Ajitabh Pandey's Soul & Syntax

Exploring systems, souls, and stories – one post at a time

Author: Ajitabh

  • Rethinking Resilience in the Age of Agentic AI

    A short while back, I wrote a series on Resilience, focusing on why automated recovery isn’t optional anymore. (If you missed the first post, you can find it here: [The Unseen Heroes: Why Automated System Recovery Isn’t Optional Anymore]).

    The argument that human speed cannot match machine speed, is now facing its ultimate test. We are witnessing the rise of Agentic AI. Agentic AI is a new class of autonomous attacker operating at light speed, capable of learning, adapting, and executing a complete breach before human teams even fully wake up.

    This evolution demands more than recovery; it requires an ironclad strategy for automated, complete infrastructure rebuild.

    Autonomy That Learns and Adapts

    For years, the threat landscape escalated from small hacking groups to the proliferation of the Ransomware-as-a-Service (RaaS) model. RaaS democratized cybercrime, allowing moderately skilled criminals to rent sophisticated tools on the dark web for a subscription fee (learn more about the RaaS model here: What is Ransomware-as-a-Service (RaaS)?).

    The emergence of Agentic AI is the next fundamental leap.

    Unlike Generative AI, which simply assists with tasks, Agentic AI is proactive, autonomous, and adaptive. These AI agents don’t follow preprogrammed scripts; they learn on the fly, tailoring their attack strategies to the specific environment they encounter.

    For criminals, Agentic AI is a powerful tool because it drastically lowers the barrier to entry for sophisticated attacks. By automating complex tasks like reconnaissance and tailored phishing, these systems can orchestrate campaigns faster and more affordably than hiring large teams of human hackers, ultimately making cybercrime more accessible and attractive (Source: UC Berkeley CLTC)

    Agentic ransomware represents a collection of bots that execute every step of a successful attack faster and better than human operators. The implications for recovery are profound: you are no longer fighting a team of humans, but an army of autonomous systems.

    The Warning Signs Are Already Here

    Recent high-profile incidents illustrate that no industry is safe, and the time-to-breach window is shrinking:

    • Change Healthcare (Early 2024): This major incident demonstrated how a single point of failure can catastrophically disrupt the U.S. healthcare system, underscoring the severity of supply-chain attacks (Read incident details here).
    • Snowflake & Ticketmaster (Mid-2024): A sophisticated attack that exploited stolen credentials to compromise cloud environments, leading to massive data theft and proving that third-party cloud services are not magically resilient on their own (Learn more about the Snowflake/Ticketmaster breach).
    • The Rise of Non-Human Identity (NHI) Exploitation (2025): Security experts warn that 2025 is seeing a surge in attacks exploiting Non-Human Identities (API keys, service accounts). These high-privilege credentials, often poorly managed, are prime targets for autonomous AI agents seeking to move laterally without detection (Read more on 2025 NHI risks).

    The Myth of Readiness in a Machine-Speed World

    When faced with an attacker operating at machine velocity, relying solely on prevention-focused security creates a fragile barrier.

    So, why do well-funded organizations still struggle? In many cases, the root cause lies within. Organizations are undermined by a series of internal fractures:

    Siloed Teams and Fragmented Processes

    When cybersecurity, cloud operations, application development and business-continuity teams function in isolation, vital information becomes trapped inside departmental silos, knowledge of application dependencies, network configurations or privileged credentials may live only in one team or one tool. Here are some examples –

    • Cisco Systems’s white-paper shows how siloed NetOps and SecOps teams lead to delayed detection and containment of vulnerability-events, undermining resilience.
    • An industry article highlights that when delivering a cloud-based service like Microsoft Teams, issues spread across device, network, security, service-owner and third-party teams—and when each team only worries about “is this our problem?” the root-cause is delayed.

    Organizations must now –

    • Integrate cross-functional teams and ensure shared ownership of outcomes.
    • Map and document critical dependencies across teams (apps, networks, credentials).
    • Use joint tools and run-books so knowledge isn’t locked in one group.

