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Turn your software into a business. Contribute to polarsource/polar development by creating an account on GitHub.

I have curated 9 cutting-edge developer productivity tools that I've recently explored and found to be valuable for boosting coding efficiency!

Simplify your DevOps with Dokploy. Deploy applications and manage databases efficiently on any VPS.

Stay up to date with the latest Google AI experiments, innovative tools, and technology. Explore the future of AI responsibly with Google Labs.

A live, interactive program that'll help you build production-ready AI & Machine Learning systems from the ground up.

AI.GENERATE_TABLE() in BigQuery lets you convert unstructured data into a structured table based on the provided prompt and table schema.

Live course to learn how to build effective AI agents with n8n.

Modern, native client with intuitive GUI tools to create, access, query & edit multiple relational databases: MySQL, PostgreSQL, SQLite, Microsoft SQL Server, Amazon Redshift, MariaDB, CockroachDB, Vertica, Cassandra, and Redis.

Master data engineering and AI like a big tech engineer

An extended edition with dozens of AI PM resources: definitions, courses, guides, reports, tools, and step-by-step tutorials

8 AI Agent Configurations. 9 Best Practices. 11 Agent Prompting Principles. 3 Agentic RAG Architectures. No Coding.

AI Product Manager in the US: $245,346. Product Manager: $123,654 per year.

The most practical guide you’ll read on AI product strategy. This will teach you how to build an AI moat that compounds and how to lead AI initiatives with confidence and clarity.

Get AI-powered comprehensive answers with direct citations from 250M+ verified research sources in minutes.

The Emergence platform generates intelligent agents on demand to meet enterprise needs—no static workflows, no limits.

Sierra’s AI research team is on a mission to advance the frontier of conversational AI agents. In this research paper, we present a new benchmark for evaluating AI agents' performance and reliability in real-world settings, with dynamic user and tool interaction. Read on for a synopsis of our inaugural publication.

Researchers at Hebrew University, IBM, and Yale summarize the latest in AI agent benchmarking and suggest four ways it could be improved.

Unlock AI agent potential with 8 essential steps. Optimize benchmarking for efficiency, real-world readiness, and enterprise success. Elevate AI impact.

Explore Droip's pricing options and select the ideal plan tailored to your requirements, offering a range of features at competitive rates.

Fellou is the world's first agentic browser that automates complex tasks with Deep Action technology. Enjoy hands-free research, cross-platform workflow automation, and AI-powered report generation - all with military-grade security. Transform how you browse and work with your intelligent digital partner.

️ مسافر بره مصر؟ فسحة ولا شغل؟ أول حاجة هتحتاجها هناك هي الإنترنت! مع Simlss eSIM مش هتدور على شريحة ولا تدفع في التجوال الغالي، شغّل الإنترنت قبل ما توصل، أرخص من أي خط تجوال، شغال في أكتر من 100...

Lists of company wise questions available on leetcode premium. Every csv file in the companies directory corresponds to a list of questions on leetcode for a specific company based on the leetcode ...

11K likes, 86 comments - evolving.ai on June 24, 2025: "Google just released an open source framework for building full stack AI agents with Gemini 2.5. It's fully compatible with Replit. You can run and customize your own agent with: • A built-in conversational interface • A backend optimized for AI tasks and research This makes it easier for developers and indie creators to experiment with advanced AI agents. repo: https://github.com/google-gemini/gemini-fullstack-langgraph-quickstart Special thanks to @itspaulai for the workflow and the videos. What are your thoughts on this? 🤔💬 — ➡️ That's it! If you want to keep up with all the AI news, useful tips, and important developments, join 50k+ subscribers reading our free newsletter.".

Script your automations in the language of your choice

What most posts about AI Agents miss in production - Part 1 The enthusiasm around AI agents and tools like N8N is understandable, but sadly most of the posts focus on the hype and overlook what works in production for companies! 1 - Industry Leaders Favor Workflow-Based Approaches! Leading AI companies, including Anthropic, increasingly recommend "AI-powered workflows" over full autonomy. Simply put: workflows provide predictable outcomes with defined guardrails, while agents introduce variability that can compromise business operations. 2 - Leverage Existing Infrastructure First! Before introducing new platforms, evaluate your current automation capabilities. Does your company have a suite of applications from a company like Microsoft for example? if the answer is "Yes", make sure you explore something like Microsoft Power Automate first before going with something else. 3 - Define Acceptable Error Thresholds! Error tolerance varies dramatically across industries and use cases: - Financial services: Minimal tolerance due to regulatory and compliance requirements. - Marketing operations: Higher tolerance for creative and experimental processes. Establish clear error budgets and failure scenarios before deployment. 4 - Evaluate Code-First Solutions, and yes, they work and get things done more than you expect! Not every automation challenge requires generative AI where you sprinkle some prompts and API calls and that's it - traditional programming solves a myriad of real-world challenges. Share with me your thoughts in the comments below!

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