage, not competition. Here are seven tips to help keep young professionals in demand no matter how quickly the fieldโs tools evolve. 1. Master the fundamentals first. AI tools can help you code, but you still need strong fundamentals in: Data structures and algorithms for problem-solving. Operating systems, databases, and networking for system-level understanding. Core programming languages such as C++, Java, and Python. AI can autocomplete syntax, but if you donโt understand how things work under the hood, youโre likely to struggle to debug or optimize. 2. Learn how to work with AI, not against it. The best engineers will not try to out-code AI. Instead, they will learn to: Write clear prompts to generate better code snippets. Review and debug AI-generated code for accuracy, performance, and security. Use AI for productivity boosts while still exercising judgment. Think of AI as a teammate. The real skill is knowing when to trust it and when not to. 3. Build projects that showcase end-to-end thinking. Employers increasingly look for engineers who can design and build systems, not just solve problems. Create projects that show you can: Define requirements clearly. Use AI tools responsibly within the workflow. Deliver a product that scales and is maintainable. 4. Sharpen your system design skills early. Even junior engineers are now asked questions about basic system design with AI. Expect to explain to prospective employers: How you would responsibly integrate AI into a system. How to design fallbacks when AI fails. How to ensure scalability and reliability. 5. Develop strong communication skills. Todayโs engineers donโt just code in isolation. You will be expected to: Explain design choices to teammates and stakeholders. Document decisions clearly. Collaborate effectively in cross-functional teams. This is one area where AI cannot replace you. Clear communication is a career accelerant. 6. Stay curious and keep learning. The tech industry moves fast, and AI is accelerating that pace. Cultivate habits such as: Following industry news, blogs, and open-source projects. Experimenting with new AI tools, frameworks, and libraries. Engaging in communities such as GitHub, IEEE Collabratec, LinkedIn, and Medium. Employers value engineers who keep themselves sharp and relevant. 7. Think beyond coding. AI will increasingly handle routine coding tasks. The differentiators for you will be: Problem-framing: Can you take a vague idea and turn it into a solution? Architectural judgment: Can you design systems that scale and last? Ethical awareness: Can you spot risks in AI use and address them responsibly? For more career advice, subscribe to the IEEE Spectrum Career Alert Newsletter. The biweekly newsletter features the latest information on jobs, education, management, and the engineering workplace.
The MAI model family spans reasoning, coding, image, voice, and transcription โ and lets Microsoft avoid paying third parties like OpenAI
In the space of a few weeks, OpenAI, Anthropic, and Google released new AI models. Now, coders are rethinking their jobs โ and what comes next.
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Six job-specific plugins for data analytics, creative production, sales, product design, and finance expand Codex beyond its coding roots
Coding tools are becoming an increasingly big target for Google and Microsoft as they try to catch up to Anthropic and OpenAI.
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Zig, an open-source programming language bans contributors from using AI. Its president said that the these submissions have "no value whatsoever."
The project is being spearheaded by new Copilot chief Jacob Andreou, as Microsoft seeks to streamline its lineup of AI tools amid competition from Google, OpenAI, and Anthropic.
Cognition makes Devin, the first and arguably most successful AI coding agent. But famed coder Wu says it isn't designed to supplant human programmers.
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