Research hubs
One page per topic — aggregating every relevant Notifire briefing with an editor's intro and frequently-asked questions. A stable starting point for engineers going deep on a subject.
Adversarial AI: Securing and Defending AI Models
A deep dive into the threats facing AI models, from prompt injection to data poisoning, and the engineering strategies required to build robust defenses.
AI agents and agentic workflows
How AI agents differ from chat assistants, the current frameworks, what they're actually good at, and the failure modes.
AI coding agents
How autonomous coding agents work, what SWE-bench actually measures, and where IDE and terminal agents fit into real engineering workflows.
AI fact-checking for generated content
How AI-generated text gets fact-checked at publish time — the three signals (entity overlap, claim verification, source corroboration), how Notifire combines them, and where the field is heading.
AI Model Routing Explained
AI model routing is the process of dynamically selecting the most appropriate large language model (LLM) for a given request based on criteria like cost, latency, and required capabilities.
AI-Driven Threat Intelligence and Response
A deep dive into how AI models are transforming cybersecurity by automating threat detection, analysis, and incident response at scale.
Cloud Security Posture Management (CSPM) Explained
A deep dive into how CSPM automates the detection and remediation of security risks across multi-cloud environments by identifying misconfigurations and compliance violations.
Critical CVEs of 2026
Notifire's running roll-up of the year's highest-impact vulnerabilities — what they were, who was affected, what defenders did.
eBPF
What eBPF is, why it changed Linux observability and security, and the production stacks (Cilium, Pixie, Falco) built on top of it.
GPU Infrastructure Management for AI Workloads
A guide to the complex engineering challenges of provisioning, scheduling, and optimizing GPU resources for training and inference at scale.
Implementing Post-Quantum Cryptography: The Engineer's Migration Guide
A technical guide for engineers on migrating systems to quantum-resistant cryptographic standards to defend against future threats.
Kubernetes security
CVEs in the Kubernetes ecosystem, hardening practices, supply-chain risks, and the policy-engine landscape.
LLM evaluation
How teams measure whether an LLM application is actually working in production, without relying on vibes.
llms.txt
What llms.txt is, why publishers are adopting it, and how it differs from robots.txt and the sitemap.
Model Context Protocol (MCP)
What MCP is, why every major AI vendor adopted it in 2025, and the security model engineering teams need to understand before exposing tools.
Non-Human Identity and Agent Credentials Explained
Non-human identity refers to a digital credential used by a machine, application, or automated process to authenticate and access resources without direct human intervention.
Observability
How modern observability works — OpenTelemetry, the traces/metrics/logs trio, and controlling telemetry cost at scale.
OLAP vs OLTP — and Where ClickHouse Fits
OLAP (Online Analytical Processing) systems are databases optimized for complex analytical queries on large datasets, whereas OLTP (Online Transactional Processing) systems are designed for managing large numbers of short, atomic transactions.
OS-Level Optimizations for AI Workloads
A deep dive into kernel-level tuning, memory management, and scheduling strategies to maximize performance for AI training and inference on modern hardware.
Platform engineering
How internal developer platforms, golden paths, and Backstage are replacing ad-hoc DevOps with self-service infrastructure.
Postgres Extended-Support Options
Postgres extended-support options are commercial services from cloud providers or third-party vendors that provide security patches and technical assistance for PostgreSQL versions that are no longer supported by the community.
PostgreSQL at scale
Operating PostgreSQL when the dataset and write rate stop fitting on a single instance — partitioning, replication, vacuum tuning, and the managed-service landscape.
Prompt Injection: A Practical Primer
Prompt injection is a critical vulnerability in large language model (LLM) applications where an attacker uses crafted inputs to manipulate the model's behavior and cause it to perform unintended actions.
Retrieval-augmented generation (RAG)
What RAG is, why teams adopt it, how graph-enhanced RAG changes the architecture, and the latest releases.
SBOM Explained for AI Pipelines
An SBOM for an AI pipeline, or AI Bill of Materials (AI-BOM), is a formal inventory of all components used to build and operate an AI system, including software packages, ML models, training datasets, and model weights.
Securing MCP Servers: Risks and Checklist
Securing Model Context Protocol (MCP) servers is the practice of protecting the tools, APIs, and data sources they expose to AI agents against risks like token leakage, over-permissioning, and supply-chain attacks.
Software supply-chain security
How modern attacks move through dependencies, build systems, and image registries — and the defences (SLSA, sigstore, SBOMs) that block them.
The Engineer's Guide to AI Governance and Compliance
A technical deep-dive into building, deploying, and maintaining AI systems that adhere to emerging global regulations and ethical standards.
The Engineer's Guide to AI-Generated Malware and Defense
A technical deep-dive into how threat actors use AI to create novel malware and the advanced strategies engineers can use to detect and mitigate these evolving threats.
The Engineer's Guide to Efficient AI Inference
A deep dive into the techniques and technologies for optimizing the performance and cost of running large AI models in production.
The Engineer's Guide to Securing Critical National Infrastructure (CNI)
A deep dive into the frameworks, technologies, and best practices for protecting essential systems like energy, finance, and defense from modern cyber threats.
The Essential Guide to Securing LLM Deployments
A comprehensive overview of the threats and best practices for securing production-grade LLM applications and infrastructure.
Vector databases
How vector databases power semantic search and RAG — pgvector vs. dedicated engines, HNSW vs. IVF indexing, and hybrid search.
What Is an AI Gateway
An AI gateway is a centralized control plane that sits between applications and large language model (LLM) providers to manage requests, enforce policies, and provide observability.
Zero-Downtime Kernel Patching: The Engineer's Guide to Live Updates
Explore the mechanisms, benefits, and trade-offs of applying critical Linux kernel security patches without rebooting servers.
Zero-trust architecture
What zero trust actually means beyond the marketing — identity-centric access, microsegmentation, and how teams migrate from perimeter security.
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