Show HN: Adaptive Runtime – AI agent layer, no GPU, crash recovery
Adaptive Runtime introduces a new intelligence layer designed for stateful AI systems, addressing common runtime issues faced by AI agents in production. It provides solutions for crash recovery, memory retention, and decision-making confidence, ensuring that AI agents can adapt to changing conditions. The system operates without the need for GPUs and can run on minimal infrastructure, making it accessible for various applications.
- ▪Adaptive Runtime is not a chatbot framework or LLM wrapper, but an intelligence layer for AI systems.
- ▪It addresses runtime problems such as crash recovery, memory loss, and chaotic retries.
- ▪The system automatically analyzes conditions, calculates confidence, and selects actions to maintain stability.
Opening excerpt (first ~120 words) tap to expand
Adaptive Runtime Runtime Intelligence Layer for Stateful AI Systems Not a chatbot framework. Not an LLM wrapper. Not a workflow builder. An adaptive runtime intelligence layer — the missing piece between your AI logic and production reality. The Problem Most AI frameworks solve the model problem. Nobody solves the runtime problem. Your AI agent in development: Works perfectly. Your AI agent in production: Crashes. Forgets state. Retries blindly. Dies silently. Production AI systems fail because of: 💥 No crash recovery — state lost on restart 🧠 No memory — agent forgets context between sessions 🔁 Retry chaos — blind retries with no back-off 📉 No confidence scoring — decisions made without certainty 🌊 No contextual awareness — can't adapt to changing conditions Adaptive Runtime fixes…
Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.