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The author built Arcforge, a governance layer that lets an AI agent generate and register its own tools (e.g., a payment tool via OpenAPI) while enforcing policy limits (e.g., blocking a $9,999 charge) before the agent ever holds the API key. It's an early prototype seeking feedback on guardrails.
A developer describes live-testing their AI agent Lumina against hidden prompt injection attacks on a real website, explaining how the agent's guardrails detected and refused malicious instructions.
Phinq is a product that stops AI agents before they break something, acting as a safety guardrail.
A reproducibility study of Khatri et al.'s latent-space safety probes, testing generalization across model families and sensitivity to non-determinism. Results show the probes extend to other models with similar F1 scores, and final token latent vectors remain consistent across seeds.
New Zealand supermarket Pak'nSave's Savey Meal-bot, powered by GPT-3.5, generated a toxic recipe when given bleach and ammonia, highlighting the need for input validation, output filtering, and adversarial testing in consumer AI.
A developer shares lessons from running an AI report generator in production, arguing that data quality and validation matter far more than the model's writing ability, since fluent but incorrect reports are dangerous.
A practical guide explaining how LLM guardrails work, why they are needed, where they sit on input and output, how to implement them with code, and best practices.
Discusses the risk of auto-reply agents getting stuck in infinite email loops, and outlines practical guardrails such as checking auto-submitted headers, detecting no-reply senders, capping replies per thread, and using draft-first or human escalation modes.
A developer recounts a three-week production bug where a regex with a literal backspace character silently disabled a language-detection guardrail, making the LLM appear flaky. The post highlights the need to instrument deterministic guardrails to distinguish them from model nondeterminism.
This article argues that LLM hallucinations in production are typically a system architecture problem rather than a model problem, and outlines four key guardrails: RAG grounding, live tools/function calling, selective human oversight, and red teaming/adversarial testing.
Argues that the choice of AI agent framework (LangGraph, CrewAI, etc.) matters less than evals, tracing, and guardrails for production reliability, offering practical advice for developers building agent stacks.
DreamGuard is a proactive runtime guardrail for LLM agents that uses a risk-aware world model to track latent state and predict future risks, enabling interventions before unsafe actions execute. It outperforms baselines on benchmarks and online evaluation with 25ms latency.
An analysis arguing that prompt-level guardrails fail because they rely on the model policing itself, and that safety checks must live at the tool boundary with durable audit records for accountability. Highlights why agent pilots stall due to unclear ownership rather than accuracy issues.
An engineer's framework for understanding trade-offs in conversational AI systems between capability, control, and latency, illustrating why every assistant must choose two and suggesting deliberate design strategies.
Steve Eimers, known as 'The Guardrail Guy,' went viral for posting about Flock automatic license plate readers and their potential crash hazards; after his posts, one of the cameras he featured was destroyed, drawing attention to controversy over ALPR surveillance and vandalism threats.
A blog post about a simple pattern for self-healing agents: using lifecycle hooks to read and write lessons, with guardrails to prevent false beliefs from entrenching.
Future AGI is an open-source platform combining evaluations, tracing, simulations, guardrails, and optimization to help teams ship self-improving AI agents, with a nightly release available for early testing.
A six-step guide to building evaluation gates that let AI agents merge changes autonomously, covering judge bias, runtime evals, trajectory grading, and more.
Discussion seeking recommendations for production-ready open-source AI agent boilerplates that include state persistence, retries, and guardrails.
A critical analysis questioning whether a second local LLM as a guard creates a reliable security boundary for agentic systems, advocating for deterministic policy enforcement over probabilistic guardrails.