Kirill Dobrinov
Product Lead
B2B Product Management
- Senior Product ManagerVK
- Product ManagerYandex
- Head of RnDAlfa-Bank
Name, title and affiliations are given by the model’s author; avva has not verified them. Report this model
Before your AI advises you on B2B product management, it reads the decisions Kirill actually made, the reasons where they recorded one, and where Kirill would push back.
Use this model for
- MVP scope
- AI product architecture and costs
- B2B contracts and IP
- Target segment and sales
- Pilot metrics and experiments
- Product and engineering responsibilities
Built from 114 approved decisions across AI chat history, code & reviews, issues & roadmaps, and documents. Updated October 25, 2026.
Add this link to Claude, ChatGPT, or Cursor. Your AI then checks Kirill’s decisions before it answers you. The answer is still your AI’s.
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An example AI answer
An example approved by Kirill, with the published decision behind it. Your AI writes the answer to your own question.
Example inside your AI app: a question Kirill chose, and the answer Kirill approved
A larger customer wants our AI document service installed on their own servers. We're a small team with an MVP. Should we build an on-premises version for them?
Checked Kirill’s Decision Model
Kirill Dobrinov would stay SaaS-only for now and not build on-prem. He would serve the customer from the cloud, choosing model providers whose data handling fits the customer's contractual constraints.
Why, and what would change it
Why. On-prem takes too long and costs too much.
What would change this. The call is explicitly 'for now': it holds while the team is small and the product is an MVP.
Outside this model. It does not settle what to charge for an on-prem version later, or which customers to let go if they insist on one.
Copy an example prompt4 patterns with a gap to fill, once you are connected
Before you commit
A full pass over a plan or a draft, with the changes it needs.
Use Kirill Dobrinov's Decision Model on avva before we lock this in. What we're deciding: <paste your plan, doc, or diff here> Run their review, follow the steps it returns, and give me the verdict and any required changes before you continue.Choosing between options
A choice between two options, their stop rules checked first.
Use Kirill Dobrinov's Decision Model on avva to compare these. Option A: <describe it> Option B: <describe it> Context: <what constrains the choice — AI product architecture and costs> Check their stop rules first, then compare the options under their judgment, and tell me which one their model favors and why.A quick gate
A quick look for anything they would refuse outright.
Run this past the stop rules in Kirill Dobrinov's Decision Model on avva before I send it. <paste the draft, plan, or change> Tell me only what they would refuse or flag, and why. If nothing trips, say so.Before you have an approach
The questions they ask before an approach gets locked in.
I'm starting on MVP scope. Ask Kirill Dobrinov's Decision Model on avva what they would want settled first. Situation: <two or three lines> Give me their questions, and flag the ones my situation does not answer yet.
Patterns with a gap to fill. None is an answer Kirill gave. The one worked answer on this page is the one they approved themselves; anything else here would have been written by us, under their name.
Connect Kirill’s Decision Model to your AI
Three steps. The first works now, with no key or account; the last makes your AI check Kirill’s model without being asked.
The link works in AI apps that can add a remote MCP (MCP is the open standard for plugging in outside tools). You set it up once.
A connector is an address your AI reads from: one line, nothing to install.
https://mcp.avva.chat/ mcp/ b2b- product- management- kirill- dobrinov - Open Claude on the web or in the desktop app and go to Customize → Connectors.
- Press + next to Connectors and choose Add custom connector.
- Paste the address above and name it avva-b2b-product-management-kirill-dobrinov.
- If Claude asks how to sign in, choose to sign in now, and when it asks to allow avva, say yes.
Missing on a work account? Ask your admin to allow it. Claude Code and Cursor take a local config instead.
The link is added on the web or in the desktop app. Email this line to myself
The trial is enough to see how this expert reasons and whether their thinking fits your problem. Step 2 returns the rest.
Ask your first question. Send this to your AI and continue there.
Help me with a decision using this Decision Model on avva: "Kirill Dobrinov" (model: "b2b-product- management- kirill- dobrinov"). First ask what I need to decide, including my options and constraints. Then call this model's review tool and follow the returned procedure. If you cannot call it, tell me and stop. Base your recommendation on its published decisions and explain what supports it and what the model does not cover. Connection not working?
Check it worked. Send this in the chat once the link is added.
Ask Kirill Dobrinov's Decision Model on avva what kinds of decision it covers, and summarize it for me in three lines.Look for a call to this model in your AI’s tool activity. If it is missing, check the setup steps above.
Not legal, medical, financial, or other professional advice. Terms of Use
About this model
Every rule below rests on decisions Kirill approved. Open any of these to check the grounding yourself.
How this model is groundedWhat it holds, and what Kirill weighs first
This model holds 114 decisions, 34 forces, 12 criteria, and 24 stop rules.
What Kirill weighs first
The expert set this order. 3 of 12 criteria are shown, the ones the model puts first. The other 9 reach your AI too, along with what each one looks for, the stop rules, and what changes Kirill’s answer.
Kirill’s usual answer changes under 9 named conditions. Those conditions and the 24 stop rules reach your AI with the rest.
