#agentic workflows

Explore how agentic AI and multi-agent systems are redefining artificial intelligence by enabling autonomous planning, decision-making, and collaboration.

In this episode, we break down what AI agents are, why they matter beyond generative AI, how industries like healthcare, finance, and cybersecurity are using them today, and the risks, safety challenges, and governance frameworks shaping their future.

For more visit: https://techlifewell.com

#AgenticAI #MultiAgentSystems #AutonomousAI #AIagents #AIGovernance #AIethics #FutureOfAI #EnterpriseAI

On June 1, GitHub (owned by Microsoft) switched its billing system from a flat subscription rate to a token-usage system. I’ve described here before how my $39-per-month subscription provided a certain number of premium requests. I was working well within that tier, and in the past two weeks, my agentic workflow has been really smooth.

I didn’t do any development work yesterday, as I was building my band’s website, but today I dove back in. It was early afternoon when Copilot informed me that I had used 50% of my credits. What would usually last me about 15 days, I had burned through in less than one. I was aware that they were changing their billing model, but that was a shock.

I spent the rest of the afternoon overhauling my workflow to make it more efficient. By the end of my work day, I was at 71%. If I were to continue at that rate, what was costing me $39 will instead cost around $609. That’s a 15x increase.

I fully admit, I was part of the problem. Their original use case was a developer using AI as a coding assistant for code completion, writing a function, fixing a bug, or generating a component. I’ve created an entire product development platform with a multi-agent development loop involving a Planner, Architect, Designer, Builder, Reviewer, Backlog Manager, Tester, and DevOps Manager. I built out an entire design system while at the same time building two entire applications from scratch. I’m probably the exact person they are targeting.

On the other hand, they have encouraged this type of use, and now they’re pulling the rug out from under us. I’ve spent weeks building my workflow with the intention of using it for my future livelihood. But now, all of a sudden, what I’ve built is no longer sustainable.

I’m not the only one feeling the pain, as evidenced by recent tech news.

Technology is moving faster than ever before, and industries across the world are transforming the way they work. Businesses are now using Artificial Intelligence to automate tasks, improve productivity, create content, analyze data, and manage customer experiences. One of the biggest developments in this transformation is the rise of Generative AI and Agentic Workflows.

Students and professionals who fail to adapt to these technologies may struggle to stay competitive in future job markets. This is why choosing a Skill Development Institute in Kochi that focuses on modern technologies has become extremely important for career growth.

At Knovista, learners are introduced to industry-oriented training methods that help them understand emerging technologies and practical workflows required in modern workplaces.

Skill Development Institute in Kochi Explains the Rise of Generative AI

Generative AI is changing the way companies create and manage work. From content generation and coding assistance to automated design support and customer interaction systems, AI tools are becoming part of everyday business operations.

Many companies now expect employees to understand:

AI-assisted productivity tools

Automated content systems

AI-based customer support

Smart workflow management

Prompt engineering concepts

Data-driven decision-making

A modern Skill Development Institute in Kochi helps students understand how these technologies work in real-world environments instead of only teaching theoretical concepts.

At Knovista, learners are encouraged to understand practical AI applications that can improve efficiency, creativity, and professional performance.

Skill Development Institute in Kochi Helps Students Understand Agentic Workflows

Agentic workflows are becoming one of the most powerful concepts in modern AI systems. Instead of performing a single task, AI agents can now complete multi-step actions such as planning, researching, analyzing, generating reports, scheduling tasks, and assisting businesses with automation.

This means future professionals must learn how humans and AI systems work together efficiently.

A professional Skill Development Institute in Kochi can help students understand:

Workflow automation

AI task coordination

Smart business processes

Productivity optimization

AI-assisted collaboration

Real-time problem solving

These skills are becoming valuable across industries including software development, digital marketing, customer support, healthcare, education, finance, and e-commerce.

Why Generative AI Skills Matter for Future Careers

Companies are not only hiring people with academic qualifications anymore. They are searching for individuals who can adapt to technological changes and improve workplace productivity using modern tools.

Students with AI knowledge can explore opportunities in:

Digital Marketing

Software Development

UI/UX Design

Content Creation

Data Analysis

Business Automation

Customer Experience Management

Freelancing and Remote Work

Learning these technologies early can provide a strong advantage in future career growth.

