Team.me

Raw Node or NestJS? One dev builds, benchmarks, and stress-tests both to find the best backend setup for a $1K budget and a $6 VPS.

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Unlock DevOps: Basics, benefits, cases, and resources to start your journey. For individuals and organizations, spark innovation and efficiency!

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Learn everything you need to know about Team Management via these 148 free HackerNoon stories.

148 Stories To Learn About Team Management

Articulating the vision of a 3D immersive virtual world often involves breaking down the complex meaning of the metaverse.  

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Temporal's Samar Abbas believes developers shouldn’t have to even think about losing state.

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Want to learn how to localize a website? Look no further. In this post, I share a step-by-step guide to localize your website in under one week. 

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Using data from database collections or from a 3rd-party source can be a powerful tool to enhance your site's functionality. However, sending a lot of data to the browser from the server can be a time-consuming operation and negatively affect your site's loading time. Therefore, you want to minimize the amount of data that is sent from the server to the browser.  This article lists a number of approaches you can use, whether you're using a dataset or the Data API, to improve your site's performance.

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Since leaving the corporate world, and jumping into entrepreneurship I’ve founded three startups. In that time, I’ve seen my fair share of co-founders.

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At <a href="https://plaid.com/">Plaid</a>, we make heavy use of Amazon-hosted ElasticSearch for real time log analysis — everything from finding the root cause of production errors to analyzing the lifecycle of API requests.

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<em>Learn how Ann Phan took her organic food and product marketplace from $0 to $10,000 in revenue in only 3 months.</em>

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Me.mento is a company based in Berlin, Germany. They make vrXcity, a Sims-like virtual world where users can interact in VR with artificially intelligent, photo realistic avatars of their favorite erotic stars with which they can carry out any and all of their fantasies. They are raising money to put the finishing touches to vrXcity, to launch the product and increase the number of adult content stars on their roster to over 7,000 in 2 years.

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<span>I</span>magine this: You’re an engineer at a small startup. You’re in charge of both designing and developing the front-end user interface for your product. <em>And your product relies on being available to everyone on every device as part of its value prop. </em><strong>How are you supposed to build a platform with so many targets?</strong>

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A few weeks ago I was contacted by a follower (Andre) who said he really likes the content I’ve been putting out and that he would love to hear more about how I taught myself to program.

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Work today doesn’t look like it did fifty years ago — or even ten years ago. Aside from the ways in which more powerful technology is affecting our work, more and more people are going freelance or working remote. The number of <a href="http://money.cnn.com/2017/06/21/pf/jobs/working-from-home/index.html" target="_blank">full-time remote workers is up 115%</a> over the last ten years, and <a href="https://www.nytimes.com/2017/02/15/us/remote-workers-work-from-home.html" target="_blank">43% of Americans</a> said they worked from home at least part of the time in 2016. When it comes to freelancers, <a href="https://www.bbbtrusted.org/blog/2017/08/rise-freelance-workers/" target="_blank">recent estimates put them at 35%</a> of the U.S. workforce, with a strong upward trend over the last several years.

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Deadline Driven Predictability

The working week contains 5 working days, with about 8 to 10 hours of work per day, normally. But sometimes it feels like that is not enough, that there is never enough time to get all your tasks and meetings done.

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<p><em>This is a simplified guide to an AI model called <a href="https://www.aimodels.fyi/models/huggingFace/glm-4.7-zai-org?utm_source=hackernoon&utm_medium=referral">GLM-4.7</a> maintained by <a href="https://www.aimodels.fyi/creators/huggingFace/zai-org?utm_source=hackernoon&utm_medium=referral">zai-org</a>. If you like these kinds of analysis, join <a href="https://www.aimodels.fyi/?utm_source=hackernoon&utm_medium=referral">AIModels.fyi</a> or follow us on <a href="https://x.com/aimodelsfyi">Twitter</a>.</em></p>

