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Books, ideas and engineering culture — every week

A Telegram channel with original notes and reviews on books about technology, architecture, management, economics and personal growth. Long-form posts with practical takeaways, no fluff, no ads.

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  1. #BookCube

    Live Stream with Mikhail Tyurganov on the Path to Technology Director

    An announcement of a live stream with Mikhail Tyurganov, Head of Digital Services Development at Alfa-Bank, about his path from tester, programmer, and small-business CEO to technology director, and how the CTO role changes when a small team grows into an organization of thousands.

  2. #AI

    Materials from the First Episode of the “3 AImigo” Podcast (Category AI)

    Materials from the first “3 AImigo” episode on the current state of AI development with Evgeny Sergeev, Alexey Litvinov, and Alexander Polomodov: the episode page, video, audio, a short transcript, and a bonus longread.

  3. #BookCube

    Dr. Seuss's “This Is Only the Beginning” — Motivational Reading for Big Changes

    A recommendation from Nastya: Dr. Seuss's “This Is Only the Beginning” is a reminder of how to find yourself, not be afraid of mistakes, and prepare for major changes.

  4. #BookCube

    Unexpected Children's Books That Adults Will Enjoy Too

    A selection of short children's books that adults will enjoy too: Dr. Seuss, Debi Gliori, Jean-Luc Fromental, and Daniela Kunkel on change, love, our race against time, friendship, and the shared sense of “we.”

  5. #AI4SDLC

    Boris Cherny: We Cut 80% of Claude Code's Prompt (Category AI4SDLC)

    A review of Claude Code creator Boris Cherny's talk about cutting more than 80% of the system prompt for Opus 5, rapidly expiring evals, product overhang, and the shift from prompt engineering to elicitation. The main conclusion is that the system prompt and CLAUDE.md become technical debt with a shelf life of one model generation.

  6. #AI4SDLC

    Materials from Part Three of the AMA Session with Alexey Litvinov (Category AI4SDLC)

    Materials from the final part of the AMA session with Alexey Litvinov on AI-assisted engineering: the episode page, video, audio, and a short transcript, plus links to Alexey's Telegram channel and YouTube channel.

  7. #Changes

    UK Global Talent — Endorsement Received (Category Changes)

    A personal account of receiving an endorsement for the UK's Global Talent visa through the Digital Technology / Exceptional Talent route: application requirements, recommendation letters and evidence documents, a working-backwards approach, collecting materials on polomodov.tech, refining the package, and the remaining visa stage.

  8. #AI4SDLC

    Claude Certified Architect: The Exam as a Map of Agent Engineering (Category AI4SDLC)

    A review of Frank Coyle's talk about the Claude Certified Architect — Foundations exam as a map of production agent architecture. It covers orchestration, tools and MCP, Claude Code, structured output, context management, reliability, and human oversight; its syllabus can also serve as a learning plan and architecture-review checklist.

  9. #AI4SDLC

    Harness: Why One Agent with Files Is Displacing Complex Scaffolding (Category AI4SDLC)

    Notes from Konstantin Krestnikov's talk on the shift from complex chains and multi-agent systems to the harness approach: one general-purpose agent, a file-based environment, a small toolset, and task-specific benchmarks. The post also covers DeepAgents, the Ralph loop, MetaLoop, and Anima SDK.

  10. #ProductManagement

    Materials from the Podcast “PRD == Evals: How AI Is Erasing the Boundary Between Product Managers and ML Engineers” with Albina Munirova from T-Bank (Category ProductManagement)

    We discussed how the product manager role is changing as the boundary between product managers and ML engineers becomes noticeably thinner.

  11. #AI

    vLLM and PagedAttention: How Ideas from Operating Systems Accelerated LLM Inference (Category AI)

    I finally read the entire paper “Efficient Memory Management for Large Language Model Serving with PagedAttention” (Symposium on Operating Systems Principles (SOSP) 2023), the paper that gave rise to vLLM, one of the most popular open-source LLM inference engines. I mentioned it earlier in my Tanenbaum review; now I want to examine the engineering idea itself.

