agentic ai
105 pieces on agentic ai, across articles, books, talks, and videos.
Presented at Green IO London 2026 on Green Agentic AI — embedding sustainability into the design and operation of AI agents, measuring their impact across carbon, energy and water, and building more resource-efficient intelligent systems.
As agentic AI evolves, the model is only one part of the system — the harness around it shapes how the agent behaves. If we engineer harnesses for reliability, security and autonomy, we should engineer them for resource use too. That is Sustainable Harness Engineering.
As AI moves from individual prompts to autonomous agents, the sustainability equation changes significantly. Speaking at Green IO London 2026 on Green Agentic AI: Optimizing Cost, Energy and Carbon.
I thought I was moving a website. I ended up reconsidering how knowledge should survive the next generation of the internet — why Markdown, Git, and deliberately boring architecture became a technical-debt strategy, and what twenty years of WordPress taught me about enterprise modernization.
The goal of AI should be to make the next problem easier, not the same problem more expensive. That idea became the foundation of my new book: Reusable Intelligence Beyond Inference: Building AI Systems That Learn When Not to Reason AI is becoming remarkably…
I’m looking forward to speaking at Green IO London 2026 on: Green Agentic AI: Optimizing Cost, Energy and Carbon Agentic AI can consume orders of magnitude more compute than a simple chat interaction. As agents reason, call tools, retrieve context, retry…
AI is getting remarkably good at reasoning — but why should a system keep paying to rediscover what it already knows? A handbook for building AI systems where intelligence accumulates: reuse the known, reason about the new, escalate the uncertain.
100 episodes. One evolving question: what does the future of intelligent systems really look like? When I started Agentic AI: The Future of Intelligent Systems, the conversation around AI was very different. We were focused on models, prompts and copilots.…
The internet taught companies to design information for humans. AI may force companies to redesign information for machines. For decades, the content pipeline was simple. A company created information. A human found it, read it, interpreted it and acted on…
Building a powerful AI model is one thing. Making an enterprise depend on it is another. AI research is moving fast, but enterprise delivery is not keeping pace. A model can look exceptional in a benchmark and still be difficult to deploy reliably across real…
The token economics model is not scalable. AI economics needs to change. Today, every time AI reasons, the meter runs. That is acceptable when the problem is new, uncertain or exceptional. But once the enterprise has already solved the problem, why should it…
Why are organizations paying AI to relearn what they already know? Much of enterprise AI today follows the same pattern: A transaction arrives. An LLM reasons. An outcome is produced. Then the next similar transaction arrives, and the LLM reasons all over…
AI is getting cheaper. But is it becoming more valuable? That question has been on my mind for some time. The AI industry has become exceptionally good at measuring consumption. We measure tokens, API calls, GPU hours, model prices, latency, infrastructure utilisation and…
Excited to announce my new book, AI Economics: Building and Scaling Intelligence. AI is getting cheaper, more capable and increasingly autonomous. But there is a question I believe matters far more: What value are we actually creating with all this…
AI can make your organization more intelligent while making it less knowledgeable. That sounds contradictory. But as AI starts doing more of the analysis, reasoning, and decision support, something subtle begins to shift: The capability remains. The…
Day 25 showed that the interface between a user and a model decides how much inference gets called. Today closes the arc at the newest interface in the stack — the one between agents — where fan-out, escalation, accumulated state, and loose contracts compound into a bill no single team owns end to end.
