Compare/Agent Kernel vs Lilith-Zero

AI tool comparison

Agent Kernel vs Lilith-Zero

Which one should you ship with? Here is the side-by-side panel verdict, pricing read, reviewer split, and community vote comparison.

A

Developer Tools

Agent Kernel

Three Markdown files that make any AI agent stateful

Ship

67%

Panel ship

Community

Free

Entry

Agent Kernel is a minimalist framework that gives AI agents persistent state using just three Markdown files — one for memory, one for plans, and one for context. No database, no complex infrastructure. Works with any LLM provider and keeps agent state human-readable and version-controllable.

L

Developer Tools

Lilith-Zero

Rust security middleware that stops AI agents from exfiltrating your data

Skip

25%

Panel ship

Community

Paid

Entry

Lilith-Zero is a security runtime written in Rust that sits between your AI agent and its MCP tool servers, enforcing deterministic access control policies and blocking data exfiltration attempts before they reach the wire. It targets what it calls the "Lethal Trifecta"—the attack chain of accessing private data, incorporating untrusted content, then exfiltrating the combination—and blocks all three steps automatically. The technical stack is serious: fail-closed architecture (default-deny everything), dynamic taint tracking that marks sensitive data with session-bound tags, cryptographically signed HMAC-SHA256 audit logs, and formal verification via the Kani prover plus cargo-fuzz fuzzing infrastructure. Performance overhead is under 0.5ms at p50 with a 4MB memory footprint. It ships as a pip-installable Python SDK that auto-discovers and wraps its Rust binary. This is a Show HN project that appeared on Hacker News today and is currently at version 0.1.3 with 260 commits—small community (15 stars) but deeply engineered. As AI agents gain write access to filesystems, databases, and APIs, the absence of a policy enforcement layer becomes a serious liability. Lilith-Zero is one of the first open-source tools to treat this problem with the rigor it deserves.

Decision
Agent Kernel
Lilith-Zero
Panel verdict
Ship · 2 ship / 1 skip
Skip · 1 ship / 3 skip
Community
No community votes yet
No community votes yet
Pricing
Free / Open Source
Open Source (Apache 2.0)
Best for
Three Markdown files that make any AI agent stateful
Rust security middleware that stops AI agents from exfiltrating your data
Category
Developer Tools
Developer Tools

Reviewer scorecard

Builder
80/100 · ship

The simplicity is the feature. Three Markdown files, git-trackable, human-readable. No ORM, no migrations, no database to manage. For agents that need persistent state without infrastructure overhead, this is the pragmatic choice. I would pick this over LangGraph's complexity any day.

80/100 · ship

The Kani formal verification and cargo-fuzz integration tell me this isn't just a vanity security project—it's been engineered to actually be correct. Sub-millisecond overhead means there's no reason not to run this in front of every MCP agent deployment. 15 stars seems like an embarrassing undercount given what this does.

Futurist
80/100 · ship

Agent Kernel proves that the best agent infrastructure might be no infrastructure at all. Markdown as a universal state format means your agent's memory is inspectable, debuggable, and portable. This "files over frameworks" philosophy will age well.

45/100 · hot

This is the tool that enterprise security teams will demand before they let any AI agent touch production systems. The taint tracking model is particularly elegant—once data is tagged as sensitive, it can't flow to untrusted destinations regardless of what the LLM decides to do. This is the kind of principled security primitive the agentic ecosystem desperately needs.

Skeptic
45/100 · skip

Cute for prototyping but falls apart at any real scale. No concurrent access handling, no structured queries over memory, no way to prune state as it grows. You will outgrow three Markdown files the moment your agent needs to remember more than a weekend's worth of conversations.

45/100 · skip

The claims are impressive but 15 GitHub stars and one maintainer is not a security tool I'd deploy in production. Security tools require adversarial testing by the community over time—not just formal verification. The fail-closed design is correct philosophically, but I'd want to see 6 months of battle-testing and independent security audits before trusting it with real agent deployments.

Priya Anand
No panel take
45/100 · skip

Way too deep in the Rust/MCP security weeds for me to evaluate or use. This is infrastructure for enterprise AI security teams—not something a content creator or indie builder will interact with directly. Worth knowing it exists; not something I'll try this week.

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