Skill Development Institute in Kochi Creates Industry-Ready Professionals

Many students feel confused about where to start learning advanced technologies like AI and workflow automation. Without proper guidance, learning can become overwhelming.

At Knovista, the learning approach focuses on simplifying modern concepts and helping students understand how industries actually use technology. The training environment encourages practical exposure, project-based learning, and professional development.

Instead of limiting education to traditional classroom methods, Knovista supports learners in understanding modern workplace expectations and future industry trends.

Knovista Supports the Future of Learning

The future workplace will depend heavily on intelligent systems, automation, and AI-assisted decision-making. Professionals who understand Generative AI and Agentic Workflows will have stronger opportunities in both local and global industries.

Choosing the right Skill Development Institute in Kochi can help students build confidence, improve technical knowledge, and prepare for future careers shaped by Artificial Intelligence.

On Friday, I encountered a bug. Not in my code, mind you, but in the handshake between GitHub Copilot and Claude.

First of all, realize that Copilot is configured to use multiple LLMs.

The ones at the top of the list are the most recent models. The multipliers to the right are how much they each cost in relation to the baseline amount included in your subscription. Claude Opus is the most competent and the most expensive: 15x more expensive. GPT-4.1 is pretty basic and included for free in your plan, so you can use it as much as you want, even if you’ve used all of your credits for the month.

At the very top, you’ll see that “Auto” is selected at a 10% discount. When you set Copilot to auto, it chooses which model to use based on the type of request and its complexity. GitHub gives you a discount for using that option because it’s also best for the entire system. If everyone is burning Claude all the time, the system will be less efficient. It’s a win-win situation. You save money, and the workload going over the internet is balanced.

So, that bug I mentioned—every request that Copilot sent to Claude was failing. Worse, it was corrupting my session history, so there was no way to recover from the error. I’d just have to close the session and start a new one, losing recent context in the process. So, I worked with Copilot to troubleshoot the issue. We switched to different models, confirmed that it was an issue with Claude and likely to do with the Copilot update I had just run. Eventually, it gave me a command to run in Apple’s console after quitting out of VS Code, and that cleared things up.

After a relaxing weekend, I picked up Monday where I left off. I got a lot done on Tuesday and Wednesday, and one of the apps in particular was coming along swimmingly. Today was especially productive. Then, all of a sudden, a message popped up on my session, mid-run, saying that I had reached my premium request limit for the month.

How could that be? I had been tracking it, and I wasn’t going to have any problem staying within budget. I hadn’t checked it this week for that very reason. I checked my usage statistics.

Well, something obviously changed this week.

That screenshot of the model list up there is nice and big for you, but understand that the little Auto indicator there in the bottom bar of the window is tiny and surrounded by a lot of other UI cruft. Apparently, when I switched one of my sessions back to Auto, it didn’t take. It was stuck on Claude Opus. So, every request I made this week on that product was being directed to the most expensive model. No wonder that project was performing so well.

After a couple months of adding rules, gates, checks, and reports to my agentic workflow, it was becoming sluggish, and I felt like it was acting dumber. I had a feeling I had reached a point of process complexity that was doing more harm than good. I explained to my DevOps agent the symptoms I was seeing and my hypothesis and it agreed with me. It basically told me that the agents had become more focused on meeting the process requirements than doing the work.

That happens to human teams, too. It’s one of the things that always bugged me about Agile, especially SAFe. Teams get so hung up on the particulars of scrums and the responsibilities of each of the roles, they forget that it’s supposed to be in service to the work.

So, I told my agent to run an analysis of the workflow and propose some simplifications that won’t lose the essence of the guardrails we had put in place. It did that in part by introducing a complexity rating given to each task. For simple tasks, it can skip a lot of the checks and reports. The more complex tasks require more rigor. It also cleaned up a lot of repetition and some conflicting instructions—cruft that had built up through iterations.

If You Don’t Know Claude Code, You’re Already Behind Kim Jongwook · 2026-05-18 TL;DR Claude just passed OpenAI in paid enterprise AI adoption: 34% vs 32%. Claude’s share jumped from 8% to 34% in only 12 months. Claude Code and extended context windows are driving trust in complex workflows. Enterprise AI lock‑in makes today’s vendor choices structurally important, not cosmetic. Leaders must…