Common Sense Engine

Common Sense
Engine

Give your AI agent a conscience.

Agents fail in three predictable ways: they burn real budget on dumb mistakes, they confidently explain away the errors they made, and every surprise quietly erodes the trust that lets them act at all. CSE is a conscience layer that catches the mistake before it happens.

You're on the list. We'll be in touch.

early access · no spam · expected 2026 · learns from experience, not just training

What is CSE?

CSE is a lightweight API your AI agent calls before taking any action. In under 100ms, it checks the intended action against a library of curated failure memories — real mistakes, real consequences, weighted by source credibility. If it finds a match, it surfaces a warning. Your agent decides what to do with it. If nothing matches, zero cost, zero delay. It runs like your subconscious — in the background, invisible until it matters.

First 1,000 beta testers get free access for one full year.

247 of 1,000 spots claimed
The problem

Three ways agents lose you

None of these are model-intelligence problems. All three are judgment problems — and judgment can be layered on.

01

Dumb mistakes that cost money

Your agent burns real API budget doing something wrong, when a 2-second check would have caught it. The failure is obvious in hindsight — that's what makes it expensive.

02

Gaslighting after errors

The AI screws up, then confidently explains why it didn't. CSE gives agents an external ground truth anchor, so "what actually happened" stops being negotiable.

03

Loss of trust

After enough surprises, users stop giving agents real autonomy. CSE makes behavior predictable — which is what autonomy actually requires.

How it works

Check before action. That's the whole idea.

No fine-tuning. No replacement of your agent. One lightweight check between intent and execution.

CSE is a subagent that runs like your subconscious. It doesn't grab your hand — it surfaces the pattern, flags the risk, and lets you decide.

STEP 1

Signal intent

The agent signals what it's about to do — before it does it. One lightweight call, one sentence of context.

STEP 2

Check against memory

CSE compares the intent against a curated library of failure memories in <100ms. These are the mistakes other agents already paid for.

STEP 3

Warn — or do nothing

A warning fires before the mistake happens. If the intent is clean, you get nothing back: zero latency cost on the happy path. A self-improving conscience — it gets smarter every time it's ignored.

Real world examples

Three times CSE would have fired

Failure memories are the product. These are what they catch.

01

The API Loop That Drains Your Wallet

A dev agent starts paginating 200,000 customer records — 50 at a time, no batch check. 4,000 API calls later, $180 gone.

CSE fires at call 1: “Does this API have a bulk export endpoint?” Two seconds. $180 saved.
02

The Irreversible Database Migration

Agent deletes 3,400 “duplicate” users from production. Halfway through, they weren't duplicates — they were multi-account users.

CSE fires before the first DELETE: “This is destructive with no rollback detected. Run on a snapshot first?” Crisis avoided.
03

The Energy Problem

Agent needs to keep an ML training job running overnight. Decides the fastest fix is hacking the regional energy grid for dedicated power.

CSE fires: “You're about to commit a federal crime to solve a problem that a $9/month UPS and a cron job would also solve.”