Day 25 of Green, Efficient AI is live: The Interface Sets the Bill. A user creates intent. The interface translates that intent into inference demand. The model produces the bill. Two products can wrap the same underlying model and produce inference bills…
Before we build the next AI data center, we should answer 8 questions. Not after construction. Not in the next sustainability report. Before the shovel goes into the ground. 1️⃣ How much water will it use — and from where? 2️⃣ How much electricity will it…
The token model doesn't tell us what AI accomplished. It tells us what AI consumed. Tokens. Compute. Inference. Context. But consumption isn't the same as value. An AI system can consume 100,000 tokens and still produce nothing useful. Another can consume…
What if AI is making you more capable—but not smarter? We’ve spent the last few years learning how to get AI to produce more. More code. More content. More analysis. More decisions. But there’s a question we’re not asking enough: Who owns the thinking? In the…
The Token Economy has an expiration date. Not because AI is slowing down. Because intelligence itself is becoming infrastructure. For the past three years, we've optimized prompts, tokens, latency, and inference costs. That's exactly what every technology…
From Zero Trust to Zero Assumption for Agentic AI systems. I believe this is the next evolution of enterprise security for Agentic AI. Zero Trust transformed security by ensuring that no identity is trusted by default. But autonomous AI systems introduce a…
Day 23 of Green, Efficient AI is live: The Model Keeps Its Environmental Receipts. Every model in production carries a receipt for what it cost to exist. Training was a paid event. The footprint closed the moment the run finished, and the model has been…
HR for AI Agents? It sounds unusual today. In a few years, it may become a standard enterprise function. As organizations deploy hundreds—or even thousands—of AI agents, managing them won't be just an engineering problem. It will become a management…
Day 22 of Green, Efficient AI is live: The Silicon in the Rack. A cloud-native platform team approved a hardware refresh. Newer accelerators. Better performance per watt. Clean operational case. The sustainability lead asked one question before signing off,…
49 new efficient skills for your AI agent. The kind that spot waste — before your cloud bill or carbon footprint does. The latest edition of Technology Bytes is live — and it comes with something you can actually use, starting today. Last article, I wrote…
AI Skill = Capability × Efficiency Today's AI agents are measured by what they can do. Can they search? Can they reason? Can they write code? Can they use tools? Can they collaborate with other agents? But as enterprises move from deploying a handful of…
Day 20 of Green, Efficient AI is live — The Capacity That Waits. A retail team ran per-call optimizations across their assistant for months. The bill barely moved. When they pulled utilization data across the full stack — model endpoints, vector database,…
Speaking at Google I/O on Lean Agentic AI: as organizations scale from a handful of agents to thousands, systems must be efficient by design — across cost, energy, and carbon. Slides and demo available on GitHub.
It was a pleasure speaking at the Google I/O event on Lean Agentic AI. As organizations move from deploying a handful of AI agents to thousands, efficiency can no longer be an afterthought. We need to design agentic systems that are efficient by design—across…
Tomorrow, I'll be speaking at Google I/O Connect, Bengaluru on a topic I've become deeply passionate about: Lean Agentic AI. We're entering an era where organizations will deploy not one or two agents—but thousands. The question is no longer: can we build…
🚨 AI is advancing faster than your organization can transform. That may be the single biggest reason why so many enterprises are struggling to demonstrate ROI from Agentic AI. Every month, we see smarter models, better reasoning, lower costs, and more capable…
Day 19 of Green, Efficient AI is live — The Test Tail. A team spent six months bringing production AI costs down. The playbook worked — production inference became dramatically cheaper. The monthly bill barely moved. The gap was hiding in plain sight. Every…
AI doesn't need another breakthrough model. It needs a return to engineering fundamentals. Somewhere between foundation models and agentic AI, we started confusing capability with architecture. Bigger models, more agents, longer context windows, and…
Day 17 of Green, Efficient AI is live — The Invisible Payload. A user asks a support agent to reset their password — seven words, roughly ten tokens. The trace shows the model actually receives thousands of tokens. A system prompt written months ago. Every…
Day 16 of Green, Efficient AI is live — Every Guardrail Is a Call. The most overlooked line item in an AI system is the safety wrap. So why do most teams run four or five model-based checks on every request without ever costing them? In many production…
The future of enterprise AI is not about maximizing intelligence. It is about delivering the minimum intelligence required to achieve the maximum business outcome. This idea has increasingly shaped how I think about the next phase of enterprise AI. Over the…
A session at the Green Software Development Karlsruhe meetup on connecting Software Carbon Intensity (SCI) to agentic systems — why cost, energy, and carbon are deeply connected but not the same thing, and how to start measuring.
