Alternatives
Products that do what ACGC - Agent Context Garbage Collector does
Runtime context manager for agentic stack
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9
- 10
- 11AF
Hi HN, I’m Vincent from Aden. We spent 4 years building ERP automation for construction (PO/invoice reconciliation). We had real enterprise customers but hit a technical wall: Chatbots aren't for real work. Accountants don't want to chat; they want the ledger reconciled while they sleep. They want services, not tools. Existing agent frameworks (LangChain, AutoGPT) failed in production - brittle, looping, and unable to handle messy data. General Computer Use (GCU) frameworks were even worse. My reflections: 1. The "Toy App" Ceiling & GCU Trap Most frameworks assume synchronous sessions.…
Feb 2026 · github.com
- 12
Open Source Context Infrastructure for AI Agents
May 2026 · ravbyte-ai.github.io
- 13
- 14
- 15
- 16TA
Hi HN, There’s been a lot of discussion lately around context graphs, decision traces, and how AI systems reason. One thing we kept running into: when AI agents make real decisions, the why behind those decisions often disappears. The context is scattered across prompts, tools, policies, and approvals. Logs show what happened, but not why it was allowed. TraceMem is an attempt to make decision context durable. It records the reasoning, authority, and context behind AI actions as a system of record, not as monitoring data, but as memory. Happy to share more details or answer questions. - Tommi
Jan 2026 · tracemem.com
- 172C
Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com
- 18CA
Hi all, I'm the creator and maintainer of Dapr. Today we announced an agentic AI framework that allows developers to run thousands of agents on a single core that can scale to/from zero with minimal latency, with a durable execution engine that supports automatic retries. Us maintainers would very much appreciate your feedback
2025 · github.com
- 19AK
Mar 2026 · github.com
- 20
- 21
Another month, another agent-shell update. If you missed the last one, have a look at the 0.63 update. While this post showcases the latest highlights...
22d ago · xenodium.com
- 22CW
Jul 2026 · github.com
- 23NA
Hi, I'm a Dapr CNCF project maintainer. We've recently released Dapr Agents which provides agentic AI features together with built-in durable execution to guarantee statefulness and reliable agentic workflows that run to completion and retry upon failure. It runs natively on Kubernetes, has built-in OTEL integration and uses a lightweight architecture where agents scale to zero, allowing you to run thousands of agents on commodity hardware. It'd be great if you can test it out and give us feedback.
2025 · github.com
- 24CA
Jul 2026 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →