HB-Eval System

Founder @ HB-Eval | AI Reliability Researcher.
Cracking the code of Withdrawal Pathology. 🧠
Creating the world's first Graded Certification for AI Agents (L1-L

[HB-Eval System @hbEvalSystem]

I’m excited to join the technology and AI community and share my research journey, where I’m working on building a new generation of explainable agents with measurable cognitive performance.
Abuelgasim Adam
Founder of HB-Eval System

[HB-Eval System @hbEvalSystem]

Modern AI agents operate in messy environments:
• APIs fail • Tools become unavailable • Context changes • Memory becomes inconsistent • Plans need revision
Traditional benchmarks rarely capture these conditions.
Yet these are exactly the situations that determine whether an

[HB-Eval System @hbEvalSystem]

Most AI benchmarks measure what a model can do.
Very few measure what happens when things go wrong.
A model can achieve 95% accuracy in evaluation and still fail in production.
Why?
Because capability and reliability are not the same thing.
🧵

[HB-Eval System @hbEvalSystem]

The Day of Arafah is the greatest of days, a day on which God forgives sins and pardons. I ask God to forgive you all past and future sins, and that next year you may be in the best of circumstances. I send you sincere prayers from the depths of my heart while I am fasting.

[HB-Eval System @hbEvalSystem]

@GeminiApp Yes you are doing great job o human thank alot

[HB-Eval System @hbEvalSystem]

3,000 Experiments in Progress! 🚨 Testing the limits of AI Reliability.
​Watching the HB-Eval engine stress-test the giants: Llama-3.3-70b, 3.1-8b, and Gemma-2-9b.
​We aren't just asking "Can it reason?" — We are asking "When will it break?" 🔍 Current Stage: Cycle 50/1000

[HB-Eval System @hbEvalSystem]

Breaking the Illusion of AI Reliability 🚀⚖️
​I’ve just completed a massive 3,000-run stress test on LLM agents using HB-Eval.
​The goal? Testing behavioral reliability under systematic Compound Fault Injections.
Results show that "Bigger" doesn't mean "Reliable." 📊👇

[HB-Eval System @hbEvalSystem]

Introducing HB-Eval: A multi-layered architecture designed for the "Real World"
​Unlike traditional benchmarks, HB-Eval uses Episodic Narrative Memory EDM to detect failure contexts before they happen.
​It’s not just about getting the right answer it’s about Preemptive Adaptation

[HB-Eval System @hbEvalSystem]

a catastrophic 43% Reliability Gap. 📉
​I’ve discovered a hidden failure mode called "Withdrawal Pathology"—where agents choose to fail efficiently rather than succeed reliably.
​Here is how my framework HB-Eval solves the Nash Equilibrium of AI failure. 🧵👇

[HB-Eval System @hbEvalSystem]

Witness HB-Eval in action!
​Cycle 1: System detects a reliability gap and stores the failure context in Episodic Memory.
Cycle 2: Preemptive Intelligence detects a 'Similarity Match' and adapts BEFORE the failure occurs.
​This is how we move from AI Capability to Reliability "

[HB-Eval System @hbEvalSystem]

@shizhediao Thank you for your great job i watched the presentation its very amazing, so can you take a QUICK look for our papers in Flow links
https://t.co/3OuqYRG3xs

https://t.co/8PzaSdJjCG

https://t.co/wSU9ADlx1S

https://t.co/rHOmgGoKR0

[HB-Eval System @hbEvalSystem]

@shizhediao Can take a QUICK look of our papers in Flow
https://t.co/3OuqYRG3xs

https://t.co/8PzaSdJjCG

https://t.co/wSU9ADlx1S

https://t.co/rHOmgGoKR0

[HB-Eval System @hbEvalSystem]

@dair_ai https://t.co/rYrSwOasnM

[HB-Eval System @hbEvalSystem]

Full text: https://t.co/mcWafkh9Ds
​#AI_Safety #FutureOfAI
@Preprints_org وحسابات مهتمة بالذكاء الاصطناعي مثل @IEEEorg (

[HB-Eval System @hbEvalSystem]

The Results 📊
Our controlled simulations show that grounding explanations in certified performance history works:
✅ Calibrated Trust Score: 4.62/5.0
✅ Transparency Index: 0.91
✅ 51% reduction in human cognitive load compared to traditional baselines.​#AI_Safety #FutureOfAI

[HB-Eval System @hbEvalSystem]

The Problem: "Explainability
Current AI explanations (like Chain-of-Thought) are often "post-hoc linguistic rationalizations." They sound fluent but aren't always grounded in the agent's actual decision history.
​In high-stakes environments, we need evidence, not just narratives

[HB-Eval System @hbEvalSystem]

🚀
I am thrilled to announce the publication of my latest research paper: "HCI-EDM: Performance-Grounded Interpretability."
​We are moving beyond "guessing" why AI acts to "proving" it through certified performance history.
​🔗 Read the full paper here: https://t.co/rHOmgGod1s

[HB-Eval System @hbEvalSystem]

@alshbabyt66607 https://t.co/3OuqYRFvHU

https://t.co/8PzaSdILN8
https://t.co/wSU9ADkZck

[HB-Eval System @hbEvalSystem]

The Architecture
It’s not just a benchmark; it’s a 4-layer stack for trustworthy AI:
🔹 HB-Eval (Evaluation)
🔹 Adapt-Plan (Real-time Control)
🔹 EDM (Memory Governance)
🔹 HCI-EDM (Certified Interpretability)
A complete loop to prevent reliability #AgenticAI #LLMs #Reliability

[HB-Eval System @hbEvalSystem]

@langchain, @MicrosoftProjectAutoGen, or researchers like @AndrewYNg or @karpathy.
https://t.co/wSU9ADkZck
https://t.co/kSSUI7pUYc

[HB-Eval System @hbEvalSystem]

@langchain, @MicrosoftProjectAutoGen, or researchers like @AndrewYNg or @karpathy.
https://t.co/8PzaSdILN8
https://t.co/kSSUI7pUYc