Day 14 of Green, Efficient AI is live — The Grid You Didn't Choose. Most production AI runs in a region somebody picked years ago, on hardware procured for a different workload, and on schedules chosen for operational convenience rather than carbon…
Day 12 of Green, Efficient AI is live — Cache What Doesn't Change. Depending on the workload, forty to ninety-five percent of every AI prompt is the same as the last one — the system prompt, the tools, the document the agent is reading. The model reprocesses…
Day 11 of Green, Efficient AI is live — Reset the Loop When Context Decays. An agent runs for fifteen turns. Each turn costs more than the one before it. By the last few turns, a single turn can cost more than the first several combined. The questions did not…
Day 10 of Green, Efficient AI is live — Close the Loop with the Right Tool. Two agents, same customer question: "What's the status of my last order, and when will it arrive? Agent A has four clean tools — look up the customer, list orders, fetch shipping,…
🚨 The Token Shock — Why Companies Are Running Out of AI Budget 🎙️ Episode 91 of Agentic AI: The Future of Intelligent Systems is out now. Are we creating value… or simply generating activity? That may quietly become one of the biggest questions organizations…
Wait… the AI budget is already gone? This is becoming a real conversation inside organizations. Coding assistants. Meeting summaries. Research agents. Copilots. Multi-agent workflows. AI feels effortless… until someone sees the token bill. In early 2025, I…
Most people know AI consumes electricity. But very few realize that AI may also have a water story. As Agentic AI evolves from answering questions to reasoning, planning, coordinating tools, and acting autonomously, an important question quietly emerges: What…
What if the future of AI becomes too expensive to sustain? Not because models are costly. But because intelligence itself becomes something we consume continuously. We are moving toward a world where AI systems won’t just answer questions. They will quietly…
Technology Bytes NewsLetter has crossed 5000+ subscribers. Thank you for being part of this journey—your engagement, shares, and conversations are what make this community meaningful. In the latest edition of Technology Bytes, I explore a shift that is…
This software was developed by AI. A newer, more powerful version of that AI has now taken over. No problem,” they say. “We have all the history. Code. Logs. Decisions. Data. Everything is fed into the new AI. It understands everything. Almost. Except why the…
I have open-sourced Lean Agentic AI as Claude Skills. Agentic systems are rapidly becoming the new application architecture. They are more capable than ever.But capability without discipline leads to waste — unnecessary compute, unchecked cost, and unmeasured…
Enterprise Agentic AI is not a model play. It is engineered autonomy. As model capabilities accelerate — larger context windows, stronger reasoning, embedded coding agents, automated security scans — the industry conversation continues to focus on performance…
Every technology wave expands before it refines. Agentic AI will be no different. Cloud expanded before it matured. Microservices scaled before governance caught up. Data lakes grew before lifecycle control became necessary. Agentic AI is now in that…
As India’s AI Impact Summit 2026 reflects the scale of ambition shaping our AI journey, it also presents an opportunity to consider a structural question: How do we scale AI without proportionally scaling cost, carbon, and complexity? In the latest edition of…
If you’re overseeing an Agentic AI roadmap, these ten principles can save cost, carbon, and complexity. In the race to deploy autonomous agents, many organizations are quietly accumulating Agentic Debt — systems that are over-orchestrated, expensive to run,…
As personal AI assistants move beyond request–response interaction and begin operating across inboxes, calendars, files, and external services—often through familiar chat interfaces—they naturally start to form networks of activity. One agent triggers…
💡 Blaming AI for Layoffs Misses the Bigger Problem AI influences layoffs — but it doesn’t define them. AI didn’t take those jobs. Inefficiency did. It’s easy to point fingers at technology — to say AI replaced people. But the truth is far more complex: most…