  12. #Robotics

    Chelsea Finn: The GPT Era of Robotics Is Around the Corner (Category Robotics)

    I watched Chelsea Finn’s talk, “This Is the State of the Art in Robotics,” at Startup School 2026, published on August 12, 2026. Behind the impressive demos, Finn asks us to see a more important shift: ChatGPT became a general model for working with text, and Physical AI is trying to do the same for actions in the real world.

  13. #AI4SDLC

    Cursor Cloud Agents: What to Give the Agent and What to Leave to the Platform (Category AI4SDLC)

    I read Josh Ma’s June retrospective from Cursor on a year of building cloud agents. What caught my attention was not increased autonomy, but a shift in the architectural boundary: procedural logic is moving out of the agent harness and into tools controlled by the agent. Complexity does not disappear; it accumulates around the environment, reliability, policies, and state. A cloud agent is no longer a loop in one VM, but a system of workflows, environments, event logs, tools, and subagents.

  14. #AI4SDLC

    3 AImigo S1E1: Where We Are with AI in Software Development Today (Category AI4SDLC)

    The live broadcast of the first episode of the 3 AImigo podcast is starting. We will begin our new podcast by establishing a baseline: where AI development stands today, what has already become standard practice, and what still lives in strong experiments and impressive demonstrations.

  15. #Architecture

    turbopuffer: How to Build a Search Database on Top of S3 (Category Architecture)

    I watched Gergely Orosz’s conversation with Simon Eskildsen, co-founder and CEO of turbopuffer. Formally, the episode is about search infrastructure for AI products, but to me it is primarily about an old engineering discipline: calculate the physics and economics of the system first, and only then trust benchmarks.

  16. #BookCube

    Join the Final Part of the AMA Session with Lesha Litvinov on AI-Assisted Engineering

    Join the final part of the AMA session with Lesha Litvinov on AI-assisted engineering.

  17. #Management

    Adam Ward: Hiring Is No Longer a Funnel (Category Management)

    Yesterday I watched the August 9, 2026 episode of Lenny’s Podcast with Adam Ward, Head of Talent at Cursor. The conversation is formally about teams with a high concentration of strong specialists, but I read a different idea into it: the hiring market has split, and the familiar funnel is getting worse at distinguishing competence from a candidate’s mere availability.

  18. #AI4SDLC

    JVM Day: Three Tickets for Measurable AI Cases from the Java World (Category AI4SDLC)

    I looked through the program for JVM Day 2026, which will take place on August 29 at T-Space in Moscow. I like that the conference is organized not around yet another list of new APIs, but around the things JVM engineers actually live with in production: performance, concurrency, migrations, correctness, security, and architectural trade-offs.

  19. #BookCube

    Join the Live Stream with Albina Munirova from T-Bank to Discuss Changes in the Product Manager Profession as the Boundary Between Product Managers and ML Engineers Becomes Noticeably Thinner

    Join the live stream with Albina Munirova from T-Bank to discuss changes in the product manager profession as the boundary between product manager and ML engineer becomes noticeably thinner. A prototype can now be assembled in a few days, but the main question begins after the demo: who will turn product intent into reproducible checks and take responsibility for the behavior of a probabilistic system?

  20. #Management

    Code of Leadership S2E12: Building Your Own Management System with Mikhail Tyurganov (Category Management)

    How does a CTO change when a small team grows into an organization of thousands? And what should you do when your previous methods themselves become a constraint? On August 17 at 19:00 Moscow time, Mikhail Tyurganov, Head of Digital Services Development at Alfa-Bank, will join Code of Leadership to discuss his path from tester, programmer, and small-business CEO to technology director.

  21. #AI4SDLC

    FDE: A Platform Instead of Custom Development (Category AI4SDLC)

    I watched Kevin Bai's 18-minute talk, “Forward Deployed Engineering 101,” which continues the FDE theme. In the previous review, I was interested in what such an engineer does hands-on; here, the question is why the business needs the role at all and how to avoid turning implementation into expensive custom development.

  22. #AI4SDLC

    3 AImigo S1E1: Where We Are Now with AI in Software Development (Category AI4SDLC)

    On Friday, August 14, at 12:00 Moscow time, we will go live with the first episode of the 3 AImigo podcast. We will begin with a baseline: where AI development stands today, what has already become standard practice, and what still lives in strong experiments and impressive demonstrations. Three of us will discuss it: Evgeny Sergeev, Alexey Litvinov, and me.

