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Showing posts from January, 2026

Agentic AI and The Mythical Agent-Month

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The premise of this position paper is appealing . We know Brooks' Law : adding manpower to a late software project makes it later. That is, human engineering capacity grows sub-linearly with headcount due to communication overhead and ramp-up time. The authors propose that AI agents offer a loophole: "Scalable Agency". Unlike humans, agents do not need days/weeks to ramp up, they load context instantly. So, theoretically, you can spin up 1,000 agents to explore thousands of design hypotheses in parallel, compressing the Time to Integrate (TTI: duration required to implement/integrate new features/technologies into infrastructure systems) for complex infrastructure from months to days. The paper calls this vision Self-Defining Systems (SDS), and suggests that thanks to Agentic AI future infrastructure will design, implement, and evolve itself. I began reading with great excitement, but by the final sections my excitement soured into skepticism. The bold claims of the intro...
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Rethinking the University in the Age of AI

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Three years ago, I wrote a post titled "Getting schooled by AI, colleges must evolve" . I argued that as we entered the age of AI, the value of "knowing" was collapsing, and the value of "doing" was skyrocketing. (See Bloom's taxonomy. ) Today, that future has arrived. Entry-level hiring has stalled because AI agents absorb the small tasks where new graduates once learned the craft. So how do we prepare students for this reality? Not only do I stand by my original advice, I am doubling down. Surviving this shift requires more than minor curriculum tweaks; it requires a different philosophy of education. I find two old ideas worth reviving: a systems design mindset that emphasizes holistic foundations , and alternative education philosophies of the 1960s that give students real agency and real responsibility. Holistic Foundations Three years ago, I begged departments: "Don't raise TensorFlow disk jockeys. Teach databases! Teach compilers! Tea...
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Cloudspecs: Cloud Hardware Evolution Through the Looking Glass

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This paper (CIDR'26) presents a comprehensive analysis of cloud hardware trends from 2015 to 2025, focusing on AWS and comparing it with other clouds and on-premise hardware. TL;DR: While network bandwidth per dollar improved by one order of magnitude (10x), CPU and DRAM gains (again in performance per dollar terms) have been much more modest. Most surprisingly, NVMe storage performance in the cloud has stagnated since 2016. Check out the NVMe SSD discussion below for data on this anomaly. CPU Trends Multi-core parallelism has skyrocketed in the cloud. Maximum core counts have increased by an order of magnitude over the last decade. The largest AWS instance u7in now boasts 448 cores. However, simply adding cores hasn't translated linearly into value. To measure real evolution, the authors normalized benchmarks (SPECint, TPC-H, TPC-C) by instance cost. SPECint benchmarking shows that cost-performance improved roughly 3x over ten years. A huge chunk of that gain comes from AWS G...
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The Sauna Algorithm: Surviving Asynchrony Without a Clock

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While sweating it out in my gym's sauna recently, I found a neat way to illustrate the happened-before relationship in distributed systems. Imagine I suffer from a medical condition called dyschronometria , which makes me unable to perceive time reliably, such that 10 seconds and 10 minutes feel exactly the same to me. In this scenario, the sauna lacks a visible clock. I'm flying blind here, yet I want to leave after a healthy session. If I stay too short, I get no health benefits. If I stay too long, I risk passing out on the floor. The question becomes: How do I, a distributed node with no local clock, ensure operating within a safety window in an asynchronous environment? Thankfully, the sauna has a uniform arrival of people. Every couple of minutes, a new person walks in. These people don't suffer from dyschronometria and they stay for a healthy session, roughly 10 minutes. My solution is simple: I identify the first person to enter after me, and I leave when he leaves....
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Are Database System Researchers Making Correct Assumptions about Transaction Workloads?

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In this blog, we had reviewed quite a number of deterministic database papers, including Calvin , SLOG , Detock , which aimed to achieve higher throughput and lower latency. The downside of these systems is sacrificing transaction expressivity. They rely on two critical assumptions: first, that transactions are "non-interactive", meaning they are sent as a single request (one-shot) rather than engaging in a multi-round-trip conversation with the application, and second, that the database can know a transaction's read/write set before execution begins (to lock data deterministically). So when these deterministic database researchers write a paper to validate how these assumptions hold in the real world, we should be skeptical and cautious in our reading. Don't get me wrong, this is a great and valuable paper. And we still need to be critical in our reading.  Summary The study employed a semi-automated annotation tool to analyze 111 popular open-source web applications...
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Too Close to Our Own Image?

