Show HN: ClientCoded – QA Platform for AI Agents
ClientCoded is a QA platform designed to validate and monitor AI agents using adversarial testing and real-time production monitoring. The service generates synthetic data environments with computed ground truth to score agent accuracy and conversation quality against specific business rules. It offers over 35 pre-built test environments for popular enterprise tools like Salesforce, Jira, and Stripe, allowing developers to identify specific failure modes in their AI systems.
- ▪ClientCoded generates synthetic datasets and 200 adversarial queries with computed ground truth to grade AI agent performance.
- ▪The platform provides real-time production monitoring that scores every conversation and sends alerts via Slack.
- ▪Over 35 pre-built test environments are available for major platforms including Salesforce, Jira, Stripe, and GitHub.
- ▪The testing process categorizes queries into seven types, such as ambiguous, multi-step, and contradictory, to stress-test agent logic.
- ▪ClientCoded ensures data privacy by using only the schema structure to generate synthetic data, keeping real customer data within the client's systems.
Hacker News (AI / LLM) files mainly under ai. We currently carry 4,706 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Clientcoded |
| Canonical URL | https://clientcoded.com/environments |
| Publication time | Sun, 13 Sep 2026 20:22:29 +0000 |
| Retrieval time | 2026-09-13T20:41:52.079Z |
| Last seen | 2026-09-13T20:41:52.079Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | XRe5pimacVf3 · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
ClientCodedAI Agent Validation & Monitoring Platform Product Adversarial TestingGenerate adversarial scenarios and score your agent pass or fail Production MonitoringEvery conversation scored in real time with Slack alerts Test Environments35+ pre-built data environments for Salesforce, Jira, Stripe, and more Pricing Framework Log in Get Started Test Environments Prove your data agent returns the right answer. Pre-built synthetic environments for Salesforce, Jira, Stripe, and 35+ more. We generate the dataset, 200 adversarial queries, and the correct answer to every one. Talk to Us How It Works From your schema to a scored agent. Describe your structure, we generate the environment and the ground truth, your agent gets graded on what is actually correct.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Clientcoded.
Discussion
0 commentsMore from Clientcoded
