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pheromone-network

A zero-dependency TypeScript memory kernel that gives any agent long-term memory. No training or backpropagation: each output reads a few tag-compatible neighbors, updated by a manual Hebbian rule. Links used often are reinforced; idle ones evaporate by half-life. Based on the paper Local Pheromone Network (arXiv:2606.30669).

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This is 1 of 177 launches in persistent memory for ai agents — see how it stacks up on momentum and crowding →

9 other launches read as similar to this one →

Details

External ID
1403762779
Source
GITHUB
Company
—
Product
pheromone-network
Website domain
github.com
Launched
Oct. 4, 2026
Cohort
—
Upvotes
39
Upvotes percentile
0.65
Tags
agent-memory, associative-memory, local-learning, memory, npm, offline-ai, semantic-recall, typescript

Enrichment

Niche
persistent memory for ai agents
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
typescript memory kernel for ai agents
Manually corrected
False

Could you build this?

Partial Translating the algorithmic equations from an arXiv paper on local pheromone networks into TypeScript is feasible, but validating and tuning novel associative memory networks without existing reference code requires mathematical rigor.

What it would actually take: Requires implementing a graph-based associative memory network in TypeScript with custom decay functions (half-life evaporation) and Hebbian link weight adjustments. The challenge lies in accurately implementing the mathematical dynamics specified in the academic paper (arXiv:2606.30669) so that memory recall, edge pruning, and tag compatibility converge properly under high load.

Competitors

Other products that read as similar to this one — 9 launches clear the similarity bar, closest 8 shown.

Attention rank: #2 of 10 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 279 days after the earliest competitor.

Other launches for this product