Book Cube: 2026, page 6
Book Cube publications from 2026, page 6: bilingual notes, sources, and original Telegram posts.
- · #Consulting
Code of Leadership S2E7: Consulting in the Age of AI: What is left without beautiful presentations? (Category Consulting)
Code of Leadership S2E7: Consulting in the Age of AI: What is left without beautiful presentations? (Rubric Consulting ) If AI can already gather analytics, make recommendations, and deliver a compelling presentation in a matter of minutes, what will companies pay consultants for?
- · #AI4SDLC
Philipp Schmid on agent skills: first eval, then post (Category AI4SDLC)
Philipp Schmid on agent skills: first eval, then post (Rubric AI4SDLC ) Watched a short talk by Philipp Schmid of Google DeepMindDon't Ship Skills Without EvalsThe basic thesis is simple: skill changes the behavior of an agent, so releasing it without checking is like changing code without testing. Schmid suggests checking not whether the agent has read SKILL.md, but the result of the work. To do this, each skill needs a small set of tasks: where it should connect, where it should not and what result is considered correct.
- · #PlatformEngineering
ingress-nginx: how a small API acquired its own language (Category PlatformEngineering)
ingress-nginx: how a small API acquired its own language (Rubric PlatformEngineering ) Dealing with closing ingress-nginx. This story can be described as an open source drama: the component for about half of cloud-native environments, according to internal data from Datadog, was supported for years by one or two people in their spare time. But I'm more interested in the mechanism that made him unaccompanied. The Ingress API was deliberately left small: host, path, backend, TLS.
- · #AI
Anthropic and parallels with OpenAI’s Empire of AI: How a Laboratory Becomes an Institute (AI column)
Anthropic and parallels with OpenAI’s Empire of AI: How a Laboratory Becomes an Institute (Rubric AI ) Looked at the extended interview Emily Chang with Dario Amodei for Bloomberg The Circuit, published 17 June 2026 years. Over the past few months, I’ve been deconstructing large AI labs from different angles: Google agency workflowsProhibited in Russia Meta - through world models (They were driven by Jan LeCun, who had already left the company.)Thinking Machines - through interactive large models.
- · #Architecture
Research Insights Made Simple 25Why the architect’s AI-copilot still hasn’t worked out (Category Architecture)
Research Insights Made Simple 25Why the architect’s AI-copilot still hasn’t worked out (Rubric Architecture ) AI already knows how to suggest an architectural pattern, form an ADR, and draw a compelling diagram. But does it hold the history of decisions, constraints, and consequences of change throughout the system?
- · #AI
How a product from Meta launches products without being able to program (AI column)
How a product from Meta launches products without being able to program (Rubric AI ) I looked back six months ago. release Lenny's Podcast with Zevi Arnovitz, a product from banned in Russia Meta and former PM in Wix, but forgot to write about it. Then it seemed to me that this is a new filling of the role of the product, but if it works in a conditional Meta, then it is not a fact that it is easily transferred to other companies:) Now I wrote a post about what awaits products and remembered this video and decided to share it with you.
- · #SRE
Addiction Graph as a Filter to Chaos Engineering (Category SRE)
Addiction Graph as a Filter to Chaos Engineering (Rubric SRE ) Read the five-page work of Anatoly KrasnovskiyModel Discovery and Graph Simulation: A Lightweight Gateway to Chaos Engineering" The main idea is simple: before expensive experiments with failures, you can automatically collect dependency graphs from distributed tracks, add the number of replicas and cheaply run Monte Carlo along it.
- · #AI4SDLC
AMA Session on AI-assisted Engineering with Alexey Litvinova n (Category AI4SDLC)
AMA Session on AI-assisted Engineering with Alexey Litvinova n (Rubric AI4SDLC ) Monday, 17:00 in Moscow together with Alexey Litvinov live Let’s talk about AI-Assisted Engineering and how to build an AI-Native organization in general, where we can discuss topics from working with one agent to the operating model of the whole team and organization. By the way, Lyosha has her own tg channel - @tip\ podcast, subscribe to it.
