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agent-recall-ai
Your AI agent never starts over again
AI agents die mid-task when context fills — losing every decision and WHY it was made. agent-recall-ai fixes this with Decision Anchors: critical reasoning is protected from compression and never pruned. Zero-code for Claude Code: pip install agent-recall-ai && agent-recall-ai install-hooks Works with OpenAI, Anthropic, LangChain, LangGraph, CrewAI. Includes live dashboard, PII redaction, and cost monitors.
Hey Product Hunt! 👋 I'm Srinath, and I built agent-recall-ai.
The backstory: I was doing a complex auth refactor with Claude Code. 2 hours in, the context window filled and the session died. Every decision, every constraint, every "why" — gone. Starting from scratch felt wrong. So I built structured auto-save for AI agents.
The key insight is Decision Anchors — messages containing words like "decided", "rejected", "because", "constraint" are mathematically protected from context compression. The reasoning chain survives forever, no matter how long the session runs.
Zero-code setup for Claude Code users:
pip install agent-recall-ai
agent-recall-ai install-hooks
Two commands. Every session protected from that point on.
Would love to hear from anyone building long-running agents — what's your biggest pain point when sessions die? Happy to answer any questions about the architecture or design decisions!
About agent-recall-ai on Product Hunt
“Your AI agent never starts over again”
agent-recall-ai was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #135 on the daily leaderboard. AI agents die mid-task when context fills — losing every decision and WHY it was made. agent-recall-ai fixes this with Decision Anchors: critical reasoning is protected from compression and never pruned. Zero-code for Claude Code: pip install agent-recall-ai && agent-recall-ai install-hooks Works with OpenAI, Anthropic, LangChain, LangGraph, CrewAI. Includes live dashboard, PII redaction, and cost monitors.
On the analytics side, agent-recall-ai competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how agent-recall-ai performed against the three products that launched closest to it on the same day.
Who hunted agent-recall-ai?
agent-recall-ai was hunted by Srinath S. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of agent-recall-ai including community comment highlights and product details, visit the product overview.
Srinath S