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Artificial Intelligence|Sep 30, 2026

Who needs documentation anyway in the era of AI?

When software engineering emerged in the mid-20th century, shaped by pioneers such as Alan Turing, John von Neumann, Grace Hopper, Edsger Dijkstra, and later Fred Brooks, software was largely about logic, mathematics, and precise instructions for a machine. Programs were smaller, the gap between the implementation and the knowledge required to understand was relatively short, and much of the truth about a system could be found directly in its source code. The code was the documentation.

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Artificial Intelligence|Sep 30, 2026

OWASP AISVS 1.0 - Practical Look at the New AI Security Standard

Not so long ago, I wrote an article about OWASP ASVS 5.0 (a comprehensive security checklist aiming for web applications). I mentioned there that AI security was intentionally left outside of its scope. There is now a brand new OWASP document specifically for filling this gap: AISVS. I've looked at this standard. Is it actually helpful when building an AI-enabled system?

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Artificial Intelligence|Sep 28, 2026

AI-driven CVE overload: where the secure SDLC breaks, and how to fix it

Around 66,000 CVEs are expected in 2026. Most won't affect your code, but which ones will? A practical look at layered, AI-supported vulnerability triage.

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Artificial Intelligence|Sep 22, 2026

How Banks Govern Autonomous AI in Software Development

For a bank, introducing autonomous coding agents is an architecture, security and governance problem. Here is how Visdom addresses data residency, machine-enforced boundaries, credential security, AI tracing, audit integrity, human oversight, code quality, test verification, organizational context and cost governance.

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Artificial Intelligence|Sep 7, 2026

Shadow AI Is Already in Your Codebase - Why Banking Needs a Risk-Based Governance Model for AI-Native SDLC

Most of the AI-generated code already in your codebase arrived through unsanctioned tools on personal accounts. This is Shadow AI — and like shadow banking before 2008, the risk is invisible until it isn't. Here's how to govern it with risk-based triage, traceability, and Continuous Modernization.

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Artificial Intelligence|Sep 2, 2026

Why AI-Native Software Delivery Needs More Than a Better Model

AI tools work. Adoption is above 80%. And yet measurable business value remains stubbornly low. The bottleneck is not the model — it's the software delivery system around it.

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Artificial Intelligence|Sep 2, 2026

When AI Writes the Code, What Runs the SDLC?

A coding agent is not an AI-native SDLC. Visdom provides the control plane — context, orchestration, sandboxing, and auditability — required to turn AI-generated code into software enterprises can trust in production.

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Artificial Intelligence|Jul 14, 2026

Natural language search to domain query search with AI & AWS Bedrock

Learn how to build a natural language search feature using AI and Amazon Bedrock. Translate user intent into secure, structured SQL or GraphQL queries without training custom LLMs.

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Artificial Intelligence|Jul 13, 2026

How to evaluate your agents?

Evaluating agentic systems is a multi-dimensional challenge that requires a multi-layered framework. A robust evaluation system must verify both functional and non-functional requirements. The system should verify whether an agent is fulfilling its core objectives, while performing efficiently, safely and with low latency. Furthermore, the system must account for scalability while ensuring the agent's underlying reasoning remains transparent and traceable. Those different evaluation layers allow, to evaluate the model both from the technical and strategic business perspectives.

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Artificial Intelligence|Jul 1, 2026

AI Must-Read for June 2026: Top Trends that Keep Great Engineers Ahead

A monthly reading roundup - no chasing every model, no top-50 lists, no marketing. One thread running through it all: the best model on the planet can be switched off on a Friday afternoon, so the real asset is what you build around it. You lease the model, but the process is yours.

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Artificial Intelligence|Jun 26, 2026

Diffusion models quantization benchmark

Diffusion models became de facto standard in image generation. While remarkably powerful, they rely on a multi-step process of iterative denoising, which takes time. Text generation is also processed in a sequential manner, however the text can be streamed and visualized token by token, giving a natural, real-time feeling, similar to how humans read or write a text. With images, we must wait for the final denoising step to complete before a usable result appears. This makes optimizing diffusion models for speed and efficiency a critical challenge.

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Artificial Intelligence|Jun 3, 2026

GitHub All-Stars vol.17: CodeBurn - The $200/Day Therapy Session Your Terminal Didn't Know It Needed

A slightly unsettling realization hit us at VirtusLab not long ago - our collective list of starred GitHub repositories had quietly ballooned into something that could generously be called "a problem." Instead of pretending it wasn't happening, we decided to lean into it: every two weeks, we pick a trending open-source project, pull the hood off, and tell you what we find underneath. We focus on fresh, relatively unknown repos - not the usual suspects that everybody and their tech newsletter already covered (because let's be honest, you don't need us for that).

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