<h2>Model overview</h2>
<p><code>GLM-4.7</code> is a large language model developed by <a href="https://aimodels.fyi/creators/huggingFace/zai-org?utm_source=hackernoon&utm_medium=referral">zai-org</a> that excels at coding, reasoning, and tool use. The model brings substantial improvements over its predecessor, achieving 73.8% on SWE-bench (up 5.8%), 66.7% on SWE-bench Multilingual (up 12.9%), and 42.8% on the Humanity's Last Exam benchmark with tools (up 12.4%). This model represents a significant step forward in agentic capabilities, particularly for developers and teams building AI-powered coding systems. Compared to <a href="https://aimodels.fyi/models/huggingFace/glm-4.5-zai-org?utm_source=hackernoon&utm_medium=referral">GLM-4.5</a>, <code>GLM-4.7</code> delivers marked gains in multilingual coding, terminal-based tasks, UI generation quality, and complex reasoning tasks.</p>
<h2>Model inputs and outputs</h2>
<p><code>GLM-4.7</code> accepts text prompts and tool calls, processing requests for coding assistance, reasoning tasks, web browsing, and general conversation. The model supports context windows up to 131,072 tokens by default, enabling it to handle extensive code repositories and complex multi-turn interactions. Output quality varies based on task type—coding tasks benefit from extended reasoning with preserved thinking across turns, while simpler requests can leverage lightweight modes for faster responses.</p>
<h3>Inputs</h3>
<ul>
<li><strong>Text prompts</strong> for coding, reasoning, creative writing, and conversation</li>
<li><strong>Tool calls</strong> for web browsing, code execution, and external API integration</li>
<li><strong>Multi-turn conversation context</strong> with automatic thinking preservation for agent tasks</li>
<li><strong>Structured function calling</strong> for integration with external systems</li>
</ul>
<h3>Outputs</h3>
<ul>
<li><strong>Code generation</strong> with support for multiple programming languages and frameworks</li>
<li><strong>Reasoning explanations</strong> with intermediate thinking steps for complex problems</li>
<li><strong>Web browsing results</strong> with improved tool use and context management</li>
<li><strong>UI components</strong> and webpage generation with enhanced visual quality</li>
<li><strong>Mathematical solutions</strong> and step-by-step problem breakdowns</li>
</ul>
<h2>Capabilities</h2>
<p>The model excels at core coding tasks with terminal-based interactions, supporting agentic workflows in frameworks like Claude Code and Cline. It produces cleaner, more modern webpages and better-looking slide decks with accurate layout and sizing. Tool use has improved significantly on benchmarks like ^2-Bench and web browsing performance via BrowseComp. The model introduces interleaved thinking, where it reasons before every response and tool call, plus preserved thinking for coding agents that reuses reasoning across multi-turn conversations rather than re-deriving information. Turn-level thinking allows control over reasoning per request, disabling it for lightweight tasks to reduce latency and cost while enabling it for complex problems.</p>
<h2>What can I use it for?</h2>
<p>Development teams can use <code>GLM-4.7</code> as a coding partner for software engineering tasks, including repository analysis, bug fixes, and feature implementation. The model works well for agentic automation, where it can browse the web, execute code, and manage complex workflows across multiple turns. Content creators can leverage its improved UI generation for building webpages and presentation slides. For research and mathematics, the model handles complex reasoning tasks and proof generation. Businesses can integrate it into customer service systems via web browsing capabilities and deploy it locally using vLLM or SGLang for private inference. The API is available through the <a href="https://docs.z.ai/guides/llm/glm-4.7">Z.ai API Platform</a>.</p>
<h2>Things to try</h2>
<p>Enable preserved thinking mode when working on long-horizon coding tasks to see how the model reuses reasoning across turns rather than starting fresh. Compare responses with thinking enabled versus disabled to understand the latency and quality tradeoffs for your specific use case. Try the model on your own codebase to evaluate its repository understanding and refactoring suggestions. Experiment with turn-level thinking control to optimize cost and speed for different request types. Test its web browsing and tool calling capabilities on structured tasks requiring external data retrieval. Deploy locally using Docker with vLLM or SGLang to evaluate inference performance on your hardware, leveraging FP8 quantization for improved throughput.</p>

<hr/><p><strong>Original post:</strong> <a href="https://www.aimodels.fyi/models/huggingFace/glm-4.7-zai-org?utm_source=hackernoon&utm_medium=referral">Read on AIModels.fyi</a></p>

GLM-4.7 Turns “AI Pair Programmer” Into “AI Dev Teammate”

Code review is an essential step needed for effective software development.

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Is it cool to message your colleagues in ALL CAPS? What is Canada's murder capital of the world? Let's find out.

ALL CAPS, New Teammates, and Canada's Murder Hotspots

In VS Code, open up the team tab by clicking on the GitLive icon on the activity bar. Locate the teammate you are interested in and click the arrow

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Team.me's stories on HackerNoon

Why I Chose 60 Lines of JavaScript Over NestJS for a Budget Project

DevOps for Beginners: Navigating the Transition from Traditional Development

148 Stories To Learn About Team Management

'The Metaverse Is Not a Zero-Sum Game': Hrish Lotlikar, SuperWorld Co-founder & CEO

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How We Localized Our Website in 9 Languages in Under a Week — And So Can You

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Yo Scrum Master, whatchadoin all day? (Survey Results)

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Building Cross-Platform Applications with a Universal Component Library

How I taught myself to program and the top 5 lessons you can learn from my story

How to build a better marketing team

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The “75/25 Rule” for a result orientated work environment.

GLM-4.7 Turns “AI Pair Programmer” Into “AI Dev Teammate”

Do not Troll Your Teammates: 5 Key Rules for Reviewing Code

ALL CAPS, New Teammates, and Canada's Murder Hotspots

How to See Which Branch Your Teammates are on in VS Code

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