---
title: "Technical Problem Solving & Rescue CTO | Artem Zaitsev"
slug: "problem-shooting"
type: "page"
lang: "en"
date: "2026-10-16"
last_modified: "2026-10-16"
version: "1.0"
summary: "Diagnose critical outages and bottlenecks, find root causes, and implement durable fixes so your systems stay fast, stable, and secure."
author: "Artem Zaitsev"
tags: ["Technical Problem Solving", "Fractional CTO", "Artem Zaitsev", "technology leadership"]
use:
  training: allow
  rag: allow
  embedding: allow
attribution: required
---

# Technical Problem Solving

> Facing critical technical hurdles, performance bottlenecks, or persistent bugs? My experience excels at diagnosing and resolving complex technical problems, ensuring your systems run smoothly, efficiently, and securely. I dive deep to find root causes and implement robust, long-term solutions.

## My Troubleshooting Methodology

A comprehensive, multi-layered approach to identifying and resolving technical issues at their source.

- **Deep System Diagnostics** — Comprehensive analysis of logs, metrics, and system behavior to pinpoint issues.
- **Performance Bottleneck Identification** — Profiling applications and infrastructure to find and resolve performance drains.
- **Security Vulnerability Remediation** — Thorough audits to identify and fix security flaws, protecting your assets.
- **Root Cause Elimination** — Focusing on fixing the underlying cause, not just symptoms, for lasting stability.

## My Diagnostic Approach

A systematic, proven methodology that moves from problem identification to validated solution deployment, ensuring thorough resolution and long-term stability.

- **Isolate & Replicate** — I systematically isolate the problem area and create a reliable way to replicate the issue.
- **Root Cause Analysis** — I use a combination of logging, monitoring tools, and code analysis to dig beyond the symptoms and find the fundamental cause.
- **Formulate & Test Solution** — I develop a hypothesis for a solution, implement it in a controlled environment, and rigorously test it.
- **Deploy & Verify** — Once validated, the fix is deployed to production, and I monitor the system to verify that the problem is resolved and no new issues have been introduced.

## Common Scenarios I Address

From performance bottlenecks to elusive bugs, I tackle a wide range of technical challenges with proven diagnostic methods and scalable solutions.

- **Application Performance Degradation** — Handling sudden performance drops and optimizing code, databases, and infrastructure.
- **Intermittent & Hard-to-Trace Bugs** — Advanced debugging techniques for complex software issues.
- **Database Query Optimization** — Efficient database queries to improve performance and reduce load times.
- **Scaling Challenges During High-Traffic Events** — Building scalable systems to handle increased user load and traffic.
- **Post-Incident Security Hardening** — Enhancing security measures after a security breach to prevent future incidents.

## The Value of Expert Intervention

Expert problem-solving delivers immediate impact while building long-term system resilience and operational efficiency.

- **Immediate Problem Resolution** — Swiftly resolving critical technical issues to keep your business running smoothly.
- **Preventative Measures** — Implementing measures to prevent future issues, strengthening your system's resilience.
- **Cost Efficiency** — Saving you time and money in the long run by addressing issues efficiently and effectively.

## Ready to discuss your Technical Problem Solving?

Let's explore how Technical Problem Solving initiatives can move faster with on-demand CTO leadership.

## Frequently Asked Questions

Formal responses to the most common escalation, reliability, and remediation questions.

### How do you triage a critical incident when telemetry is incomplete or untrustworthy?
We begin with a containment sprint that mirrors practices from the [Google SRE Workbook incident guidance](https://sre.google/workbook/incident-response/). Engineers and operators share one communication channel while I build a lightweight incident timeline. We immediately instrument temporary probes, capture packet traces, and snapshot affected services so evidence is preserved. Within the first hour we split the team into three roles: containment, diagnostics, and communications. Containment focuses on customer impact (feature flags, traffic shedding, read-only modes). Diagnostics pursue hypotheses, log every test, and rule out noise. Communications keeps executives, customers, and legal informed with timestamped updates. Even with imperfect telemetry, this structure stops the bleeding and produces the raw data we will later harden into dashboards or tracing pipelines. Once the incident is stable we retroactively codify metrics, logging, and alert thresholds so the system never becomes blind again.
### What timelines should leadership expect for an emergency stabilization engagement?
Most engagements follow a 30-60-90 cadence. The first 30 hours are devoted to containment, root-cause identification, and tactical fixes that keep the business online. The next 60 hours focus on closing systemic gaps such as instrumentation, on-call hygiene, regression suites, and documentation. The 90-hour mark delivers strategic reforms—architecture refactors, platform upgrades, or contract renegotiations—that prevent recurrence. All three phases are tracked in a single remediation plan that executives review twice per week. If the incident intersects with regulated workloads like those handled in [Fintech Innovation](https://zaitsevartem.com/fintech), we align milestones with audit evidence requirements so remediation doubles as compliance preparation. When problems touch AI-heavy components, I coordinate closely with the data science leadership to keep model retraining, data hygiene, and explainability efforts synchronized with infrastructure repairs.
### How is regulatory and commercial context incorporated into purely technical fixes?
I treat every remediation as both an engineering and a governance program. Early in the engagement we map contractual SLAs, customer commitments, and regulatory obligations using frameworks like the [NIST Computer Security Incident Handling Guide](https://csrc.nist.gov/publications/detail/sp/800-61/rev-2/final). Each root cause is then tagged with its commercial blast radius: lost revenue, regulatory penalties, or ecosystem impact. This prevents teams from optimizing purely for technical purity while ignoring contractual risk. When the issue overlaps with blockchain or tokenized flows, I pull specialists from [Blockchain Solutions](https://zaitsevartem.com/blockchain) to ensure ledger integrity, custody, and compliance questions are addressed alongside code fixes. The output is a remediation register that legal, finance, and engineering can all read, ensuring everyone agrees on what must be delivered, when, and why.
### How do you preserve knowledge so the team does not regress after the crisis?
After containment I facilitate post-incident reviews modeled on [Stripe’s postmortem culture](https://sre.google/sre-book/postmortem-culture/). The sessions produce actionable narratives, not blame. Each document includes a detailed timeline, mitigations, remaining risks, and owner-assigned follow-up tasks. We then convert the learnings into durable assets: runbooks linked directly from alerts, regression test suites added to CI/CD, and onboarding modules for future hires. If the organization is scaling rapidly, I coordinate with [Tech Staffing & Team Building](https://zaitsevartem.com/staffing-team-building) to embed these materials in the hiring and ramp-up process. The goal is institutional memory—future engineers should be able to search the knowledge base, understand past incidents, and avoid repeating them without needing veterans to retell the story.
### How do you coordinate with parallel initiatives so fixes do not block product momentum?
Problem-solving rarely happens in isolation. I run a dependency board that tracks every remediation task alongside in-flight projects such as growth experiments, cloud migrations, or AI features. When engagements overlap with the [AI & Machine Learning offering](https://zaitsevartem.com/ai-ml), I create shared milestones and cross-team demos so nobody is surprised by system freezes or schema changes. Externally, I align updates with partners and customers, referencing expectations from sources like the [Stripe incident communication guide](https://sre.google/sre-book/postmortem-culture/) so stakeholders receive clear, timely information. This coordination ensures that stabilization work accelerates rather than delays the broader roadmap.

## Problem-solving articles

Architecture, performance, and incident resolution insights.