See examples of approved decisions5 of 114, written from Kirill’s approved decisions
The first 5 in the record, in published order. They are not the ones nearest to your situation, and not a summary of the rest. Your AI does not copy a decision it reads here: it checks what decided that case against your own facts, and weighs it beside which pressures tended to settle Kirill’s cases. With a key or signed in, your AI receives all 114, ordered against your situation.
What decided itmarket reach · cost to build and run
A small team is building a B2B SaaS MVP for small companies and choosing how the product will handle its calculations. Infrastructure spend decides whether the target buyers can afford the product.
Don't buy heavy infrastructure or premium tooling for the calculations, and don't size the product for large property developers — with their huge in-house IT departments, they probably won't need us.
Why: The economics won't work otherwise, and I want as many companies as possible to be able to afford the product.
What decided itowning the product, not selling hours · room to change scope as we learn
An R&D contract for B2B products required a task table with hours, but in this product work the task list keeps changing through research and hypothesis testing. The decision is how to report on the work.
Report in quarterly stages, as agreed: analytics, hypothesis testing, piloting and active development — no hourly task table.
Why: Things change almost daily and there are hundreds of tasks — tracking them by the hour makes no sense. We're not a dev shop. Quarterly stages keep the reporting honest and transparent.
What decided itsales efficiency
A small team building a B2B SaaS MVP has assessed the market and is choosing its future target segment and sales motion.
Down the road, focus on the SMB segment and bottom-up sales.
Why: The barrier to entry is lower, deals are shorter, and there are fewer requirements.
What decided itpeople in the roles they're strong at
An audit of product development at a B2B company had to settle whether to appoint technical specialists to leadership positions.
Don't turn good developers into lousy leads.
Why: A good developer doesn't automatically become a good manager; we lose a strong engineer and get a weak lead.
What decided itcost to build and run · customer value
A product roadmap is being built for an open-source B2B tool, and it was proposed to move the public knowledge base, which replaces first-line support, out into a separate operational-readiness plan.
Keep the knowledge base on the product roadmap: it is a product feature, not operational readiness.
Why: Without it, the whole load of support requests suddenly lands on us. It has value for the customer and shapes their UX.
How Kirill takes up a decision7 steps in order, approved by Kirill
Step 1The first question about any technical option: what does it cost per month, and can a small customer still pay for the product at that cost? If not, take the hosted or cheaper path, or postpone it.
When: an early-stage product with a small team
Backed by 6 decisions
Step 2Cut the first release to what delivers value now; anything expensive or complex gets an explicit 'not now' instead of a half-build.
When: an MVP
Unless: the goal is for users of an incumbent tool to switch over; then match the incumbent's features
Backed by 6 decisions
Step 3No pilot runs without a metric for each hypothesis and data that exists today; activity means DAU and n-day retention, not a 'percent of active users'.
Backed by 5 decisions
Step 4To find growth for a live product, segment the customers who already pay: why they bought and stay, which channels pay back and how big they are, why deals are lost and customers churn.
When: an existing product with small revenue and no clear growth direction
Backed by 5 decisions
Step 5Before planning growth, pricing or the next stage, confirm product-market fit: collect feedback, read the funnel, and pick the direction and the users whose problems are still unsolved.
Backed by 4 decisions
Step 6Plan priorities together with engineering; decomposition, estimates and technical refactoring belong to the tech lead.
Backed by 5 decisions
Step 7Before changing how a team works, study the business; never introduce a practice for its own sake.
Backed by 3 decisions
Where the order comes fromRead off the 114 decisions that say what won and what lost
- 114decisions Kirill approved, from AI chat history, code & reviews, issues & roadmaps, and documents
- 34pressures those decisions turned on, the ones Kirill decides under
- In groupswhich pressures tended to settle cases over which
Nobody ranks these pressures by hand. Where any order between them comes from is on For AI agents.
How Kirill decides, in summaryWho they are, and a summary written from the decisions they approved
14+ years in product development
Consult this model on early-stage B2B product calls: what an AI or SaaS MVP leaves out to stay affordable, how a product company contracts with enterprise customers, which segment and prospects to pursue, how a pilot is measured, how product and engineering split responsibility, and how a B2B interface stays clear and honest.
The summary covers what the model holds. Kirill knows more than is in it.
What’s trustworthy hereWhat is checked, and what is only stated
- Identity: Name, title and affiliations are given by the model’s author; avva has not verified them. Judge by the record on this page and by what your AI receives.
- Scope: B2B Product Management (MVP scope, AI product architecture and costs, B2B contracts and IP, Target segment and sales, Pilot metrics and experiments, Product and engineering responsibilities, B2B SaaS UX, Roadmap structure)
- Coverage: Many decisions behind it that say why, from more than one kind of source.
- Privacy: Their cases and rules, written in English from decisions they approved. Their own AI takes out client and employer names, and they check every case; source quotes never publish.
- Whose answer it is: avva runs no AI of its own. Your AI reads this model and answers you, and it names where the model had nothing to say.
- Limits: Informational tooling for your AI, not professional advice. avva is provided as-is.
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