Launched this week
Extella.AI
Agentic platform that evolves & builds reusable systems
120 followers
Agentic platform that evolves & builds reusable systems
120 followers
Extella is an agentic AI platform that self-evolves. It remembers what works and reuses it, so each task runs faster and cheaper. That memory lives in four layers: Rules adapt to you, Concepts build a knowledge base, Experts turn work into automations, and a KV store keeps your keys encrypted. Bring your own LLM, connect any tool (Slack, Notion, Gmail, GitHub), any GitHub library, ML model, or your own — all managed from a single workspace. By Day 30, it's a system only you have.
Voquill
Intereting. Just curious how this handles conflicts or inconsistencies when it starts learning across different workflows. Good luck!
Absolute Cryptography
@henry_habib Good question — and an honest one.
Conflicts surface explicitly, not silently. When two Rules contradict, the agent flags it during interaction. You decide which stays, or you merge them into a new Rule that resolves the tension. Nothing conflicting quietly accumulates in the background.
For knowledge across workflows, Concepts handle it the same way. When similar knowledge comes in from different sources, the system deduplicates and merges rather than stacking duplicates. If there's a genuine inconsistency — two workflows that learned opposite things — it gets surfaced for human resolution, not auto-resolved by the system.
But here's where it gets more interesting.
You can teach the agent exactly how to handle ambiguity — not just flag it, but resolve it. You define Rules for how to research a contested claim, how to fact-check, how to assess recency and relevance, how to weigh conflicting sources by importance. The agent learns your epistemology, not just your preferences. Once those Rules exist, the same judgment you'd apply manually gets applied automatically — every time, at scale.
You can also teach the agent to recognize the boundaries of its own knowledge. Rules and Concepts can encode a self-assessment protocol: when the agent hits a gap, it doesn't guess — it identifies what it doesn't know, flags it, and can trigger an automated research or learning workflow to close that gap. It learns to know what it doesn't know.
And then the final step: you automate the configuration work itself. Once the agent understands your standards for conflict resolution, fact-checking, and self-improvement — you build Experts that handle that process automatically. New knowledge comes in, gets verified against your criteria, gets merged or flagged, gets added to memory — without you touching it.
The goal of human involvement is not to be always present. It's to teach the system well enough once that it stops needing you for that class of decisions entirely. Every hour you spend teaching the agent reduces the next thousand hours of manual intervention to zero.
That's the trajectory the architecture is designed for. You start in the loop. You work yourself out of it.
Thank you for asking!
This is a great companion when you are on a cross between creativity and technology!
I built some tools for my TTRPGs and automated script writing with this tool
Absolute Cryptography
Absolute Cryptography
If you want to test Pro today – here's how it works:
1. Apply code PRO-PLAN to activate the plan first
2. After that, top up credits inside the app using code PHPROMO50 (first 50 users)
If you already have an Anthropic or OpenAI key, connect it instead of buying credits.
Either works, but the Pro activation has to go first.