Research & Engineering Notes
Deep dives into non-deterministic evaluation, formal verification, prompt injection defense, and resilient agent architectures.
Why Your QA Team Can't Catch What AI Systems Actually Break
Traditional QA teams test deterministic input-output mappings with binary assertions. In probabilistic systems, tests pass while the system fails catastrophically in semantic space. Here is the mathematical reality behind AI quality failure.
LLM-as-Judge in Production: Mitigating Evaluator Drift and Positional Bias
Using large language models as automated judges for production evaluation introduces self-preference bias, verbosity bias, and evaluator drift over fine-tuning cycles.
Synthetic Data Generation for Edge-Case Test Harnesses in Regulated AI
How leading medical and financial engineering teams synthesize millions of adversarial, boundary-testing scenarios without leaking private training data.
Non-Deterministic Regression Testing in High-Velocity Continuous Delivery
When temperature is non-zero, every commit can introduce silent regression. Here is how to architect statistical CI/CD gates that do not halt deployment pipelines.
Automated Test Authoring with Mayar: From Product Specs to Living Assertions
Deep dive into Adept Mayar’s automated authoring engine that parses product requirements, OpenAPI schemas, and user journeys into executable test harnesses.
Measuring Confidence Calibration in Probabilistic Systems
An uncalibrated model is dangerous: when it claims 99% certainty on a hallucinated fact, catastrophic failure ensues. Learn Expected Calibration Error (ECE) testing.
Flaky Tests vs. Probabilistic Variance: A Mathematical Framework
Engineering teams waste thousands of hours debugging what they assume is code flakiness. We introduce a mathematical framework to differentiate infrastructure bugs from model variance.
Deterministic Guardrails Around Non-Deterministic Autonomous Agents
How to wrap probabilistic reasoning agents in formal state machines and deterministic sandboxes to guarantee mathematical safety boundaries in production.
Tool-Calling Architecture: Preventing Hallucinatory Side-Effects
Designing resilient function calling and tool schemas that reject ungrounded arguments, enforce idempotency keys, and block unauthorized recursive execution.
State Machine Verification for Autonomous Workflow Agents
Applying formal methods from aerospace avionics to multi-agent autonomous software workflows. Model checking and invariant verification in practice.
Latency Budgeting in Multi-Step Reasoning Pipelines and Compound AI Systems
Architecting compound AI systems with speculative decoding, semantic caching, and parallel routing to deliver sub-second responses on complex queries.
Graceful Degradation Patterns for Foundation Model Outages and Provider Latency
Building multi-provider circuit breakers, localized edge fallbacks, and deterministic rule-based degradation to guarantee 99.99% uptime.
Memory Management and Context Window Hygiene in Production AI Systems
Why stuffing millions of tokens into context windows degrades reasoning quality ("needle in a haystack" decay) and how to engineer active memory pruning.
Prompt Injection Defense-in-Depth: The Kawas Firewall Architecture
Why system prompt instructions alone will always fail against sophisticated attackers, and how Adept Kawas enforces real-time semantic token inspection.
Indirect Prompt Injection Mitigations for Enterprise RAG Pipelines
Malicious instructions hidden in crawled webpages, user PDFs, and database fields can hijack enterprise LLMs. A blueprint for untrusted content isolation.
Adversarial Red-Teaming for Enterprise Language Models and Agent Meshes
Moving beyond automated vulnerability scanners to human-directed, automated-amplified red-teaming across OWASP Top 10 for LLMs and agent swarms.
Zero-Trust Inference Architecture for Confidential Compute and On-Premises AI
Securing sensitive proprietary weights and private user prompts using cryptographic enclaves, hardware root of trust, and zero-trust perimeter isolation.
Jailbreak Taxonomy and Automated Fuzzing Methodologies in 2026
A comprehensive taxonomy of modern model jailbreaks—from multilingual cipher encoding and ASCII art attacks to recursive role-playing exploits.
Model Inversion and Training Data Extraction Countermeasures
Preventing malicious actors from extracting proprietary source code, PII, and training dataset memorization through membership inference attacks.
The Cost of Unvalidated AI: Measuring Stealth Technical Debt in Enterprise Systems
Deploying unverified AI into core business workflows creates invisible compound risk. How enterprise CTOs quantify and remediate probabilistic tech debt.
ISO 42001 and AI Governance Readiness for Engineering Leaders
A practical technical guide for engineering teams preparing for ISO/IEC 42001 certification, EU AI Act compliance, and NIST AI RMF audits.
Why Prompt Engineering Is Not a Security Strategy
Relying on system prompts to enforce access control and safety boundaries is the 2026 equivalent of client-side validation. Security requires architectural boundaries.
From Evals to Guardrails: Operationalizing AI Precision Across the Lifecycle
How leading technology organizations connect pre-deployment evaluation benchmarks with real-time runtime guardrails to achieve continuous system reliability.
The Three Pillars of Modern AI Resilience: QA, Product Engineering, and Cybersecurity
Why treating quality assurance, distributed system engineering, and cybersecurity as separate silos guarantees failure in mission-critical AI systems.
Why Precision Is Not Negotiable: The Adept Engineering Philosophy
When autonomous software makes medical diagnostics, executes billion-dollar settlements, and controls physical machinery, tolerance for hallucination is zero.