The Three Levels of Vibe Coding Vibe coding” is the new frontier of AI-assisted development — where you describe what you want, and the model writes the code. It feels effortless. Instant. Almost creative. But like all shortcuts, it has layers — and limits.…
Long before algorithms could recognize text or predict outcomes, humans learned to recognize something far more abstract — patterns in the cosmos. We looked up at the night sky and began connecting stars into constellations, linking the movements of the sun and moon to seasons,…
There’s a bold narrative sweeping through the software industry: AI coding assistants will redefine engineering. We’ve all seen the headlines — “All code will soon be AI-generated,” “Developers 10× more productive,” “AI writing most of our applications.” The promise is…
The biggest myth in AI today? That tools like LLMs, CoPilots, MCPs, and Agents will do the engineering for you. They won’t — because AI is engineering. LLMs. MCP. Agents. They’re all just that — tools. Yet many organizations are spending an extraordinary…
Copilots are like humans. First, they invent a problem. Then, they proudly solve it. In practice, that means copilots can generate complexity that wasn’t there before. They might over-engineer a simple task, suggest unnecessary fixes, or loop through steps…
🚀 Agentic AI is 90% Engineering Building agentic systems is not just about prompts and orchestration. It’s engineering. In fact, Agentic AI is ninety percent engineering. Think about what makes an agent work in the real world: -> Planning: Beyond breaking…
🧭 Still searching for your place in the age of AI? This isn’t just about learning new tools. It’s about unlearning old habits. As AI transforms how software is designed, built, and maintained — engineers face a new challenge: How do you lead, adapt, and stay…
🤖💳 What if your AI agent could walk into the marketplace, bargain like a pro, and pay instantly on your behalf—all while following the exact rules you set? That’s the future Agentic Commerce promises, and Google’s newly announced Agent Payments Protocol (AP2)…
🌍 The Hidden Cost of AI at Scale: It's Time for a Sustainable AI Playbook Most reports focus on the cost of a single prompt in terms of energy — but that misses the bigger picture. The real challenge? Billions of prompts running daily. Multi-agent workflows…
⚠️ While LLM providers keep increasing context window sizes, designing for long context windows isn’t the right approach. Here’s why: 🔹 Inefficiency at Scale Bigger windows mean more tokens per request. That adds overhead without delivering proportional gains…
The true test of Agentic AI isn’t how much it can do — it’s how efficiently, responsibly, and sustainably it can do it. 🎙️ Tune in to my latest episode of Agentic AI: The Future of Intelligent Systems — “Designing Lean Agentic AI: Principles for Sustainable…
If the internet transformed how businesses connect, AI agents will transform how businesses think. Nobody talks about internet protocols or servers anymore. We just use them—silently powering how every business runs. That’s where AI agents are heading.…
Agentic AI is moving fast, with new frameworks, orchestration models, and multi-agent workflows appearing every month. Organizations that rely only on off-the-shelf setups risk locking into vendor-driven decisions that may not fit their cost, carbon,…
I’m making the Lean Agentic AI repository available to help teams design agentic systems that are efficient, sustainable, and scalable from day one. Agentic AI has massive potential — but without a lean approach, it can quickly spiral into runaway cost,…
🚦 When GPT-5 Felt “Dumber” — The Hidden Risks of Model Routing A single “autoswitcher” glitch recently made GPT-5 behave differently. It wasn’t just a tech hiccup — it exposed something deeper about how AI systems decide which model answers you. In the latest…
🚀 Just ran OpenAI’s new GPT‑OSS 20B model locally on my Mac M-series — and it worked seamlessly. No GPUs. No cloud setup. No latency. Just one line to get started: ollama run gpt-oss:20b 🧠 For context — GPT‑OSS is OpenAI’s first open-weight model release…
When advancing Agentic AI systems from prototype to production, these three operational realities define the boundary between experimentation and enterprise-scale impact: ❗ COST – Every prompt, tool invocation, and memory update consumes tokens—and dollars. 🌍…
