Individual developers and 1–5 person teams
Indie devs & small teams
You spent the afternoon debugging a forgotten fact. The embedder had failed.
Correct a fact and watch the old one stay on record instead of vanishing.
The problem
You shipped an agent. It forgot something, or contradicted itself. Logs say the write succeeded. Retrieval returns nothing. Vector-first memory made the embedder a single point of silent failure — and you had no audit trail to prove what happened.
Silent memory loss when the embedder fails — the write succeeds, the fact is unretrievable.
Documented in mem0 #5245How CLS++ handles it
Persistence comes from the engine's own tokenization, not the embedding — so a dead embedder degrades ranking but loses nothing. The SDK is three calls: learn, ask, correct. Swap it in over mem0 / LangGraph / CrewAI without a rewrite. Package name everywhere: clsplusplus.
Under the hood — the real script
from clsplusplus import Brain — your first auditable memory in three lines.
pip install clsplusplusfrom clsplusplus import Brain
brain = Brain("my-agent")
brain.learn("Customer is on the Pro plan")
brain.correct("Customer is on the Pro plan", "Customer upgraded to Enterprise")
brain.ask("What plan is the customer on?")
# -> current belief; the old one is archived, not gone500 free API calls/day is enough to evaluate against your real agent — not a toy sandbox.