- · #RnD
Causal AI database: first graph, then effect (RnD heading)
Causal AI database: first graph, then effect (Rubric RnD ) Watched a short report by Vadim Porvatov from SberChallenges and prospects of Causal AIfrom the Data Fest 2026. It’s a good fifteen-minute route on a topic that’s often boiled down to “correlation doesn’t mean causation.” The main thesis here is more practical: before assessing the effect of an action, it is necessary to restore at least a plausible structure of causes.
- · #BookCube
I love meeting interesting people at CxO Community meetings. Different companies have such communities, but Sber often has this not only with networking, but also with interesting experience.
I love meeting interesting people at CxO Community meetings. Different companies have such communities, but Sber often has this not only with networking, but also with interesting experience. Last time the event was around wine tasting, and this time we listen to Oscar Konyukhov, the head of staff of his father, Fyodor Konyukhov. The story is about the planning and implementation of complex projects on the edge of technical and human capabilities. Thanks to the organizers of Sber CxO TechCommunity, these are really interesting events.
- · #AI4SDLC
Research Insights Made Simple 23 - The economics of AI in development (Category AI4SDLC)
Research Insights Made Simple 23 - The economics of AI in development (Rubric AI4SDLC ) The vote showed that the topic is interesting and therefore tomorrow 17:00 into live Let's break down the economics of AI in development. The bottom line is that tokens get cheaper, models get faster, but the company’s AI budget doesn’t necessarily decrease. The more work scenarios appear, the more tasks, agent chains, infrastructure, checks, and error costs become.
- · #BookCube
Yesterday he spoke at the Podlodka AI Club and talked about his thoughts on the economics of AI in development.
Yesterday he spoke at the Podlodka AI Club and talked about his thoughts on the economics of AI in development. When I was ready, I made this one. longrid like this slide-deckBut the speech itself was not recorded. I can record a separate video for channel subscribers if you want, but let’s collect , under this post so I know you like the idea. If there are more than twenty in the end, the video will be released on YouTube, if not, then only text versions will remain.
- · #Management
Graham Weaver: How to come up with a game you want to win (Category Management)
Graham Weaver: How to come up with a game you want to win (Rubric Management ) I saw it. last lecture Graham Weaver for Stanford GSB class 2025 years How to Design a Winnable Game ? Graham is a professor of management at Stanford and the founder and partner of Alpine Investors. But he’s not talking about investing, he’s talking about the moment you realize that you’ve been playing the wrong game for years. The lecture begins with a personal moment when during a crisis.
- · #Architecture
ArchBench: a good frame, a weak leaderboard (Category Architecture)
ArchBench: a good frame, a weak leaderboard (Rubric Architecture ) I read a short paper.ArchBench: Benchmarking Generative-AI for Software Architecture Tasks" The idea is sound: to assemble disparate evals for software architecture into one extensible system. But 19 July 2026 This is more a frame of the future benchmark than a working leaderboard for choosing a model. (You can evaluate the leaderboard for yourself. bench). Team. SERC From India's IIIT Hyderabad, they assembled an open system from the CLI and React site.
- · #AI
Bringing GenAI into Operations — Live with Artem Bondar
A Code of Leadership live stream with Artem Bondar on GenAI in support, accounting, marketing, and building design—from polished demos to measurable operations.
- · #Management
McKinsey on AI Agent Economics: Measure Outcomes, Not Tokens (Category #Management)
A business view of agent economics: cost per accepted task, the autonomy tax, KPIs, and the consequences of failure rather than token price alone.
- · #AI4SDLC
Theo Browne on AI development: think bigger, design stricter (Category AI4SDLC)
Theo Browne on AI development: think bigger, design stricter (Rubric AI4SDLC ) I saw it. final keynote Theo Browne "Everything we knew about software has changed" with AI Engineer World's Fair 2026. Theo builds tools for developers, so it’s interesting to listen to him not as a model commentator, but as a practice in which AI has already changed the scale of projects. The main point of his report: the border of "too big" is time to draw again. Theo's shift shows through its own staircase Reddit scraper was a two-day project.
- · #AI4SDLC
Published a longrid on agent stack configurations. The dispute usually boils down to a choice between “own OpenCode” and “alien Claude Code or Codex”, but this is a false fork: the binding, model and code are selected separately.
Published. longrid about the configurations of the agent stack. The dispute is usually reduced to a choice between “own OpenCode” and “alien Claude Code or Codex”, but this is a false fork: the binding, model and tools are selected separately, and control is needed over the entire chain from data and identity to actual action in the system. I analyzed eight stack options: their TCO, lock-in, characteristic failures and security boundaries. Sovereignty and security are properties of the entire architecture, not a single component.