Mistral just published one of the most detailed environmental lifecycle assessments for a large language model. Their report on Mistral Large 2 transparently covers emissions, water usage, and resource depletion across training, inference, and hardware…
Tokens are the new compute currency. They seem cheap—fractions of a cent, a flicker of GPU time. But scale them across agents, retries, and escalations, and they explode into massive financial and environmental burdens. 💰 Pricing Reality (OpenAI API): GPT-4o…
Vibe coding needs a VIBE mindset—Validated, Integrated, Balanced, Effective. In an era of fast AI-powered development, vibe coding feels great: fast starts, fluid ideation, and instant results. But here’s what I’ve learned after evaluating top AI models for…
LangChain recently published a helpful step-by-step guide on building AI agents. 🔗 How to Build an Agent – It covers key phases: 1. Defining realistic tasks 2. Documenting a standard operating procedure 3. Building an MVP with prompt engineering 4. Connect &…
When software begins to think, plan, and act, how do humans stay ahead? Today, we mark 50 episodes of Agentic AI: The Future of Intelligent Systems, reflecting deeply on our relationship with software that no longer just computes but genuinely thinks. From…
In the Agentic era, choosing how to think is as important as what to think. Agentic AI systems don’t just act—they reason. But not all reasoning is created equal—and getting it wrong can waste both cost and carbon. Here’s a simple framework for reasoning…
Most Agentic AI conversations are missing a key dimension: cost, carbon, and complexity. While the spotlight is often on autonomy, orchestration, and innovation, the reality is that Agentic AI systems—if not designed intentionally—carry hidden risks that quietly erode value: ❗…
Most Agentic AI conversations are missing a key dimension: cost, carbon, and complexity. While the spotlight is often on autonomy, orchestration, and innovation, the reality is that Agentic AI systems—if not designed intentionally—carry hidden risks that…
AI cost estimates can be off by 500–1,000% as per Gartner.Recent FinOps Foundation data shows 63% of organizations now actively manage AI spend—double last year—showing cost control is now mission critical. Agentic AI enables transformative automation, but…
The command line is the backbone of productivity for many developers, data professionals, and content creators. Yet with growing volumes of files, drafts, and project assets, even the most organized users face content chaos — duplicate files, forgotten revisions, and manual…
🚀 New White Paper: Building Production-Ready Agentic AI applications with Cost, Carbon, and Conscience in Mind AI agents shouldn’t just work—they should scale responsibly, remain auditable, and respect real-world limits. This white paper introduces a 10-step…
Code migration is no longer a manual, one-off effort. With agentic AI frameworks like CrewAI, Google ADK, and LLM-powered tools, we can now design multi-agent systems that analyze legacy code, detect compatibility issues, recommend modern syntax, and even…
🚀 Engineering with the New AI: Copilots, Agents, and the Human Orchestration. AI is no longer a silent assistant working behind the scenes. Today, it’s embedded in every phase of engineering—design, coding, deployment, and even documentation. From copilots…
🚀 What if your stock portfolio could analyze itself? I've published an experimental project that automates investment portfolio analysis by connecting three powerful technologies: Zerodha KITE MCP, CrewAI, and Large Language Models. The open-source repository…
In the era of AI, engineering isn’t about stepping back—it’s about stepping up to new responsibility. To remain relevant and drive real impact, the skills that matter most aren’t about writing every line of code, but about mastering the art of…
We are living through the most transformative era in engineering history. Artificial intelligence—once the domain of research labs and specialized applications—now sits at the core of how systems, products, and organizations are built and operated. For engineers, this brings…
