Pawel DudaBook a call

AI Engineering Productivity · Fractional VP-Eng / CTO

I help SaaS scale-ups turn AI from a chaotic experiment into measurable engineering ROI.

Based on a program I designed and scaled at a global enterprise SaaS that cut bug-triage costs by80–90% across the org. I work with VP Engineering and CTOs at 50–500-engineer companies who need AI in the SDLC to actually move the cost and quality numbers — not just appear in the board deck.

Book a 30-min discovery callGet the Maturity Scorecard

No prep doc required. Bring the org chart and the most painful workflow.

PD

About

Senior engineering leader. Builder of the AI program that paid for itself in a quarter.

I’m Pawel Duda. I spent 18 years at a global enterprise SaaS company, most recently asSenior Manager, Services Engineering, where I led the redesign and scaling of an AI-Powered Bug Triage program that reduced bug-triage cost by 80–90%across the engineering organisation.

Earlier in the same company I built and led the founding mobile-offline team for a product deployed in the 2020 U.S. Census — approximately 300,000 iOS devices in the hands of 400,000 field enumerators, with zero tolerance for data loss. I’m a co-inventor on two granted U.S. patents and hold an M.Sc. in Computer Science from AGH University of Science and Technology in Krakow.

Today I run Duda Software as a one-person consulting practice. I work with VP Engineering, Directors and CTOs at scale-ups that have either committed publicly to an AI strategy or are quietly worried they haven’t.

  • Track record18 years at a global enterprise SaaS — engineering and management
  • Headline result80–90% cost reduction in bug triage at org scale
  • Production scale2020 U.S. Census — ~300k devices, ~400k field workers
  • Credentials2 granted U.S. patents · M.Sc. CS, AGH Krakow

Case study

How an AI-powered bug-triage program cut cost-per-bug by 80–90% at a global enterprise SaaS.

The situation

A multi-thousand-engineer SaaS organisation processing tens of thousands of incoming customer bugs per quarter. Triage was done by senior engineers across multiple regions — high-leverage people spending a meaningful share of their week reading repros, deciding severity, and routing to the right product team. The cost per triaged bug had been quietly creeping up for years.

What I changed

I led the redesign and scaling of an AI-powered triage pipeline: LLM-based classification and severity prediction; deterministic routing rules layered on top of the model; a closed feedback loop where engineering managers’ corrections fed back into evaluation. The critical design decision was treating cost per triaged bug as the north-star metric — not model accuracy, not throughput. Accuracy and throughput became inputs to the cost model.

The result

80–90% reduction in cost per triaged bug, sustained across the organisation. Senior engineers reclaimed a material share of their week. Routing latency dropped. The eval harness we built became the template for the next set of AI-in-SDLC initiatives.

What transfers

Bug triage isn’t special. The same pattern — pick a high-volume, judgment-heavy engineering workflow; pick a single cost metric; layer deterministic rules around the probabilistic core; build the feedback loop before you build the model — applies to code review, on-call paging, test-flake triage, support escalation and release-note drafting. That’s most of what your engineers actually spend their week on.

How we work together

Three engagement shapes. One outcome: AI in the SDLC, with the numbers to prove it.

Most engagements start with the Audit. Roughly half go on to a Transformation engagement; a smaller subset move into Fractional leadership. Lighter on-ramps — a paid pilot workshop or a keynote — are also available; mention what you’re looking for on the call.

Offer 01

AI Engineering Productivity Audit

2 weeksFrom €10,000 / 20,000 PLN

A focused two-week assessment of where AI can move the needle in your SDLC. You get a measurable roadmap, a baseline cost model, and at least one quick-win shipped within 60 days.

  • 5–8 structured interviews across eng, QA, support and product
  • Quantitative review of your bug, code-review, on-call and release pipelines
  • Maturity scorecard across 5 dimensions
  • Prioritised roadmap with cost/effort estimates
Discuss the audit

Offer 02

AI in SDLC Transformation

3–6 monthsFrom €8,000/month / 30,000 PLN/month

Implementation engagement that takes one or more SDLC areas — bug triage, code review, test generation, on-call — from manual to AI-assisted with hard metrics on cost, lead time and quality.

