Illustration for the Sazko Solutions article on the future of AI in software development
Posted on Author Mahesh Kumar Categories AI, DigitalTransformation, Software

The Future of AI in Software Development: What’s Actually Changing

By September 2026 the industry’s own framing had shifted: the value is in workflows, data rights and human review, not flashy demos. That’s a good moment to take stock of what has actually changed in how software gets built. It’s easy to be either dismissive or breathless about AI’s effect on software development, and both postures avoid the more useful question: what, specifically, is actually different about how software gets built today versus three years ago? A few concrete shifts are worth naming, separate from the marketing around them.

Read More
0
Illustration for the Sazko Solutions article on n8n and AI-orchestrated workflow automation
Posted on Author Mahesh Kumar Categories AI, App Development, Software

n8n and the Rise of AI-Orchestrated Workflows

As of August 2026, several of the newest large models are being marketed specifically for managing long-running projects and collaborating with developers. Workflow orchestration tools are where a lot of that ambition meets reality. Workflow automation tools have existed for years, but something changed once AI models got good enough to sit inside the workflow rather than just around it. n8n is a useful example: an open-source, node-based automation tool that was already popular for connecting APIs and services, and has become a common substrate for AI-orchestrated workflows precisely because its workflows are structured, inspectable, and easy for both humans and models to reason about.

Read More
0
Sazko Solutions article on long-running AI agents that improve between sessions, mid-2026
Posted on Author Mahesh Kumar Categories AI, Software

Agents That Learn Between Sessions: The Move to Long-Running AI Workflows

In May 2026, Anthropic described a technique it called “dreaming” — letting an autonomous agent review its own past behaviour between sessions, spot patterns, and adjust how it works next time. It’s part of a broader industry push toward agents that handle long-running workflows in areas like coding, finance and legal work, rather than one-shot tasks. That shift changes what you have to build around an agent.

Read More
0
Illustration for the Sazko Solutions article on agentic AI adoption in the enterprise
Posted on Author Mahesh Kumar Categories AI, Digital, Software

Agentic AI in the Enterprise: From Chatbots to Systems That Act

Google’s Cloud Next in April 2026 was billed as the arrival of the “agentic era,” complete with an enterprise agent platform and chips designed for it. The word “agent” gets applied loosely enough right now that it’s worth being precise. A chatbot takes an input and returns an output. An agent does something meaningfully different: it holds a goal, plans a sequence of steps to reach it, calls tools or other systems along the way, observes the results, and decides what to do next — often without a human approving each step. That loop, not the underlying language model, is what “agentic AI” actually refers to.

Read More
0
Illustration for the Sazko Solutions article explaining the Model Context Protocol (MCP) and agentic AI
Posted on Author Mahesh Kumar Categories AI, App Development, Software

What MCP Actually Is, and Why It’s Becoming AI’s Common Plumbing

By March 2026, the Model Context Protocol had reportedly crossed tens of millions of installs, and NVIDIA’s GTC keynote was full of enterprise agents running in production. Every AI agent eventually needs the same thing: a reliable way to reach outside its own context window — into a database, a ticketing system, a filesystem, an internal API — and act on what it finds. Before the Model Context Protocol (MCP), teams solved this the same way they solved every integration problem: a bespoke adapter per tool, per model, per vendor. MCP’s contribution is boring in the best possible way — it standardizes that connector so it only has to be built once.

Read More
0