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Autogen Studio receives praise for its robust AI-driven automation capabilities, which streamline workflows effectively. However, some users express concerns about occasional software glitches and steep learning curves. While there is limited detailed information on pricing, sentiment seems generally neutral, with some users hinting that the cost might be justified by the tool’s advanced features. Overall, Autogen Studio holds a positive reputation among users for enhancing productivity, despite some technical challenges.
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Autogen Studio receives praise for its robust AI-driven automation capabilities, which streamline workflows effectively. However, some users express concerns about occasional software glitches and steep learning curves. While there is limited detailed information on pricing, sentiment seems generally neutral, with some users hinting that the cost might be justified by the tool’s advanced features. Overall, Autogen Studio holds a positive reputation among users for enhancing productivity, despite some technical challenges.
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116,177
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HuggingFace models
Pricing found: $999, $999, $999, $999, $999
I run a team of Claude agents that ships PRs to production — open source
I've been running a multi-agent system in production for a few months — a co-CTO agent + specialist agents (PM, dev, ops) that handle real engineering work end-to-end: design specs, code review, PR implementation, deploys, monitoring. The architecture: Each agent is a Docker container running claude -p (with optional Codex fallback) wrapped in .NET 10. A central orchestrator coordinates them via Temporal workflows + RabbitMQ. Agents talk to me over Telegram (DMs + group chat for the whole team). Memory is Qdrant + Ollama embeddings — agents recall past decisions across sessions. A web dashboard shows live agent status and in-flight workflows. What it does day-to-day: I drop a one-line request in Telegram. PM writes the spec, two reviewers run consensus, dev implements the PR, CI ships to staging, PM verifies, I approve the merge gate, prod deploy. Same pattern handles infra: deploy verifications, health checks, daily digests, incident triage. Agents have access to fleet-memory (semantic memory MCP) — they search before acting, write learnings after. 5-min demo of an actual production PR being shipped: https://youtu.be/DIx7Y3GfmGc Why I built it instead of using crewai/autogen/langgraph: I wanted Temporal-backed durability (workflows survive restarts, retries are deterministic) and ops-grade observability (every workflow visible in the temporal UI, every signal auditable). The agents themselves are just claude -p — the magic is in the orchestration layer. Open source: https://github.com/anurmatov/phleet Side note for those who recognize me — this runs on the Mac Studio I documented in mac-studio-server. The dogfooding is real. Happy to dig into prompts, system architecture, memory strategy, or how the agents handle PR reviews — AMA. submitted by /u/_ggsa [link] [comments]
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Deep analysis of microsoft/autogen — architecture, costs, security, dependencies & more
Pricing found: $999, $999, $999, $999, $999
Key features include: Pendaftaran yang simpel tanpa ribet, langsung siap bermain, Penarikan langsung cair tanpa harus menunggu lama, aman, dan cepat, Tersedia berbagai jenis permainan seperti PG SOFT dan Pragmatic Play, semua dalam satu platform, Data dan transaksi Anda dilindungi dengan sistem enkripsi yang kuat, Tanpa gangguan login atau error, pengalaman bermain jadi lebih nyaman, Customer affirms that s/he is at least legally 18 years of age., "Customer" means the undersigned that is the owner of the Product or has been authorised by the owner of the Product to make decisions on the Product., The Trade-in programme is provided to iStudio customers by Laku6 as a third party company. Apple is not a party in the transaction..
Autogen Studio is commonly used for: Developing AI chatbots, Creating recommendation systems, Building custom AI models, Automating data analysis tasks, Integrating AI into existing applications, Prototyping AI solutions for client projects.
Autogen Studio integrates with: OpenAI API, TensorFlow, PyTorch, Keras, Scikit-learn, Jupyter Notebooks, Slack for team collaboration, GitHub for version control, AWS for cloud deployment, Microsoft Azure services.
Autogen Studio has a public GitHub repository with 56,503 stars.
