HN Explorer

kundan_s__r

↗ HN profile [ 45.2 ms ] full profile

No user record in our sample, but kundan_s__r has activity below (stories or comments). Likely we have partial data — the full bulk-load will fill profiles in.

  1. Ask HN: How are you preventing LLM hallucinations in production systems?

    Hi HN, For those running LLMs in real production environments (especially agentic or tool-using systems): what’s actually worked for you to prevent confident but incorrect outputs? Prompt engineering and basic filters…

    3 points 5
  2. Show HN: Verdic Guard – Deterministic guardrails to prevent LLM hallucinations (verdic.dev)
    1 points 0
  3. Show HN: Verdic Guard – Deterministic guardrails to prevent LLM hallucinations

    I’ve been working on Verdic Guard, a validation layer for production LLM systems where prompts, filters, and monitoring aren’t enough. In many real deployments (fintech, enterprise workflows, agentic systems), the…

    2 points 1
  4. Show HN: Verdic Guard – deterministic guardrails for production AI

    I’m building Verdic Guard to explore a problem I kept seeing with LLMs in production. Models often behave well in demos and short interactions, but once they’re embedded into long, agentic, or real-world workflows,…

    1 points 0
  5. Show HN: Verdic Guard – validating LLM outputs against intent, not just prompts

    I’m building Verdic Guard, an experiment around a problem I kept running into while working with LLMs in production. LLMs usually behave well in demos and short interactions, but once they’re embedded into long,…

    2 points 0
  6. Show HN: A policy enforcement layer for LLM outputs (why prompts weren't enough)

    We’ve been working on production LLM systems and noticed a recurring issue: even well-crafted prompts fail under real-world conditions. We wrote a technical breakdown of the failure modes (intent drift, hallucinations,…

    1 points 0
  7. Show HN: Verdic Guard – Policy Enforcement and Output Validation for LLMs
    1 points 1
  8. Verdic – Intent governance layer for AI systems https://www.verdic.dev/

    We built Verdic (https://www.verdic.dev/ )after repeatedly running into the same issue while deploying LLMs in production: most AI failures aren’t about content safety, they’re about intent drift. As models become more…

    1 points 0