    Runbooks That Are Theoretical, Not Executable

    Policies and operational run-books often exist only in Wiki or Confluence pages. These are usually never tested end-to-end for a real-world crisis. When a disruption hits, these “prepare-on-paper” plans prove next-to-useless because they haven’t been executed, updated or validated in context. Some of the examples to illustrate this are –

    • A study on cloud migration failures emphasises that most issues aren’t purely technical, but stem from poor process, obscure roles and un-tested plans.
    • In the context of cloud migrations, the guidance “Top 10 Unexpected Cloud Migration Challenges” emphasises that post-migration testing and refinement are often skipped. This means that even when systems are live, recovery paths may not exist.

    The path forward lies in to –

    • Validate and rehears e run-books using realistic simulations, not just table-top reviews.
    • Ensure that documentation is maintained in a form that can be executed (scripts, automation, playbooks) not just “slides”.
    • Assign clear roles, triggers and escalation paths—every participant must know when and how they act.

    Over-Reliance on Cloud Migration as a Guarantee of Resilience

    Many organisations assume that migrating to the cloud automatically improves resilience. In reality, cloud migration only shifts the complexity: without fully validated rebuild paths, end-to-end environment re-provisioning and regular recovery testing, cloud-based systems can still fail under crisis.

    Real-world examples brings this challenge into focus –

    • A recent issue reported by Amazon Web Services (AWS) showed thousands of organisations facing outage due to a DNS error, reminding us that even “trusted” cloud platforms aren’t immune—and simply “being in the cloud” doesn’t equal resilience.
    • Research shows that “1 in 3 enterprise cloud migrations fail” to meet schedule or budget expectations, partly because of weak understanding of dependencies and recovery requirements.

    These underscores the importance to –

    • Treat cloud migration as an opportunity to rebuild resiliency, not assume it comes for free.
    • Map and test full application environment re-builds (resources, identities, configurations) under worst-case conditions.
    • Conduct regular fail-over and rebuild drills; validate that recovery is end-to-end and not just infrastructure-level.

    The risk is simple: The very worst time to discover a missing configuration file or an undocumented dependency is during your first attempt at a crisis rebuild.

    Building Back at Machine Speed

    The implications of Agentic AI are clear: you must be able to restore your entire infrastructure to a clean point-in-time state faster than the attacker can cause irreparable damage. The goal is no longer recovery (restoring data to an existing system), but a complete, automated rebuild.

    This capability rests on three pillars:

    1. Comprehensive Metadata Capture: Rebuilding requires capturing all relevant metadata—not just application data, but the configurations, Identity and Access Management (IAM) policies, networking topologies, resource dependencies, and API endpoints. This is the complete blueprint of your operational state.
    2. Infrastructure as Code (IaC): The rebuild process must be entirely code-driven. This means integrating previously manual or fragmented recovery steps into verifiable, executable code. IaC ensures that the environment is built back exactly as intended, eliminating human error.
    3. Automated Orchestration and Verification: This pillar ties the first two together. The rebuild cannot be a set of sequential manual scripts; it must be a single, automated pipeline that executes the IaC, restores the data/metadata, and verifies the new environment against a known good state before handing control back to the business. This orchestration ensures the rapid, clean point-in-time restoration required.

    By making your infrastructure definition and its restoration process code, you match the speed of the attack with the speed of your defense.

    Resilience at the Speed of Code

    Automating the full rebuild process transforms disaster recovery testing from an expensive chore into a strategic tool for cost optimization and continuous validation.

    Traditional disaster recovery tests are disruptive, costly, and prone to human error. When the rebuild is fully automated:

    • Validated Resilience: Testing can be executed frequently—even daily—without human intervention, providing continuous, high-confidence validation that your environment can be restored to a secure state.
    • Cost Efficiency: Regular automated rebuilds act as an audit tool. If the rebuild process reveals that your production environment only requires 70% of the currently provisioned resources to run effectively, you gain immediate, actionable insight for reducing infrastructure costs.
    • Simplicity and Consistency: Automated orchestration replaces complex, documented steps with verifiable, repeatable code, lowering operational complexity and the reliance on individual expertise during a high-pressure incident.

    Agentic AI has closed the window for slow, manual response. Resilience now means embracing the speed of code—making your restoration capability as fast, autonomous, and adaptive as the threat itself.