- · #AI4SDLC
Benoit Schillings: R&D after code (Category AI4SDLC)
Benoit Schillings: R&D after code (Rubric AI4SDLC ) I saw it. keynote report Benoit Schillings, VP from Google DeepMind at AI Engineer World's Fair 2026. His position is interesting to me - he is not a product IT leader implementing an agent in SDLC, but a head of R&D. His team is building the technology that Gemini will need on a month-to-year horizon. So instead of backlog, CI/CD and SLO, he discusses what the next model should learn. The story has a funny beginning.
- · #Chess
Moscow 2026 International Chess Forum (Category #Chess)
The final day of the Moscow 2026 forum, Ernesto Inarkiev and Sergey Karjakin's exhibition match, and an idea for a stream on how programmers and AI agents think.
- · #AI4SDLC
Materials on Evaluating Coding Agents in Dialogue (Category #AI4SDLC)
Slides, video, audio, and a concise transcript of a Research Insights Made Simple episode with Alexey Litvinov on evaluating coding agents through dialogue.
- · #Software
Alexey Milovidov and ClickHouse: from curiosity to a company in $15 billion (Category Software)
Alexey Milovidov and ClickHouse: from curiosity to a company in $15 billion (Rubric Software ) I watched with great interest a great interview Elizabeth of Ossetia (foreigner) with Alexei Milovidov, creator and CTO ClickHouse. Formally, this is the story of a company with a valuation of $15 billion But I found it more interesting as an engineering project, from curiosity and internal tools to open source and global business.
- · #AI4SDLC
Materials about coding agents and the importance of expertise (Category AI4SDLC)
Materials about coding agents and the importance of expertise (Rubric AI4SDLC ) Prepared materials with podcast Code of Leadership, which was on Wednesday with Evgeny Sergey:
- · #Software
The Java Story: How the Language Became a Long-lived Platform (Category Software)
The Java Story: How the Language Became a Long-lived Platform (Rubric Software ) I watched it live yesterday. documentary CultRepo’s The Java Story is about the history of Java. In the frame were James Gosling, Joshua Bloch, Brian Goetz, the creators of Tomcat, Spring, Hibernate and Kotlin, as well as engineers of the Java ecosystem. But for me, it's not so much a story of language, it's more of a story about a whole technology platform that's survived its own mistakes, its own change of ownership, and its attempts to declare it dead.
- · #AI4SDLC
Research Insights Made Simple 22How to Build a Managed Agent Stack (Category AI4SDLC)
Research Insights Made Simple 22How to Build a Managed Agent Stack (Rubric AI4SDLC ) What does the company do in the agent platform: the client code, model, execution contour, data, or the agent’s right to change internal systems? These things are often confused and reduce the choice to a dispute between “own OpenCode” and “alien Claude Code or Codex.”
- · #AI4SDLC
Materials about AI-assisted Engineering (Category AI4SDLC)
Materials about AI-assisted Engineering (Rubric AI4SDLC ) Prepared materials with podcast Code of Leadership, which was with Alexei Litvinov on Wednesday:
- · #BookCube
Through 5 We will start the stream with Alexei Litvinov, where we will talk about fresh benches of interactive work with agents: SWE-Together and SWE-INTERACT.
Through 5 minutes off stream with Alexei Litvinov, where we will talk about fresh benches of interactive work with agents: SWE-Together and SWE-INTERACT Connect to the stream and ask questions in the comments - we will try to respond intreactively to them:)
- · #Architecture
Thoughts on architecture (Category Architecture)
Thoughts on architecture (Rubric Architecture ) I realized that in my pet projects I architecture I'm getting better from the idea that I want to cut chips fast, but
- · #BookCube
A couple of promised pictures for the analysis of architecture with links between
A couple of promised pictures to parsing architecture with connections between
- · #Architecture
AI for Software Architecture: Why 2026- The architect's copilot still doesn't work. (Category Architecture)
AI for Software Architecture: Why 2026- The architect's copilot still doesn't work. (Rubric Architecture ) A systematic review of the literatureArtificial Intelligence Support for Software Architecture PracticeIt is a practical question - what architectural tasks AI can already support and why individual successes do not yet add up to a holistic practice. The first version appeared in 2025 year, but in 2026 It was updated in the year and 2 July 2026 year the article came out ACM Transactions on Software Engineering and Methodology.
