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Unleashing the Power of Autonomous AI in Everyday Life
Hi! My name is Igvir, I'm a Computer Science Engineer, I´ll be here "Printing My Working Directory" That's where the name $PWD comes from. Updates, Articles, and Personal Insights about what I´m doing.
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Te cuento sobre mi libro sobre spec-driven-development con Kiro.
A series on AI-DLC, the methodology for AI-driven software development. Drawing from three workshops as a certified practitioner — what compresses, what breaks, and what changes about the developer's job. This is post three of three.
This is the second post in a three-part series on AI-DLC. The first post covered what I saw running three AI-DLC workshops. This one is about the problem AI-DLC tries to solve. The third will get into
Software teams have been promised compression for thirty years. Faster sprints. Better tooling. Lower ceremony. The methodology layer keeps getting renamed and the actual delivery curve barely moves.
Yes, we're already flooded with coding assistants that promise to accelerate development. I myself have been writing extensively on LinkedIn with the results of my research. But I can't ignore the fact that IBM has introduced Project Bob, a tool I ha...
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This is PWD, Print Working Directory, It shows you the complete path of the technology we are currently working in. Check my website https://www.igvir.com/
AI is getting smarter, and Agentic AI is the next big leap. Unlike traditional AI, which waits for commands, Agentic AI acts on its own. It sets goals, makes decisions, and adapts in real-time—like a digital assistant that actually thinks for itself.
Incorporating agentic AI into organizational workflows offers significant benefits, including enhanced operational efficiency, innovation, and improved decision-making. For instance, in supply chain management, agentic AI can predict potential disruptions and proactively recommend solutions to maintain continuity. In customer service, autonomous agents can handle complex support tickets from start to finish, improving response times and service quality. Moreover, by automating routine tasks, employees can focus on creative and strategic responsibilities, enhancing job satisfaction and overall productivity.
Agentic AI systems think more logically, making them less likely to generate false or misleading information (hallucinations) like generative AI often does. They can also evaluate sources more effectively, ensuring higher-quality and more trustworthy decisions. For example, if customer data is spread across emails, databases, and spreadsheets, an agentic AI can identify the most reliable source—such as the company’s CRM system. Additionally, these systems quickly learn a company’s values and brand principles, helping ensure their decisions align with business goals.
Challenges Ahead
Agentic AI has great potential to improve teamwork and business growth, but it’s still in early development. While it enhances reasoning and execution, it doesn’t eliminate workforce management challenges—it changes them. Managers still need to focus on team roles, set clear goals, and decide when AI should make decisions versus when humans should step in.
Works Independently – No constant human input is needed.
Learns & Adapts – Improves by analyzing its environment.
Takes Initiative – Anticipates needs before being asked.
Handles Complex Tasks – Breaks down big problems into steps.
Interacts Effectively – Communicates with people and other AI systems.
Agentic AI follows a four-step process:
Observes: Gathers data from its surroundings.
Decides: Uses AI models to choose the best action.
Acts: Executes tasks automatically.
Learns: Evaluates results and improves over time.
Agentic AI is already transforming industries:
Customer Support: AI chatbots that fully resolve customer issues.
Finance: Smart trading systems that analyze markets and act fast.
Healthcare: AI diagnosing patients and suggesting treatments.
Logistics: Managing supply chains and preventing delays.
As exciting as Agentic AI is, it comes with challenges:
Ethical Concerns: AI must make fair, unbiased decisions.
Security Risks: Preventing misuse or errors.
Human-AI Balance: Finding the right mix of automation and oversight.
Bernard Marr gives a detailed explanation in his video, you might find it helpful:
Agentic AI is changing the game, making AI more independent and proactive. From improving customer service to managing logistics, its potential is huge. The key is to develop it responsibly and ensure it works with humans, not against them.
The future of AI isn’t just smart—it’s agentic. And it’s already here. Are you ready?