  • The AI Gold Rush: Why Narrow Intelligence Will Generate Trillions

    There’s no doubt that Artificial Intelligence (AI) is the technology of our time, promising to reshape industries and create unprecedented economic value. But beneath the headlines and hype, what exactly is driving this revolution, and where is the estimated $13 to $22 trillion in annual value going to come from by 2033?

    The source for this valuation is a landmark 2018 report from the McKinsey Global Institute (MGI) on the impact of AI on the world economy. You can find the full details of this modeling here: Notes from the AI frontier: Modeling the impact of AI on the world economy.

    The answer requires demystifying AI and understanding its three core ideas.

    The Three Faces of AI

    The term “AI” can be confusing because it refers to three distinct concepts:

    Artificial Narrow Intelligence (ANI)

    Artificial Narrow Intelligence (ANI) is the powerhouse driving the vast majority of AI value creation today. Unlike the broader, theoretical concept of human-level AI, ANI refers specifically to focused AI systems designed to master one specific task incredibly well. These systems are essentially “one-trick ponies,” but when the trick is appropriately chosen, the resulting impact is transformative and lucrative. Common examples include –

    • the spam filters that protect your inbox
    • the algorithms that power object detection in self-driving cars
    • the smart speakers that recognize your wake word, and
    • the automated visual inspection systems used in manufacturing to spot tiny defects in products coming off the assembly line.

    This high-impact, focused nature is why studies, such as those by the McKinsey Global Institute, consistently suggest that the largest portion of the projected multi-trillion dollar future value of AI will be unlocked through these narrow, yet highly optimized, applications, frequently relying on the machine learning technique known as Supervised Learning.

    Generative AI (GenAI)

    Generative AI, or GenAI, is absolutely the newest superstar in the tech world. This kind of AI has rapidly become famous because it can produce amazing, high-quality content—things like coherent text, realistic images, and even audio. It’s fundamentally expanded what we thought AI could do. For instance, tools like ChatGPT aren’t just single-task programs; they can jump between being a helpful copy editor, a creative brainstorming partner, or a concise text summarizer all in one go. Even though GenAI grabs a lot of headlines, it’s expected to account for a smaller, but still massive, slice of the total economic pie, we’re talking about $4 trillion annually. Its success is blurring the lines, making it seem like the previously narrow AI (ANI) can now handle much more general-purpose tasks.

    Artificial General Intelligence (AGI)

    Artificial General Intelligence, or AGI, is the stuff of science fiction. It’s the big dream: creating an AI smart enough to handle any intellectual task a person can do, maybe even becoming super-intelligent, capable of far more than any human. But here’s the reality check: we are still very far away from achieving AGI. The recent exciting and valuable steps we’ve made with narrow AI (ANI) and generative AI (GenAI) are impressive, sure, yet they often trick people into thinking AGI is right around the corner. Instead, it’s better to think of our current progress as tiny, promising baby steps leading toward what is still a distant, long-term goal.

    Beyond Software: Where AI Will Strike Next

    AI has definitely already created tremendous value in the world of software. But we must understand that the biggest future opportunities, the most exciting part actually lie outside of the tech sector itself. We’re talking about massive transformation coming to industries like retail, travel, transportation, manufacturing, and the automotive sector. Seriously, it’s really hard to name one single industry that won’t be hugely impacted by this technology in the next few years. The real trick, the big challenge for companies that don’t build software, is figuring out exactly which specific, narrow “tricks” those powerful, focused AI applications (ANI) can use to unlock this huge, multi-trillion dollar potential right within their own daily operations.

  • Book Review: Midnight Black (Gray Man #14)

    Version 1.0.0

    Midnight Black is another fast-paced and gripping entry in Mark Greaney’s Gray Man series. This time, Court Gentry (the Gray Man) takes on one of his most personal and dangerous missions yet. His objective is not a contract or a target, but a rescue. Zoya Zakharova, his partner and former Russian spy, has been captured and thrown into a brutal prison camp deep inside Russia. Refusing to believe she’s lost forever, Gentry embarks on a desperate mission to bring her back, no matter the cost.

    The pacing is fierce right from the start. The book portrays a strong emotional drive in the Gray Man, which was never seen in any of the previous books in the series. For the first time in 14 books of the series so far, the readers (and followers of the series) see a personal side of him and he appears truly human.

    The book leans heavily toward action and military-style missions rather than subtle spy craft.