Modern financial analysis is rapidly moving toward automation and agentic workflows. Integrating large language models (LLMs) with real-time financial data unlocks not just powerful insights but also entirely new ways of interacting with portfolio data. This post walks through a…
What if the future of work isn’t about humans versus AI—but about humans moving up the stack? The newest edition of Technology Bytes explores the eight-layer Human Stack, redefining how people interface with, augment, and elevate intelligent systems. Discover…
🧠 Can Co-Pilots Truly Learn New APIs on the Fly? AI coding assistants—or “Co-Pilots”—have become powerful accelerators for development. But here’s a real-world challenge many developers are now facing: 👉 Ask them to write code using a newly released API or…
As Agentic AI transitions from labs to live environments, it brings not just promise—but unprecedented complexity. These aren’t just programs; they’re systems that plan, decide, and act autonomously. This shift calls for a new design imperative: security by…
Agentic AI is shifting from proof-of-concept to strategic capability. But for it to be enterprise-ready, it must evolve—fast. It’s no longer enough for agents to plan, reason, and act. Enterprises demand systems that are secure, efficient, observable, and…
Lean Agentic AI Principles – Minimize Cost • Carbon • Complexity Build AI that’s lean by design, not bloated by default. Agentic AI unlocks powerful capabilities—but without the right principles, it can become expensive, inefficient, and hard to scale. This…
Lean Agentic AI Principles – Minimize Cost • Carbon • Complexity Build AI that’s lean by design, not bloated by default. Agentic AI unlocks powerful capabilities—but without the right principles, it can become expensive, inefficient, and hard to scale. This…
Excited to share the release of my latest book – Lean Agentic AI: Minimizing Cost, Carbon, and Complexity 📘 I've written several tech books over the last two decades—but this one is different. It’s not just another AI book. It’s a mindset shift. The first to…
🧠 Most agentic AI systems today are overthinking, overspending, and overconsuming—on autopilot. This edition uncovers why smarter agents don’t mean bigger models or longer memory. In fact, that mindset may be the trap. Lean is not less. Lean is what makes…
AI agentic frameworks provide the infrastructure for building autonomous AI agents that can perceive, reason, and act to achieve goals. With the rapid growth of large language models (LLMs), these frameworks extend LLMs with orchestration, planning, memory, and tool-use…
🔍 What’s often missing in our AI conversations? 🚀 New LLMs are outperforming previous generations — with better accuracy, faster inference, and richer capabilities. 🧠 New AGENT FRAMEWORKS are emerging — enabling planning, memory, and autonomous execution. 📡…
🚀 From Zero to AI-Powered: Master Generative AI & Prompt Engineering! 🚀 AI is everywhere—but where do you start? This beginner-friendly course makes AI simple, practical, effective and productive for everyone. Whether you're new to AI, a business…
Organizations truly committed to responsible practices transcend regulations and global frameworks. They embed sustainability, ethics, and social responsibility into the core of their strategic operations. Relying solely on regulations to drive responsible…
LLM Agents Explained: Get the key concepts and frameworks in this concise summary. Download it. I’ve created a short summary covering: ✅ Core concepts and reasoning techniques ✅ Key agent frameworks like LangChain, Auto-GPT, and BabyAGI ✅ Real-world…
The evolution of programming is here—AI is no longer just a tool, it’s the new compiler. Instead of writing every line of code, developers are now guiding, refining, and orchestrating AI-driven solutions. 🔹 Prompt Engineering is abstracting coding itself—just…
As we welcome 2025, I’m thrilled to introduce my latest book, which reflects my vision for the future of AI—where systems go beyond automation to adapt dynamically, make informed decisions, and align with purpose and sustainability. This book address a critical gap: the lack of…
🎉 Happy New Year! 🌟 Excited to Announce My New Book: Empowering Leaders with Cognitive Frameworks for Agentic AI: From Strategy to Purposeful Implementation 📘 As we welcome 2025, I’m thrilled to introduce my latest book, which reflects my vision for the…