  • Pick 1–3 high-leverage workflows from the audit
  • Direct work with your engineers — pairing, design, evals
  • Internal evaluation harness so you can keep iterating after I leave
  • Monthly executive readout with cost and quality metrics
Scope a transformation

Offer 03

Fractional VP-Eng / CTO

~1 day/week, ongoingFrom €3,000/month / 12,000 PLN/month

Senior engineering leadership on retainer for scale-ups that don’t yet have a VP Eng or CTO in role. Hiring plans, org design, technical strategy, board prep, and the unglamorous middle-management work that decides whether engineering ships.

  • Weekly 1:1s with founders / executive team
  • Hiring loop design and senior interview panels
  • Architecture and roadmap reviews
  • Board / investor engineering readouts
Talk about fractional leadership

Invoicing in EUR for non-PL clients, PLN for PL clients. Polish JDG entity (Duda Software). Most engagements run under a one-page master agreement + per-engagement statement of work.

Free resource

AI Engineering Productivity Maturity Scorecard

A 5-dimension self-assessment that VP Engs can complete in 20 minutes with their staff engineers. Tells you, honestly, where your organisation sits on the AI-in-SDLC curve — and which of the next three investments will move the cost number, not just the press release.

  • Dimension 1Measurement & baselines
  • Dimension 2Tooling & adoption
  • Dimension 3Evaluation & quality
  • Dimension 4Change management
  • Dimension 5Cost discipline & ROI reporting

No drip sequence. You get the scorecard PDF, plus one occasional note when there’s a new case study or essay. Unsubscribe with one click.

FAQ

Things VP Engs and CTOs usually ask before the first call.

We already have a DevEx or Platform team. How is this different?
A DevEx team owns the tooling. My job is to make AI a measurable lever inside the SDLC and to give your leadership the cost and quality numbers needed to fund the next round of investment. I work with your DevEx team, not around them — most engagements end with the DevEx team owning the evaluation harness I helped build.
We’re only 80 engineers. Are we too small?
Fifty to five hundred is the sweet spot. Below fifty, the ROI on a structured AI productivity program is usually lower than just hiring two more senior engineers. Above five hundred, the org dynamics dominate and the engagement shape changes. Eighty is fine.
Our stack isn’t standard — does this still apply?
Yes. The work is about measurement, evaluation and change management. The specific LLM, IDE plug-in or RAG framework is the easy part. I’ve worked across Java, .NET, JavaScript, Swift, Objective-C and Python codebases and the principles transfer.
How do you handle confidentiality, NDA and IP?
Mutual NDA before the first technical conversation. Customer code and data stay on your systems; I bring patterns, not your competitors’ source. Anonymised case studies require explicit written consent from the customer before they appear anywhere — including on this site.
What does the pricing actually buy me?
Time, and a small amount of leverage. The Audit is fixed-scope: you get a written deliverable and a presentation regardless of how many calls it takes. The Transformation engagements are monthly retainers with named deliverables per month, capped at roughly 8 days of my time. The Fractional retainer is roughly one day per week.
Why hire you instead of a full-time VP Eng?
You shouldn’t — long-term. A full-time VP Eng is almost always the right answer once you can afford one and find the right person. The fractional model exists for the 6–18 month window where you have the budget but not yet the right hire, or where you need an outside perspective without committing to a permanent leader.
What happens after the 2-week audit?
You get the roadmap and the maturity scorecard. From there: most clients move directly into a Transformation engagement on one of the top items. Some clients take the roadmap and execute internally — that’s a fine outcome too. No retainer is required after the audit.

Talk to me

30 minutes. No deck. No pitch.

Tell me the workflow that’s eating your senior engineers’ week, and I’ll tell you whether I think AI moves the number or not. If I don’t think it does, I’ll say so on the call.

Email · pawel@dudasoftware.com

LinkedIn · /in/pawelduda

Location · Krakow, Poland · CET / CEST

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