    The narration by Jay Snyder deserves special mention. His delivery once again elevates the story to another level. The pacing of his narration perfectly matches the tension and rhythm of Greaney’s writing, and his voice modulation brings each scene and character to life. Snyder has become inseparable from the Gray Man series, and his performance here is among his best.

    Midnight Black is pure adrenaline with heart — a mix of non-stop action, emotional stakes, and high-end espionage. It’s a story about loyalty and love set against the backdrop of danger and impossible odds. I was not disappointed, and I can definitely say the series’s fans will not be either. New readers will find it a thrilling introduction to one of the best modern spy thrillers.

  • Book Review: Artillery’s Thunder – The Untold Kargil Story by Maj Gen (Retd) Lakhwinder Singh

    From Kargil’s peaks to today’s fragile LoC, this book reminds us that the echoes of 1999 still shape India’s military conscience.”

    Few books pierce the surface of India’s modern military history with the clarity and courage that Artillery’s Thunder does. Written by Major General (Retd) Lakhwinder Singh, this is not another sanitized retelling of the 1999 Kargil War—it is a ground-up reconstruction of how India’s artillery turned the tide when confusion, unpreparedness, and political hesitation loomed large.

    From the very first pages, Singh pulls readers into the raw tempo of Operation Vijay. He paints the early chaos with startling honesty: intelligence lapses, senior commanders underestimating a well-entrenched enemy, and a rush to attack without adequate reconnaissance. The Indian Air Force’s initial unpreparedness for high-altitude combat adds to the realism of his account, yet he’s quick to acknowledge their exceptional logistical support that kept operations alive.

    Where this book truly thunders is in its portrayal of the artillery corps. Singh’s descriptions of coordinated barrages by Bofors FH-77Bs roaring day and night, precisely synchronizing with ground advances reveal how artillery became the silent architect of victory. He doesn’t hesitate to critique the post-war glorification imbalance: renaming Gun Hill to Batra Top symbolizes, in his view, how institutional bias often eclipses artillery’s contributions.

    The political backdrop runs as a constant undercurrent, Singh sharply critiques the restrictions imposed for optics, such as the “no crossing LoC” rule, even as the enemy violated it. His tone remains patriotic, but it’s the patriotism of someone who has seen both the brilliance and the blunders of war up close.

    Artillery’s Thunder is not merely a military memoir, it’s a mirror held up to India’s defense establishment, urging introspection and readiness. The book closes on a haunting note: that the echoes of Kargil are far from silent, especially in the light of recent events like the Pahalgam attack and Operation Sindoor.

    In the end, this is both a tribute and a warning. It celebrates the men behind the guns as much as it cautions against complacency.

    Highly recommended for defense enthusiasts, policy thinkers, and anyone who seeks the unfiltered truth of India’s most hard-fought modern war.

  • Book Review: The Gotland Deception by James Rosone and Miranda Watson

    James Rosone and Miranda Watson’s The Gotland Deception arrives with the promise of a gripping military technothriller, setting the stage for a new global conflict in the 2030s. The book’s premise seems very compelling.

    I found that roughly 85% of the book is devoted to comprehensive world-building. This includes deep dives into family life, military exercises, spy infiltration plots, and incredibly detailed descriptions of autonomous systems and advanced equipment. While some foundational work is crucial in launching a new series, this extensive setup significantly slows the narrative pace.

    It’s clear the authors are meticulously establishing the stakes and the technology of this near-future world. They detail the “frontlines to a proxy war” across locations like Angola, Svalbard, and Taiwan, painting a plausible, if chilling, picture of how a new World War III could quietly begin.

    The good news? The meticulous setup pays off—eventually.

    The real, explosive action only kicks in during the final chapters. When it does, the pace accelerates dramatically, delivering the kind of fast-paced, engaging military action fans of Rosone’s The Monroe Doctrine series expect. That late surge of adrenaline and thrilling potential is what truly saves the book.

    I’m rating The Gotland Deception three stars, largely on the strength of that ending. It’s an undeniable hint that the sequels, built on the solid, albeit dense, foundation of this first installment, could very well deliver a continuous, gripping thriller experience. It’s a slow burn that promises much for the series to come. Readers with patience will be rewarded by a thrilling finale and an exciting glimpse into a potential future military conflict.