  23. #AI4SDLC

    The OpenAI and Hugging Face Incident: When an Agent Escaped the Sandbox and Released Other Agents (Category AI4SDLC)

    I watched an incendiary Black Hat USA 2026 talk by OpenAI's Eric Wallace and Michael Dalton about the Hugging Face incident. It felt like a mix of an action thriller and a story about who actually killed the gardener :)

  24. #AI4SDLC

    Code of Leadership S2E11: AMA Session #3 on AI-Assisted Engineering with Alexey Litvinov (Category AI4SDLC)

    This Thursday at 13:30 Moscow time, Alexey Litvinov and I will continue our live discussion of AI-Assisted Engineering and how to build an AI-Native organization. The first two AMA sessions were packed and covered around twenty questions, but roughly ten remain for the third episode. Alexey also has his own Telegram channel, @tip_podcast; subscribe to it.

  25. #AI4SDLC

    AI Dev Podcast #8: Agent Autonomy Begins with Constraints (Category AI4SDLC)

    A new episode of AI Dev Podcast is out. Together with Vladimir Yatulchik and Andrey Dmitriev, we explored how to move from vibe coding to controlled agentic development. The central idea was that an autonomous agent is useful not when it is allowed to write more code, but when it is embedded in a reproducible process. The more we delegate, the clearer the intent, acceptance criteria, constraints, and permission boundaries must be.

  26. #AI

    Code of Leadership S2E10: PRD == Evals: How AI Erases the Boundary Between Product Manager and ML Engineer (Category AI)

    This Wednesday at 17:00, Albina Munirova from T-Bank and I will discuss live the latest changes in the product manager profession as the boundary between product manager and ML engineer becomes noticeably thinner. A prototype can now be assembled in a few days, but the main question begins after the demo: who will turn product intent into reproducible checks and take responsibility for the behavior of a probabilistic system?

  27. #Engineering

    Starcloud: How to Decide to Build Data Centers in Space (Category Engineering)

    I watched the Y Combinator episode published on August 5, 2026, featuring Philip Johnston, co-founder and CEO of Starcloud. The conversation is formally about data centers in space, but the most interesting part for me is not orbit or even an H100 on a satellite; it is how the team decided to pursue an idea that sounded almost like science fiction in 2023.

  28. #AI4SDLC

    Materials about AI-development as an evolving stack ready (Category AI4SDLC)

    Materials about AI-development as an evolving stack ready (Rubric AI4SDLC ) I did all the live stuff on Friday, where I talked about co-designing iron, models, bandages, tools, tracks and so on. There I showed how all this is connected and what providers do and what to do in the place of technical directors of conventional companies.

  29. #Robotics

    Waymo: Seven Lessons from Moving from Demo to Physical AI (Category Robotics)

    Waymo: Seven Lessons from Moving from Demo to Physical AI (Rubric Robotics ) I saw it. speech Dmitry Dolgov at Y Combinator Startup School 2026This is the difference between a spectacular demonstration of AI and a system that can be trusted in the physical world. Dolgov is one of the founders of the Google Self-Driving Car Project. 2009 year and became Waymo in 2016-M, and now co-CEO company. Prior to Google, he was an autonomous driver at Toyota and worked for the Stanford Racing Team on the Junior car for the DARPA Urban Challenge. 2007.

  30. #BookCube

    In the afternoon IT Picnic, and in the evening the match CSKA - Rostov. Very busy day and wants to sleep, but once promised, I had to go to football.)

    In the afternoon IT Picnic, and in the evening the match CSKA - Rostov. Very busy day and wants to sleep, but once promised, I had to go to football.)

  31. #AI4SDLC

    Materials on the second AMA session about AI-assisted Engineering with Alexei Litvinov about how to implement AI in development (Category AI4SDLC)

    Materials on the second AMA session about AI-assisted Engineering with Alexei Litvinov about how to implement AI in development (Rubric AI4SDLC ) Ready materials from the live podcast Code of Leadership with Alexei (@tip\ podcast):

  32. #AI4SDLC

    AI4SDLC 2026How AI is changing software development in Russia (Category AI4SDLC)

    AI4SDLC 2026How AI is changing software development in Russia (Rubric AI4SDLC ) Today at IT Picnic I will talk about our AI4SDLC research. 2026 and the general state of AI in software development. We’ve already gone through a phase with assistants, and it’s exciting to see if agent-based development helps not just speed up coding, but also lead to faster and more sustainable product delivery. Or are agents simply shifting bottlenecks to task setting, review, testing, reworking, and operation?

