Przemysław Zalewski

AI in your company, with receipts

An AI consultant who has shipped agents, not slide decks

I build agentic systems in production since 2024, without a framework tax: tools, evaluation loops, cost caps, MCP servers people actually use. In 2026 an agent opened about 30% of my team’s merged pull requests under rules I wrote. I can take your company from “we tried ChatGPT” to one workflow that runs on its own and gets measured. Score your readiness below in two minutes.

Available from November 2026 · Wrocław, Poland (CET), remote

Przemysław Zalewski
  • “someone you can always count on”public LinkedIn recommendation
  • “a true bias for action”client CTO, on LinkedIn
  • 15+ yearsshipping software
  • Free call, no pitch deck30 minutes, then you decide
~30%of merged PRs in 2026 opened by an AI agent, ~85% reviewed by me
~40×more commits year over year with agents under enforced rules
10,000+affiliate programs catalogd, ~97% found automatically
15+years shipping software

Why me

Adoption that survives the pilot

Most AI pilots die because nobody picked the workflow, the owner and the metric before the demo. I start with a map of your processes, choose one with a clear number attached, and ship that one to production before touching the next.

Custom agentic systems, no framework tax

No LangChain. Tools with narrow scopes, an evaluation loop with LLM-as-judge against fixtures, a cost cap in a Durable Object, models compared across releases and swapped when the numbers say so. My content platform published thousands of articles and a catalog of 10,000+ programs, ~97% automatically, on exactly that design.

Rules, skills and review for coding agents

CLAUDE.md and AGENTS.md that agents cannot skip, skills for the repeating work, hooks and lint gates in CI, a human review on every PR, AI-assisted content disclosed. That is how one product went to ~40× more commits year over year without the quality dropping.

Your product usable by agents

An MCP server with narrow tools on top of your existing auth, adoption measured per client from the first merge, a bot-protection rule that would have blocked every agent found the same day because the dashboard showed it. If ChatGPT and Claude users want to talk to your product, this is the work.

Ways to work together

Four shapes of engagement, no prices on the page

Scope first, then a number in writing. The call is free either way.

1 week

AI readiness audit

Your processes, data, API, security and team, read by someone who has shipped this. A written report: which workflow goes first, what an agent can safely do today, what has to change, a plan with milestones.

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4 to 6 weeks

One workflow, one agent

A single outcome in production: a support triage agent, a content pipeline, an MCP server for your product, a coding-agent setup for the team. Measured from the first day, handed over with the rules and the dashboard.

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workshop + 4 weeks

AI enablement for your engineers

A hands-on workshop, then rules, skills and review gates for Claude Code and Codex in your repos, then four weeks of pairing. The team keeps the speed and loses the mess.

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2 to 3 days a week

Fractional AI lead

Inside your team for a quarter or two: the roadmap for AI features, vendor and model choices, evals, costs, security reviews, hiring screens. Your people ship, I keep the quality bar.

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Proof

Work I can show

Problem, what I did, result. Client names only where I am allowed to use them.

An AI coding agent as a team member, under enforced rules

The problem
Coding agents produce ten times the output and ten times the mess. A team of four wanted the speed without a slop swamp on main.
What I did
I authored the rule set shared by Claude Code and Codex: mechanical checks over written rules, lint and test gates for security, API surface and CSP, agents working on main with hooks, every PR reviewed by a human, AI-assisted content disclosed as such.
Result
In 2026 the agent opened about 30% of merged pull requests across two products and I reviewed about 85% of them. My own output went from under 1,000 to 5,000+ commits a year.

~30% PRs by agent ~85% reviewed 5,000+ commits/yr

See also: AI & agents · Full-stack & custom software

An MCP server from first merge to first external users

The problem
Users wanted to log time from their AI assistants. The API existed, the agent surface did not.
What I did
I set the tool surface, removed destructive tools, routed every operation through the existing REST controllers so an agent gets no wider access than a person, and instrumented adoption per client in PostHog from day one.
Result
First external users within weeks. A bot-protection rule that rejected MCP clients by user agent was found and removed the same day because the dashboard showed it.