- · #RnD
Materials about Loop Engineering (RnD heading)
Materials about Loop Engineering (Rubric RnD ) Prepared materials with podcast Research Insights Made Simple, who was with Maxim Smirnov on Tuesday:
- · #BookCube
Stream's off, come watch. https://www.youtube.com/watch?v= 4xRni7V6c
Stream's off, come watch. https://www.youtube.com/watch?v=\ \ 4xRni7V6c
- · #Architecture
How I and my agents got myself live on a static site today without the usual backend (Category Architecture)
How I and my agents got myself live on a static site today without the usual backend (Rubric Architecture ) This week I have four conversations with experts live: two have already passed, two are yet to come. The format of real-time communication ceased to be a one-off experiment for me, and at some point it became strange that my website was a real-time experience. polomodov.tech He doesn't know anything about it. I wanted a simple behavior: if the next seven days are scheduled to air, the site itself shows the announcement.
- · #AI4SDLC
Research Insights Made Simple 21How to Measure Coding Agents in Dialogue (Category AI4SDLC)
Research Insights Made Simple 21How to Measure Coding Agents in Dialogue (Rubric AI4SDLC ) What changes if the requirements for coding agents do not come in perfect promptom, but are clarified along the way? 17 July 16:00 MSC discuss Alexei Litvinov on the podcast "Research Insights Made Simple" 21" We’ll talk about the new SWE-Together and SWE-INTERACT benches released on the same day. I’ve been talking to both of you on this channel. (SWE-Together and SWE-INTERACT).
- · #Books
AI-Assisted Engineering: From Successful Prompt to Engineering System (Books column)
AI-Assisted Engineering: From Successful Prompt to Engineering System (Rubric Books ) I recently read Alexei Litvinov’s book “AI-Assisted Engineering”, with whom today we will discuss his book. live. Initially, Alexei invited me to read his book and give feedback. I was happy to read the book to see how I could put the disparate practices of working with AI agents into one system.
- · #AI4SDLC
Research Insights Made Simple 20Why coding agents do not cancel the examination (Category AI4SDLC)
Research Insights Made Simple 20Why coding agents do not cancel the examination (Rubric AI4SDLC ) What happens when a coding agent selects files, runs commands, and writes an implementation? Thursday, 16 July, with 16:00 before 17:00 MSC discuss Evgeniy Sergeev in "Research Insights Made Simple - Season" 1, Episode 20" Whitepaper Anthropic: "Agentic coding and persistent returns to expertise" Eugene Sergeev Director of Engineering at Flo Health.
- · #AI4SDLC
Loop Engineering: Why a Major Part of the Agent Cycle Is the Right to Say No (Category AI4SDLC)
Loop Engineering: Why a Major Part of the Agent Cycle Is the Right to Say No (Rubric AI4SDLC ) Tonight, 16:00 In Moscow, we will discuss the stream with Maxim Smirnov materialLoop Engineering: The Anthropic Playbook for Designing Systems That Prompt Your AgentsSo I had to prepare and read it beforehand:) Below I will leave a short press, and for the expanded version come on stream.
- · #BookCube
Before I had finished reading the book “Agentic Design Patterns” about the creation of agents, I began to read the book by Eliser Yudkovsky “If someone creates it, everyone will die.”
Before I had finished reading the book “Agentic Design Patterns” about the creation of agents, I began to read the book by Eliser Yudkovsky “If someone creates it, everyone will die.” I used to know Eliser as a popularizer of science and the author of Harry Potter and the Methods of Rational Thinking, and now I will get acquainted with his public position of Doomer. (doomer) in relation to artificial intelligence. I would like to note that the book has become a bestseller in 2025 I'm doing an interesting reading this year:))
- · #AI4SDLC
Who controls the coding agent: the person or the cycle he designed?