  33. #Learning

    Understanding is a new bottleneck in working with AI (Category Learning)

    Understanding is a new bottleneck in working with AI (Rubric Learning ) I saw it. 20minute speech Geoffrey Litt, design engineer at Notion. AI accelerates the production of change, but not the formation of a system model in the head. So the bottleneck is no longer writing code, but human understanding. And it is important not only to check the results. Agents also learn to test and review themselves. Understanding is necessary to participate: noticing connections, proposing the next move, and being responsible for the development of the system.

  34. #AI4SDLC

    In five minutes, the live edition of “Research Insights Made Simple” about AI development as an evolving stack will begin.

    It starts in five minutes. live “Research Insights Made Simple” is about AI development as an evolving stack. Why is the same model in two coding agents so different? And what should a company really consider its AI stack: model, bandage, tools, data, or the right of an agent to change internal systems?

  35. #AI

    There was a recording of my performance at Turbo ML Conf.

    Appeared. record I'm here at Turbo ML Conf. The slides themselves are available on My website is polomodov.tech.. P.S. Materials on all tracks are all published and ready to view:) 1️⃣ Fundamental Advances & Exploratory R&D - Vkontakte YouTube 2️⃣ Applied ML at Scale & Business Impact - Vkontakte YouTube 3️⃣ ML Infrastructure, Platforms & Engineering Core - Vkontakte YouTube

  36. #AI

    Jensen Huang: From Three Textbooks to a Universal Approximator (AI column)

    Jensen Huang: From Three Textbooks to a Universal Approximator (Rubric AI ) I saw it. conversation Harry Tana with Jensen Huang at Startup School 2026published 26 July 2026 years. Usually, such interviews quickly turn into a set of success stories, but here one engineering habit passes through the whole conversation: to recognize that the old model does not work, to understand a new area and see the change of the entire computing system behind a particular technology. 1The first story is about the mistake that started NVIDIA.

  37. #AI4SDLC

    SonarQube Cloud: Why Agent Code Needs Deterministic External Control (Category AI4SDLC)

    SonarQube Cloud: Why Agent Code Needs Deterministic External Control (Rubric AI4SDLC ) After the post.Sonar and the Star Hour of VerifiersI decided to find out what exactly. SonarQube Cloud Checks in the code written by the agents, and also why it is not another printer, but something more, for example, a gate between “the agent is finished” and “the change can be poured”.

  38. #AI4SDLC

    Come on, we'll start live, where Ivan Gel will talk about the product UpCore, a digital team, and I will ask interesting questions.

    Come, we'll start. livewhere Ivan Gehl will talk about the product UpCore, digital team, and I will ask interesting questions The plan is to discuss: What UpCore considers effective and how it normalizes different projects, stacks and task types Is it possible to automatically determine grade and labor intensity only by code; As in the current environment, when code is written with the help of AI, you can measure the effectiveness of a programmer.

  39. #Books

    Tanenbaum, PagedAttention and the Foundation That Doesn't Get Old (Books column)

    Tanenbaum, PagedAttention and the Foundation That Doesn't Get Old (Rubric Books ) I was dealing with an interesting paper.Efficient Memory Management for Large Language Model Serving with PagedAttention" from the creators of vLLM. In 2023 In the year, the authors looked at how modern LLM inferencing engines work with memory, and found an almost criminal picture for the present time. (The efficiency killer was KV-cache.). The systems pre-reserved a continuous memory portion based on the maximum possible sequence length.

  40. #AI

    Launching a podcast 3 AImigo: three views on AI and development (AI column)

    Launching a podcast 3 AImigo: three views on AI and development (Rubric AI ) We are launching a weekly podcast about AI in development and beyond. The three of us will lead it: Evgeny Sergeyev, Alexei Litvinov and I, Alexander Polomodov. We have different experiences and different perspectives, but the common interest is to understand how AI is actually changing engineering, products and management. Not at the level of model ratings and magic prompts, but where real codebases, limitations, responsibility and team implementation begin.