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Recent work suggests we may be projecting ourselves onto LLMs more than we admit. A paper in Nature reports that GPT-4 exhibits "state anxiety". When exposed to traumatic narratives (such as descriptions of accidents or violence), the model's responses score much higher on a standard psychological anxiety inventory. The jump is large, from "low anxiety" to levels comparable to highly anxious humans. The same study finds that therapy works: mindfulness-style relaxation prompts reduce these scores by about a third, though not back to baseline. The authors argue that managing an LLM's emotional state may be important for safe deployment, especially in mental health settings and perhaps in other mission-critical domains. Another recent paper argues that LLMs can develop a form of brain rot. Continual training on what the authors call junk data (short, viral, sensationalist content typical of social media) leads to models developing weaker reasoning, poorer lon...
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The Agentic Self: Parallels Between AI and Self-Improvement

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2025 was the year of the agent. The goalposts for AGI shifted; we stopped asking AI to merely "talk" and demanded that it "act". As an outsider looking at the architecture of these new agents and agentic system, I noticed something strange. The engineering tricks used to make AI smarter felt oddly familiar. They read less like computer science and more like … self-help advice . The secret to agentic intelligence seems to lie in three very human habits: writing things down, talking to yourself, and pretending to be someone else. They are almost too simple. The Unreasonable Effectiveness of Writing One of the most profound pieces of advice I ever read as a PhD student came from Prof. Manuel Blum, a Turing Award winner. In his essay "Advice to a Beginning Graduate Student", he wrote: "Without writing, you are reduced to a finite automaton. With writing you have the extraordinary power of a Turing machine." If you try to hold a complex argument enti...
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Popular posts from this blog

Hints for Distributed Systems Design

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This is with apologies to Butler Lampson, who published the " Hints for computer system design " paper 40 years ago in SOSP'83. I don't claim to match that work of course. I just thought I could draft this post to organize my thinking about designing distributed systems and get feedback from others. I start with the same  disclaimer Lampson gave. These hints are not novel, not foolproof recipes, not laws of design, not precisely formulated, and not always appropriate. They are just hints.  They are context dependent, and some of them may be controversial. That being said, I have seen these hints successfully applied in distributed systems design throughout my 25 years in the field, starting from the theory of distributed systems (98-01), immersing into the practice of wireless sensor networks (01-11), and working on cloud computing systems both in the academia and industry ever since. These heuristic principles have been applied knowingly or unknowingly and has proven...
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My Time at MIT

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Twenty years ago, in 2004-2005, I spent a year at MIT’s Computer Science department as a postdoc working with Professor Nancy Lynch. It was an extraordinary experience. Life at MIT felt like paradise, and leaving felt like being cast out. MIT Culture MIT’s Stata Center was the best CS building in the world at the time. Designed by Frank Gehry, it was a striking abstract architecture masterpiece ( although like all abstractions it was a bit leaky ). Furniture from Herman Miller complemented this design. I remember seeing price tags of $400 on simple yellow chairs. The building buzzed with activity.  Every two weeks, postdocs were invited to the faculty lunch on Thursdays, and alternating weeks we had group lunches. Free food seemed to materialize somewhere in the building almost daily, and the food trucks outside were also good. MIT thrived on constant research discussions, collaborations, and talks. Research talks were advertised on posters at the urinals, as a practical touch of M...
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TLA+ modeling tips

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Model minimalistically Start from a tiny core, and always keep a working model as you extend. Your default should be omission. Add a component only when you can explain why leaving it out would not work. Most models are about a slice of behavior, not the whole system in full glory: E.g., Leader election, repair, reconfiguration. Cut entire layers and components if they do not affect that slice. Abstraction is the art of knowing what to cut . Deleting should spark joy.  Model specification, not implementation Write declaratively. State what must hold, not how it is achieved. If your spec mirrors control flow, loops, or helper functions, you are simulating code. Cut it out. Every variable must earn its keep. Extra variables multiply the state space (model checking time) and hide bugs. Ask yourself repeatedly: can I derive this instead of storing it? For example, you do not need to maintain a WholeSet variable if you can define it as a state function of existing variables: WholeSet =...
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Foundational distributed systems papers

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I talked about the importance of reading foundational papers last week. To followup, here is my compilation of foundational papers in the distributed systems area. (I focused on the core distributed systems area, and did not cover networking, security, distributed ledgers, verification work etc. I even left out distributed transactions, I hope to cover them at a later date.)  I classified the papers by subject, and listed them in chronological order. I also listed expository papers and blog posts at the end of each section. Time and State in Distributed Systems Time, Clocks, and the Ordering of Events in a Distributed System. Leslie Lamport, Commn. of the ACM,  1978. Distributed Snapshots: Determining Global States of a Distributed System. K. Mani Chandy Leslie Lamport, ACM Transactions on Computer Systems, 1985. Virtual Time and Global States of Distributed Systems.  Mattern, F. 1988. Practical uses of synchronized clocks in distributed systems. B. Liskov, 1991. Exp...
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Learning about distributed systems: where to start?

