AI-assisted delivery

Gate included

AI-Powered Web Development Tools

Your engineers already code with AI assistants. We make the output safe to merge: a four-step review gate, written no-AI zones, twelve weeks of measurement and internal tooling where seats fall short.

Start Building Read Brief

BRIEF: AI-TOOL-05 MODEL: TUNED

Teams already shipping AI-written code

Engineering leads and CTOs at product companies and agencies whose developers use Copilot, Cursor or Claude Code, with or without a policy. Some are about to buy seats for everyone. Others bought them a quarter ago and now face longer reviews and no number showing whether the licences pay for themselves.

Time to call us when

Half the team uses Copilot, two swear by Cursor, and nobody set rules.
Reviews slowed after we bought seats, and seniors are now the bottleneck.
We found AI-written code in our login flow that nobody checked.
Finance asks what the AI licences return; we only have seat counts.

Where AI-assisted delivery goes wrong

Review time grows with writing speed

Assistants move work from the editor to the review queue. On our own codebases, writing sped up and review time grew by roughly the same amount.

Plausible code in risky paths

Models learn from public code, insecure tutorials included. In authentication or payment code, a suggestion can compile and pass basic tests while doing the wrong thing.

Seat count posing as adoption

Active seats say nothing about value. Without edit rate on AI output and review-cycle length, nobody can tell whether a tool helps or should be cancelled.

We build the review gate before anyone buys seats

Our AI tooling work always ships the gate with the assistant. Each AI-touched pull request gets a human review around one question: what does this code assume that the model could not see? Strict static analysis, coverage on changed lines and a security reviewer for sensitive paths follow, enforced by branch rulesets and CODEOWNERS.

Before rollout we agree where assistants stay off: authentication, cryptographic primitives, payment paths, personal and health data, smart-contract logic and custom rate limiters. Elsewhere they are normal tools. Every AI-touched pull request carries a tag the dashboard can find, and tools are judged on twelve weeks of data before anyone scales them.

4-step

Review gate on AI-touched code

12 weeks

Window before judging a tool's return

Review checklist

A nine-point checklist in your PR template: input validation, ownership-based authorisation, parameterised queries, file paths, secret scanning, dependency vetting, error responses, rate limiting and audit logging.

Codebase hygiene

One linter enforced in CI, written naming conventions, one folder structure across modules and a five-minute architecture overview, so assistants have a stable pattern to follow.

Adoption metrics

Edit rate on AI output, review-cycle length, time to first merged PR for new engineers, and the review gap per reviewer, where a widening gap signals burnout.

Developer tooling

A custom layer on top of the assistant that drafts pull request summaries, explanations of legacy files, initial migration notes and internal guides from your own repository.

What stays in your repository

Rulesets and CODEOWNERS enforcing the four-step gate
A no-AI zones policy in the PR template
A tool map matching assistants to tasks
An AI-touched PR tag and edit-rate dashboard
A twelve-week readout with a verdict per tool

How the AI rollout runs

Gate first, seats second

01

01
Workflow map

A half-day workshop with your engineering lead. You bring the repository and last sprint's tickets; we map where assistants save time or add review cost.

Duration
Half-day

Result
Tool map and draft no-AI zones
- Workshop
- Tool map
02

02
Gate and hygiene

We configure branch rulesets, CODEOWNERS and strict static analysis, and standardise linting and folder structure where modules differ. Seats go out once the policy exists.

Duration
Before rollout

Result
Every AI-touched PR passes four checks
- Rulesets
- CODEOWNERS
03

03
Adoption

The first four weeks are adoption. We tag AI-touched pull requests, baseline review times and adjust the PR template where reviewers catch the same issue twice.

Duration
Weeks 1-4

Result
Tagged PRs and a review baseline
- Tagging
- Baseline
04

04
Measure and decide

Weeks five to eight are noise; weeks nine to twelve give the first data worth acting on. We compare edit rate and merge rate per tool.

Duration
Weeks 5-12

Result
Keep, narrow or remove each tool
- Edit rate
- Merge rate

Assistants and checks we use

Assistants: GitHub Copilot

Cursor

Claude Code
Gate enforcement: GitHub branch rulesets

CODEOWNERS

PR templates
Static analysis: TypeScript strict

PHPStan level 8

mypy strict

Entry points for AI tooling

Tooling workshop

Half a day for teams about to buy seats. You leave with a tool map and a review checklist for your stack.

Gate review

For teams already using assistants: we read your rulesets, CODEOWNERS and last 90 days of PRs, then list changes that lift merge rate.

Gated rollout

The gate, zones and internal tooling built as fixed-fee milestones inside a development engagement, so the rules ship with the code.

Fixed quote once a 30-minute call has covered your repositories and team.

AI coding tool questions

Which AI coding assistant should we start with?

The one that runs in the editor your team already uses, which for most teams is GitHub Copilot. We keep Copilot for inline completion and add Cursor or Claude Code once cross-file refactors or migrations repeat. See our AI coding assistants playbook.

Should we ban AI tools on security-sensitive code?

Yes, on a short list of named paths, and only there. A company-wide ban pushes usage underground, where nothing gets reviewed. CODEOWNERS enforces the no-AI zones and the PR template repeats them. Our note on when to code by hand explains why.

When can we tell if an AI tool pays off?

After twelve weeks at the earliest: four of adoption, four of noise, then four that give the first data worth acting on. Repositories with mixed conventions need two quarters or more, because early gains there come from standardising the code. Earlier calls usually reverse.

What should we measure instead of seat count?

Edit rate on AI-generated code, PR review-cycle length and time to first merged PR for new engineers. A healthy edit rate rises slowly. Near zero means the team rejects everything; near 100% means nobody reads the output. Neither is fixed by changing tools.

Can you build internal AI tools for our developers?

Yes, and the review gate ships with them. Most of our AI tooling work pays off on documentation and repeated structure: pull request summaries, legacy-file explanations, migration notes and component scaffolding. Their output goes through the same gate as any AI-touched change.

Client reviews

What clients say about working with Vadim

5.0 75 reviews on Google

All reviews

Oron Markus 2022 · Google ★★★★★

We needed a quick fix for our system. Vadim Leviev gave us fast, professional service. We will definitely keep working with him on future projects. Highly recommended!

Ben Goren 2022 · Google ★★★★★

Vadim gave me courteous, fast and professional service for a problem that came up on my site. I warmly recommend him and will certainly turn to him again when needed.

irit dulman 2022 · Google ★★★★★

Vadim really saved me at the last minute, right before the Black Friday sales. I had faults on my site; he fixed them and also built what I needed in order to sell.

reuven cohen 2024 · Google ★★★★★

Very happy with Vadim's work on WordPress sites! A true professional who meets deadlines. I work on several
projects with him and I recommend him to you.

יוסי שירי 2025 · Google ★★★★★

Great service. Vadim is there for every problem with a fast, effective fix. He has maintained two of my sites for more than 5 years.
Highly recommended.

אביחי שלום 2021 · Google ★★★★★

Vadim is a lovely guy, helpful and courteous. He supported me all the way to success, with honesty and integrity. I highly recommend him to everyone!

Roy Tal 2022 · Google ★★★★★

Vadim did two very good jobs for me this past week. I intend to keep working with him and recommend him to anyone looking for good, fast delivery.

שחר אלעד 2023 · Google ★★★★★

A champion! I had a serious problem on my site
and Vadim sorted it out in the most professional way possible, at a fair price.
Highly recommended.

Review your AI gate

Tell us which assistants your engineers use and where reviews slow down. We will suggest which of the three options comes first.