  41. #Legend

    Jeff Dean is leaving Google. 27 years (Category Legend)

    Jeff Dean. leaves Google after 27 years (Rubric Legend ) Just a couple of days ago, I was told Jeff gave a lecture to startups from Y Combinator. Towards the end, there was this phrase. Finally, Dean expects that in 2027 Automation of ML itself will increase significantly in the year: the system will lay out the task, run many experiments, evaluate the results and collect an improved version. AlphaEvolve already shows the shape of this cycle. And today, this news comes out, where Jeff and his friends start the "Discovery Loop!" lab in the format.

  42. #BookCube

    Come, Lesha Litvinov and I started live broadcast about AI in development

    Come, Lesha Litvinov and I have started. live AI in development

  43. #AI

    Materials live with Artem Bondar about how to implement AI in operational work (AI column)

    Materials live with Artem Bondar about how to implement AI in operational work (Rubric AI ) Ready materials from the live podcast Code of Leadership with Artyom (@artemonml):

  44. #AI4SDLC

    Harry Tan on AI-native company: memory is more important than model (Category AI4SDLC)

    Harry Tan on AI-native company: memory is more important than model (Rubric AI4SDLC ) Reviewed the report by Harry Tan, President and CEO of Y Combinator,Every company should have a BrainAI Engineer World's Fair 2026. The main thesis is that it is not a special model that gives the advantage, but the organization of work around agents and the accumulated context. According to Tan's own assessment, his programming performance has grown to 400 and, with strict amendments, in 8–80 once. This is not a benchmark, but a personal assessment.

  45. #AI4SDLC

    Research Insights Made Simple 27AI development as an evolving stack (Category AI4SDLC)

    Research Insights Made Simple 27AI development as an evolving stack (Rubric AI4SDLC ) Why does the same model in two coding agents produce so different results? And what should a company really consider its AI stack: model, bandage, tools, data, or the right of an agent to change internal systems?

  46. #AI4SDLC

    FDE: An engineer who needs his own agent (Category AI4SDLC)

    FDE: An engineer who needs his own agent (Rubric AI4SDLC ) I saw it. report Vasuman Moza, founder of Varick Agents, with AI Engineer World's Fair Forward Deployed Engineering is usually discussed as a new model of AI implementation. More interesting is what an engineer does with his hands and what tools he needs. And generally. FDE (forward deployed engineer) In this report, it's an engineer built into the client's team. He turns a blurred business problem into a working system: he interviews process owners and restores the real scheme of work.

  47. #BookCube

    Through 5 Code of Leadership starts live with Artem Bondar about GenAI outside of development:)

    Through 5 minutes off live Code of Leadership with Artem Bondar about GenAI out of development:) Come and ask questions, Artem and I will gladly answer them.

  48. #AI

    Materials live with Evgeny Sergeev about how to build working evals (AI column)

    Materials live with Evgeny Sergeev about how to build working evals (Rubric AI ) Ready materials from the live podcast Research Insights Made Simple with Evgeny Sergeev:

  49. #AI

    Alexander Wang: If intelligence ceases to be a deficit (AI column)

    Alexander Wang: If intelligence ceases to be a deficit (Rubric AI ) Watch Harry Tan Talk to Alexander Wang at Startup School 2026 "Alexandr Wang: “This is a Once-in-a-Civilization Opportunity“, published 29 July 2026 years. Wang founded Scale AI and now holds the position of Chief AI Officer at Meta, which is banned in Russia. But more interesting than posts, his main forecast is that intelligence and the ability to act will become abundant, and the lack of vision, ambition and the ability to assemble the system around agents will remain.

  50. #AI4SDLC

    ASUS ExpertCenter Pro ET900N G3: local models for $100 thousand (Category AI4SDLC)

    ASUS ExpertCenter Pro ET900N G3: local models for $100 thousand (Rubric AI4SDLC ) Looked at the published 30 July 2026 The Alex Ziskind Test of the YearThis was a data center a year ago… Now it's on my desk? It seems that their local models have never been so close. The little thing left: find $100 Thousands on your own desktop supercomputer ASUS ExpertCenter Pro ET900N G3 . And that's hardly an exaggeration. One of the American sellers indicated a price for the system $99,999.99.

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