AIES Community Launch Kits & Distribution Blueprints

Production-grade distribution templates for launching the AI Engineering Standard (AIES) across Hacker News, Dev.to, Substack, Reddit, and Discord.

1. Hacker News Launch ("Show HN")

Title: Show HN: AI Engineering Standard (AIES) – Open, vendor-neutral harness for AIDLC

Draft Post Content:

Hey HN, Gaurav here.

Over the past two years building enterprise AI platforms, I saw engineering teams reinventing private, incompatible dialects for system prompts, context windows, MCP tools, and eval gates. Every squad had a different way of defining "production readiness," leading to silent prompt regressions, unbounded token costs, and security gaps.

We built AIES (AI Engineering Standard) as an open-source, vendor-neutral harness specification for the AI Software Development Lifecycle (AIDLC).

Core Thesis: The LLM is one component. The harness is the product.

Key Technical Highlights:

50/50 Rule for Context Engineering: Pin critical instructions to the top and bottom 15% of context windows to overcome model attention decay ("lost in the middle").

Bounded MCP Tool Contracts: Strict schema validation and token budget limits for Model Context Protocol (MCP) servers.

CLI Conformance Auditor (npx @grvmithas/create-aies-kit audit): Automated linter that scans a repo's harness files (AIES.md, AGENTS.md, .cursorrules, stage gate schemas) and issues a 0–100% compliance score — plus npx @grvmithas/create-aies-kit fix to auto-remediate missing files.

Standards Crosswalk: Direct alignment with NIST AI RMF 1.0 (SP 1270), ISO/IEC 42001, and OWASP Top 10 for LLM Applications.

Site: https://www.ai-standards.dev
Repo: https://github.com/grvmithas/open-ai-engineering-standards

I’d love feedback on the stage gate schemas and MCP security contracts!

2. Dev.to / Medium Technical Deep-Dive

Title: How to Prevent Indirect Prompt Injection Using Bounded MCP Tool Contracts

Article Outline:

The Vulnerability: How untrusted third-party tool outputs (web search, DB queries) trigger indirect prompt injection in agentic pipelines (OWASP LLM01 & LLM07).
The AIES Harness Pattern: Restricting tool capabilities using declarative JSON Schema input/output filters and strict authorization gates.
Runnable Code Blueprint: A step-by-step TypeScript example implementing an AIES-compliant MCP tool wrapper with token truncation and output validation.
CI/CD Quality Gate: How to run npx @grvmithas/create-aies-kit audit in GitHub Actions to block unvalidated tool configurations.

3. Reddit & Discord Cookbook Posts (r/MachineLearning, r/DevOps, r/SoftwareEngineering)

Title: We standardized our LLM prompt & eval quality gates in CI/CD — here’s our open-source harness blueprint

Post Outline:

Problem: Moving LLM apps from prototype to production requires reproducible quality gates, not subjective manual testing.
Solution: Open-source AIES cookbook recipes for Promptfoo, DeepEval, and Langfuse integrated directly into GitHub Actions.
Runnable Command: npx @grvmithas/create-aies-kit --stack nextjs --ide cursor --yes
Call to Action: Try the auditor tool in your repo and share your conformance score!