Independent code quality consulting

Improve code quality to make work more predictable.

I work on code review, automated tests and BDD to reduce bugs, ambiguity in requirements and the gap between what is estimated and what actually happens. I am Luca Lucchesi, an independent Code Quality consultant, and I work with companies with at least 20 developers overall, even when they are distributed across several teams.

Structured code reviews Reliable tests Stable pipelines More autonomous teams
Get in touch and let's schedule a call
No mandatory calendars: you write to me, I suggest 2–3 options.
See what I can do for your team
No generic slide decks: we start from your code, your pipelines and the real problems your developers face.
Services

A clear path to raise quality

I do not sell tools. I sell visible improvements in code quality and in the team’s day-to-day work. To avoid fragmented interventions, I work in phases: understand the situation, decide what matters, put guardrails where they are needed, and make the team autonomous. Durations are indicative and depend on volume and complexity.

Package 1 · Entry point

Code Quality Assessment

A technical, concrete snapshot: where the hotspots are, where risk is growing, what makes sense to do now (and what does not).

  • Repository, churn and hotspot analysis
  • Targeted reading of code and workflows
  • Priorities and operational recommendations

Typical duration: 2–3 weeks.

Package 2 · Decisions

Quality Advisory & Roadmap

We turn the assessment into a sustainable roadmap: guidelines, a realistic test strategy, useful metrics and coherent technical choices.

  • 3–6 month roadmap and measurable goals
  • Review and quality guidelines that hold up in practice
  • Support for CTOs / Tech Leads on critical decisions

Typical duration: 1–2 months.

Package 3 · Guardrail

Quality Guardrail (strategic code review)

Temporary support on the most critical pull requests: preventing regressions and consolidating shared practices and criteria, without turning review into a bottleneck.

  • Selective review of high-impact PRs
  • Guideline violations and systemic risks
  • Periodic mini-report on patterns and improvements

Typical duration: 1–2 months (time-boxed, with an explicit goal).

Package 4 · Autonomy

Hands-on Quality Enablement

Practical support to make the team autonomous: in-line coaching, targeted workshops and improvements that remain after the consulting work is over.

  • Coaching on review, refactoring and testing
  • Targeted CI interventions when it is a bottleneck
  • Handover and stabilization

Typical duration: 2–3 months (optional).

Areas of intervention

What I can work on, depending on the context

These are the main areas I work on. They usually come into play in one or more phases of the path, depending on where the codebase and workflows show bottlenecks.

Analysis and review

Code and process review

Analysis of repositories, project structure, internal conventions, branch model and code review practices.

Understanding where the flow gets stuck is the first step toward making it move.

Testing and QA

QA Engineering and test automation

Design or review of automated test suites, with attention to reliability, execution times, long-term maintainability and coverage of critical cases.

Tests that create confidence, not false alarms.

Pipeline

Delivery flow stability (when needed)

Targeted interventions on builds and pipelines only when they are a bottleneck (slowness, instability, flaky tests). The goal is not to “do DevOps”, but to remove impediments that slow development and release.

Less waiting, fewer breakages, more continuity.

Metrics and governance

Metrics and internal code quality

Introduction or review of quality rules and controls (e.g. Checkstyle, SpotBugs, PMD) that can be integrated into builds. If a more complete layer of analysis and governance is needed, we can also evaluate solutions such as SonarQube together.

The simplest way to make informed decisions.

Team

Support for development teams

Pragmatic training on refactoring, effective code reviews, TDD when it makes sense and BDD: defining scenarios during refinement and translating them into automated tests, to verify that the system really satisfies the expected behaviours.

First we write examples, then we write software.

Ways of working

Modular collaborations

We can start from a limited analysis (one project, one pipeline, one test suite) and then extend the work based on results and priorities.

Starting small is often the best way to see immediately where it makes sense to invest.

Who it is for

Companies with technical maturity… and the desire to take the next step

I do not start from zero and I do not come in to do abstract evangelism. I work best with organizations that already have solid developers and existing infrastructure, but feel that quality can (and should) improve.

Typical profile

Team and context

  • Organization with at least 20 developers overall (one or more teams).
  • Software strategic for the business or sold to customers.
  • CI/CD pipelines already in place but often unstable or slow.
  • Automated tests present but not very reliable or too slow.
  • A codebase that has grown a lot over the years, with “delicate” areas.
  • Too much time spent putting out fires in production.

If you recognize yourself in at least two of these points, I can probably help.

Signals

Symptoms I often see

Bugs that keep returning cyclically in the same areas of the code.
Pipelines that fail “for no reason” or are too slow to be used often.
Flaky tests that no one knows whether to trust.
Code reviews experienced as an obstacle, not as help.

I do not judge. I work to make the flow simpler and more predictable: less friction, more confidence, more quality.

Approach

A simple, transparent and measurable way of working

Every engagement follows a clear structure. The details depend on the context, but the method remains the same: understand the situation, intervene in a targeted way, consolidate the results.

1
Assessment (2–3 weeks)
Study of repositories, CI/CD configuration, test suites and workflows. Targeted reading of the code to identify hotspots, risks and recurring patterns.
Output: priority map + concrete recommendations (do now / plan / avoid for the moment).
2
Advisory & Roadmap (1–2 months)
Translation of the analysis into sustainable decisions: code review guidelines, a realistic test strategy, useful metrics and a 3–6 month roadmap.
Output: shared roadmap and clear criteria for deciding “what matters” in your context.
3
Quality Guardrail (1–2 months, temporary)
Strategic code review on the highest-impact pull requests: regression prevention, consistency with guidelines, useful feedback with sustainable turnaround times.
Output: more stable quality without turning review into a bottleneck.
4
Enablement and consolidation (2–3 months, optional)
Practical support and in-line coaching to make the team autonomous: effective reviews, targeted refactoring, reliable tests and more stable CI where needed.
Output: practices and conventions that survive over time, even without my presence.