MCP OAuth adoption dashboard

See also: AI & agents · PostHog & product analytics

Agentic content platform built from scratch, quality measured not assumed

The problem
Thousands of articles were needed, with AI disclosure built in and without publishing slop.
What I did
Late 2024 I built the agent driver: enforced stop conditions, tool-call limits, parallelization, delegation chains. Quality came from best-of-n, LLM-as-judge, scoring against fixtures and plagiarism checks, with many models evaluated across their releases.
Result
Thousands of articles shipped through the platform. Content deployed automatically across 300+ generated sites with git-backed bulk operations and reputation monitoring.

thousands of articles 300+ sites LLM-as-judge

See also: AI & agents

Live demo

Score your AI readiness in two minutes

Twelve questions across six areas: data and APIs, process ownership, measurement, security, evaluation, team skills. You get a score per area, a verdict and a sketch of the first thirty days built from your two weakest areas. Everything runs in your browser.

Demo loading…

Copy the result as Markdown and bring it to the call. It becomes the agenda.

How it works

Three steps from this page to a running project.

  1. 1

    A 30-minute call

    You describe the product and the problem. I ask the questions I would ask on day one. If I am not the right person, I say so and point you to someone who is.

  2. 2

    Scope in writing

    A short written plan follows: what we build first, what we measure, how we work together and what it costs. No slide deck.

  3. 3

    Something to touch in week one

    The first slice ships in the first week: deployed, measured, reviewable. From there the work is paced by what the numbers say.

Fit check

Is this a fit?

A good fit when

  • You need a senior who owns delivery, not a pair of hands
  • The product has to ship and be measured, with or without a product manager
  • A solo engagement or a team of up to four
  • TypeScript, React, Node.js, Cloudflare, Postgres, PostHog

Probably not when

  • A program that needs a ten-person vendor team
  • A stack built around Java, Python or a cloud I do not sell
  • Body leasing by the hour with no say in how the work is done
  • A start before November 2026

Working style

How I work

Agents under rules

Claude Code and Codex work on main with hooks, lint and test gates. The model suggests, the criteria decide. Every PR gets a human review and AI-assisted content is disclosed.

Review as a craft

Hundreds of pull requests reviewed. I review for the product and its reasons. The code comes second.

Measured, not assumed

PostHog in every project from day one. A tracking plan per feature and dashboards leadership actually reads.

FAQ

Questions people ask before they book

Why no LangChain?
Because the problems that matter sit elsewhere: which tools the agent gets, how you know it is correct, what it costs, what happens when it is wrong. A few hundred lines of TypeScript with an eval suite beat a framework you cannot debug. The technical side is on the AI and agents page.
Which models and vendors?
Whatever wins the evaluation for your task at your budget. I run Claude, OpenAI and open models on Workers AI side by side and keep the comparison in the repo. Vendor lock-in is a decision, never an accident.
What about our data and GDPR?
EU hosting where the data requires it, no customer data in prompts without a policy that says so, prompt injection treated as a design constraint. Analytics through PostHog EU with a first-party proxy, see the PostHog page.
Will you replace our developers with agents?
No. Agents under rules make a good team faster and a careless team louder. I set the rules, the gates and the review, your engineers keep the keys. Read how I run them on the AI and agents page.
How do you measure ROI?
A metric per workflow before the build: tickets closed, hours saved, articles published, adoption per client. PostHog from day one, a dashboard leadership reads without asking, and a written go or no-go after the first month.
How soon can you start?
November 2026. Book the call and bring the readiness score from the demo below.
Przemysław Zalewski

Let’s find out in 30 minutes

A free 30-minute call. You bring the problem, I bring questions. No prices on this page because scope comes first.

If I am the wrong person I will say so on the call and point you to someone better.

After you book: a calendar invite, then the call. Nothing else to fill in.

Available from November 2026 · B2B contract or employment · Wrocław, Poland (CET), remote