Who controls the coding agent: the person or the cycle he designed? We’re used to discussing the prompts, context, and binding of a single agent launch. But when the agent returns to work—on a schedule, an event, or the outcome of a past passage—the task becomes architectural: who finds the job, checks the result, stores the condition, and can stop the cycle. 14 July 16:00 I'll go to Moscow live with Maxim Smirnov. Let's disassemble the HuaShu material.Loop Engineering: The Anthropic Playbook for Designing Systems That Prompt Your Agents?
- · #AI
Yann LeCun on JEPA: predicting not pixels, but the state of the world (AI column)
Yann LeCun on JEPA: predicting not pixels, but the state of the world (Rubric AI ) I watched Jan LeCun's lecture.World Models: Enabling the Next AI Revolutionread 29 May 2026 A year at ETH Zurich. It turned out to be almost an exploratory manifesto: it is not enough for the physical world to generate the next token - you need to build an abstract state of the world, predict the consequences of actions and plan on top of it. By the way, Jan Lekun at the end of last year left the company banned in Russia Meta, where he had long been Chief Scientist.
- · #AI4SDLC
The code is cheaper. What became expensive? (Category AI4SDLC)
The code is cheaper. What became expensive? (Rubric AI4SDLC ) An AI agent can already write code in minutes that would have taken an evening. But one successful diff does not mean that development has become faster: a bottleneck can simply move into problem setting, review, testing and validation. Wednesday, 15 July, in 13:00 ICU will hold live on my TellMeAboutTech channel. with Alexei Litvinov in the video podcast "Code of Leadership".
- · #AI4SDLC
[2/2] Claude Code and Expertise: Why Session Success Is Not a Sign of Productivity (Category AI4SDLC)
\[2/2\] Claude Code and Expertise: Why Session Success Is Not a Sign of Productivity (Rubric AI4SDLC ) Keep going. analysis research by Anthropic"Agentic coding and persistent returns to expertise" about the use of Claude Code. In the first part, we talked about the methodology and results of the study, and now we would like to understand how to interpret them and how to assess the weight of the evidence given in the study. I would put them on a scale like this.
- · #AI4SDLC
[1/2] Claude Code and Expertise: Findings from 398 Thousand Sessions (Category AI4SDLC)
Anthropic’s observational analysis links task-specific expertise with greater delegation and more frequent verified session success. Its sample and success definition limit what it says about productivity.
- · #AI4SDLC
Nick Nisi on Agent Skills: Fewer Instructions, More Evidence (Category AI4SDLC)
Nick Nisi’s Case system moves agent workflow control into code. His talk shows why evidence, product-specific guidance, and evals matter more than adding instructions.
- · #BookCube
This week my children and I spent in a sports camp near Tula, where they played football three times a day.
This week my children and I spent in a sports camp near Tula, where they played football three times a day. And I spent the first few days doing almost full-time AI engineering and it was fun. Then something happened and the Internet on the base disappeared, and the mobile Internet worked only on white lists. But I don't go anywhere without books, so I'm not confused.
- · #AI4SDLC
Stack Overflow Developer Survey 2026The survey itself has become a map of agent development (Category AI4SDLC)
Stack Overflow Developer Survey 2026The survey itself has become a map of agent development (Rubric AI4SDLC ) Half an hour ago I filled a new one. Big Stack Overflow (It's off. 23 June 2026 year and is still available for). I went there not so much for the usual set of “languages, bases, IDE”, but out of curiosity: what Stack Overflow this year asks about AI. And there's a shift that's clearly visible -- it's no longer about chat rooms or auto-additions, but an attempt to measure how AI and agents enter the production system.
- · #BookCube
And by tradition I attach the most interesting illustrations from the report "Cursor Developer Habits Report"
And by tradition I add the most interesting illustrations from the report.Cursor Developer Habits Report"
- · #AI4SDLC
Cursor Developer Habits Report: AI Gains Are Concentrated Among Power Users (Category AI4SDLC)
Cursor’s spring 2026 report shows a heavily skewed distribution of AI activity. Cohort-level measures are needed to distinguish effective agent workflows from raw usage.
- · #BookCube
Illustrations from the SWE-Interact bench
Bench illustrations "SWE-Interact"
- · #AI4SDLC
SWE-Interact: The Cost of Interactivity for Coding Agents (Category AI4SDLC)
Scale AI’s SWE-Interact compares the same coding tasks in single-turn and interactive settings. The reported performance gap, simulation design and study limitations matter when selecting agents for real users.