In the first call, I can show you a sample roadmap based on a real case (in anonymized form).

Practical setup

How we collaborate

  • I work mainly remotely, using the tools the team already uses.
  • I interact both with developers and with technical stakeholders (CTOs, area leads).
  • I fit into existing workflows: I do not arrive with a “universal manual” to apply to everyone.
  • I can support the team directly in Pull Requests, with technical reviews and in-line coaching.
  • I make explicit what we are measuring and which improvements we are trying to achieve.

If after the analysis phase I understand that I am not the right person to help you, I tell you clearly.

Why me

30 years in development. 15 in quality. No fluff.

I have spent many years writing code, reviewing it, debugging, designing pipelines and helping teams work better. This is the point of view I bring as a consultant.

Developer first, consultant later.
I know how it feels when pipelines break, flaky tests block the work and reviews seem like a waste of time.
Experience on complex enterprise and legacy projects.
I have worked on large applications that have grown over the years, with many dependencies and constraints.
Expertise in Java, QA and CI/CD.
Especially on Java codebases, test automation and Jenkins/Bitbucket pipelines, but the approach also applies to other stacks.
Goal: make the team autonomous.
My work only makes sense if the team keeps improving after the consulting engagement is over.

“I am a consultant, not a salesperson: if I cannot help you, I would rather tell you straight away than promise results I cannot guarantee.”

Examples of intervention

Concrete results from real experience

The examples below come from real experience. The contexts have been anonymized, but the results are ones I can explain and argue in detail.

Recurring pattern

Unreliable estimates and stressful releases

Team with tests in place, but not used much as a source of confidence.
Estimates are made “by feel”, bugs emerge late and the plan often breaks down in the final stages.
Typical signal: low trust in tests and poor predictability.
Recurring pattern

Hidden hotspots and invisible technical debt

A codebase grown over time, with areas that “no one is eager to touch”.
A small part of the code concentrates most of the bugs, but without data it is hard to decide where to intervene.
Typical signal: frequent regressions in the same modules.
Recurring pattern

Code reviews experienced as a brake

Long, uneven reviews or reviews perceived as control.
Pull Requests pile up, feedback arrives late and often creates friction instead of improvement.
Typical signal: quality entrusted to individual heroics.
The increase in code coverage (from 43% to 81%) led to greater confidence in the code and in the tests.

In this context, a team managed to reduce to 10% the difference between estimated time and actual time spent developing stories.
The introduction of a code review process with an external view, less immersed in day-to-day development, led to a reduction of about 30% in production bugs, thanks to early identification of potential problems.
Analysis of churn and hotspot reports made it possible to identify about 20% of the code responsible for about 80% of the bugs.

Characterization tests and subsequent refactoring were introduced in these areas, significantly reducing the risk of regressions.
By improving code readability and comprehension (clear naming, well-distributed responsibilities, lower coupling and tests as support for understanding), a new team became operational on maintenance of a project in half the time compared with previous experiences on legacy code.
The adoption of BDD, with scenarios defined during refinement, reduced by 33% bugs due to incorrect interpretation of requirements, thanks to greater shared clarity before implementation.

During a first conversation I can go into more detail on these examples, adapting them to your specific context.

Frequently asked questions

FAQ

Some questions I often receive when companies are evaluating whether to start a collaboration.

Can we start with a small assignment?
Yes. Many collaborations start from a limited code review or from the review of a single pipeline. It helps you understand how I work and what kind of impact I can have.
Do you review every Pull Request?
No: when needed, the Quality Guardrail, which is a selective review of the highest-impact PRs. The goal is to prevent regressions and consolidate practices, not to become a bottleneck.
Are the durations fixed?
No. The indicated durations are typical and are meant to give an idea of the path. They depend on the volume of work and complexity (number of repositories, release frequency, test and CI maturity).
Do you also work remotely?
Yes, I mainly work remotely. We can include in-person moments if they make sense for workshops or specific activities.
Do we need to change all the tools we use?
No. I prefer to start from the tools the team already uses (Jenkins, Bitbucket, Azure DevOps, GitLab, etc.). The goal is to improve the way you use them, not replace them by default.
How long does it take to see benefits?
It depends on the context, but the first concrete improvements are often visible within two to six weeks, especially on pipelines and tests. More structural interventions take longer, but in the meantime we begin removing the most obvious obstacles.
Do you interact directly with developers?
Yes. My work only makes sense if I talk to the people who are in the code every day. At the same time, I maintain a clear dialogue with CTOs and area leads.
What happens after the consulting work?
The goal is to leave behind processes, conventions and tools that the team knows how to carry forward autonomously. We can include periodic alignment moments if useful.
Contact

Write to me and let's see whether it makes sense

If you recognize yourself in the problems described above, the next step is to talk about your specific context. No long-term commitment: first we understand whether it makes sense to work together.

A quick, focused, technical conversation
In 20 minutes we can understand whether I can help you, where it would make sense to start and which results are realistic in your case.
In your email, you can briefly indicate your role, the size of the team and the main problem you would like to address. We will use the call to get straight to the point.