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This is definitely not a "learn distributed systems in 21 days" post. I recommend a principled, from the foundations-up, studying of distributed systems, which will take a good three months in the first pass, and many more months to build competence after that. If you are practical and coding oriented you may not like my advice much. You may object saying, "Shouldn't I learn distributed systems with coding and hands on? Why can I not get started by deploying a Hadoop cluster, or studying the Raft code." I think that is the wrong way to go about learning distributed systems, because seeing similar code and programming language constructs will make you think this is familiar territory, and will give you a false sense of security. But, nothing can be further from the truth. Distributed systems need radically different software than centralized systems do.  --A. Tannenbaum This quotation is literally the first sentence in my distributed systems syllabus. Inst...
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Optimize for momentum

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Progress comes from motion.  Momentum is the invisible engine of any significant work. A project feels daunting when you face it as a blank page. It feels easier when you built some momentum with some next steps. So, momentum makes the difference between blocked and flowing. Think of a stalled truck on a desert road. You can't lift it with superhuman strength. But by rocking it with small periodic forces at the right rhythm (matching its natural frequency) you can get it rolling. Each tiny push adds to the previous one because the timing aligns with the system's response. The truck starts to move, and then the engine catches. Projects behave the same way. A big project has its own rhythm. If you revisit it daily, even briefly, your pushes line up. Your brain stays warm. Context stays loaded . Ideas from yesterday are still alive today. Each session amplifies the last because you are operating in phase with your own momentum. When you produce something every day, you never feel...
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The Agentic Self: Parallels Between AI and Self-Improvement

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2025 was the year of the agent. The goalposts for AGI shifted; we stopped asking AI to merely "talk" and demanded that it "act". As an outsider looking at the architecture of these new agents and agentic system, I noticed something strange. The engineering tricks used to make AI smarter felt oddly familiar. They read less like computer science and more like … self-help advice . The secret to agentic intelligence seems to lie in three very human habits: writing things down, talking to yourself, and pretending to be someone else. They are almost too simple. The Unreasonable Effectiveness of Writing One of the most profound pieces of advice I ever read as a PhD student came from Prof. Manuel Blum, a Turing Award winner. In his essay "Advice to a Beginning Graduate Student", he wrote: "Without writing, you are reduced to a finite automaton. With writing you have the extraordinary power of a Turing machine." If you try to hold a complex argument enti...
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Advice to the young

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I notice I haven't written any advice posts recently. Here is a collection of my advice posts pre 2020. I've been feeling all this elderly wisdom pent up in me, ready to pour at any moment. So here it goes. Get ready to quench your thirst from my fount of wisdom. No man, think for yourself, only get what works for you. It is called foundations, not theory Foundations of computer science (or rather any field of study) are the most important topics you can learn. These lay down the frame of thinking/perspective for that area of study. Yet, I am saddened to hear these called as "theory", and labeled as "unpractical". This couldn't be farther from the truth. Take a look at how I recommend studying distributed systems . Don't you dare call this "theory" and "unpractical". This lays the bedrock that you build your practice on. Don't skimp on the foundations. Don't build your home on quicksand. Keep your hands dirty, your mind cl...
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Cloudspecs: Cloud Hardware Evolution Through the Looking Glass

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This paper (CIDR'26) presents a comprehensive analysis of cloud hardware trends from 2015 to 2025, focusing on AWS and comparing it with other clouds and on-premise hardware. TL;DR: While network bandwidth per dollar improved by one order of magnitude (10x), CPU and DRAM gains (again in performance per dollar terms) have been much more modest. Most surprisingly, NVMe storage performance in the cloud has stagnated since 2016. Check out the NVMe SSD discussion below for data on this anomaly. CPU Trends Multi-core parallelism has skyrocketed in the cloud. Maximum core counts have increased by an order of magnitude over the last decade. The largest AWS instance u7in now boasts 448 cores. However, simply adding cores hasn't translated linearly into value. To measure real evolution, the authors normalized benchmarks (SPECint, TPC-H, TPC-C) by instance cost. SPECint benchmarking shows that cost-performance improved roughly 3x over ten years. A huge chunk of that gain comes from AWS G...
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Scalable OLTP in the Cloud: What’s the BIG DEAL?

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This paper is from Pat Helland, the apostate philosopher of database systems, overall a superb person, and a good friend of mine. The paper appeared this week at CIDR'24. (Check out the program for other interesting papers). The motivating question behind this work is: " What are the asymptotic limits to scale for cloud OLTP (OnLine Transaction Processing) systems? " Pat says that the CIDR 2023 paper "Is Scalable OLTP in the Cloud a Solved Problem?" prompted this question.  The answer to the question? Pat says that the answer lies in the joint responsibility of database and the application. If you know of Pat's work, which I have summarized several in this blog , you would know that Pat has been advocating along these lines before. But this paper provides a very crisp, specific, concrete answer. Read on for my summary of the paper. Disclaimer: This is a wisdom and technical information/detail packed 13-page paper, so I will try my best to summarize the sa...
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