HackerNoonAI · Engineering
AI Is Changing DevOps, but Production Access Is Still the Line
Three filters, blast radius, rollback and visibility, decide which IoT DevOps tasks AI may touch. Production access stays human.
Writing
Writing
Ideas on AI, engineering, leadership, technology businesses and complex systems, published elsewhere and collected here.
2026
- Fast CompanyLeadership
4 management lessons for scaling your team
What broke when his company grew from 10 to 90 people, and the four management shifts that fixed it.
- ForbesAI · Leadership
The False Expertise Trap: How To Keep Your Team Thinking In The AI Era
AI erodes the entry-level work that builds engineering judgment. Four practices to keep juniors thinking instead of parroting output.
- Fast CompanyLeadership
Your team needs a supportive manager, not yoga and meditation
Why burnout is a management problem, with the story of keeping a 90-person team working after the invasion of Ukraine.
- Towards Data ScienceAI · Industrial Technology · Engineering
How AI Tools Generate Technical Debt in IoT Systems, and What to Do About It
Four ways AI assistants create IoT technical debt, backed by studies, and three disciplines to contain it: review, no-go zones, refactoring.
- HackerNoonAI · Engineering
5 Tasks Where AI Agents Deliver Real Value for Development Teams
Where a 90-developer IIoT team gets real value from AI agents (prototyping, tests, routine code) and why ISO 27001 blocks autonomy.
- Mind the ProductLeadership · Business
Training developers as an investment: How technical leaders can identify real ROI
Three signals to invest in developer training, how to tie it to business goals, and how to measure ROI, with a $10,000-a-month cloud saving as the example.
- Fast CompanyAI · Leadership
How AI is quietly exhausting you, and what to do about it
Why AI tooling tires engineering teams through micro-decisions and tool sprawl, and how to adopt it without burnout.
- SD TimesAI · Business
The trap of using external AI services: Is your business doomed, or is there a way out?
Why Shadow AI, Copilot-style vulnerabilities and automation bias threaten businesses, and four controls from corporate LLM access to data residency.
- IoT For AllAI · Industrial Technology
Hype or Inevitable Future: Will LLMs Transform Industrial IoT?
Where LLMs fit in Industrial IoT: interpreting ML predictive-maintenance output, RAG over manuals, protocol interoperability. Humans decide.
- Unite.AIAI · Engineering
5 Steps to Successfully Integrate AI Agents into Product Development
Five steps from a real Copilot Agent rollout: baseline KPIs, CI/CD embedding, prompt training, an AI policy, and scaling.
- ForbesLeadership
How Leaders Can Identify And Bridge Their Team's Skills Gaps
How to spot a skills gap early (quality drops, lead overload) and close it with 360 reviews, development plans and mentoring.
- Fast CompanyLeadership
5 soft skills that set exceptional leaders apart
Five leadership skills AI cannot replace, illustrated with situations from running a 90-person engineering team.
2025
- ForbesLeadership
Five Principles For Building An Effective Multicultural Team
Five practices for Ukraine, US and Europe teams: a written communication policy, agreed progress reporting, audience-adapted presentations, a knowledge base.
- Fast CompanyLeadership
Why teams stop developing, and how to get them moving again
A concrete cadence for developer growth: tests, sprint experiment days, monthly clubs, and how to diagnose a stalled engineer.
- HackerNoonEngineering · Business
7 Persuasive Ways CTOs Can Get Stakeholders Onboard With Code Refactoring
How to pitch refactoring to executives as ROI: cost the legacy burden, cite Southwest and Netscape, pilot one module first.
- ForbesLeadership
How IT Leaders Can Find The Balance Between Control And Trust, And Start Delegating Effectively
Why technical leaders over-control, a five-step delegation system, and the team that shrank a 16 TB database to 1 TB on its own.
- Unite.AIAI · Engineering
AI Infrastructure in the Cloud: 5 Signs Your System Isn't Ready to Scale
Five readiness checks for scaling cloud AI: data quality thresholds, elastic GPU capacity, MLOps orchestration, security KPIs, monitoring.
- Towards Data ScienceAI · Industrial Technology · Data
Why AI Still Can't Replace Analysts: A Predictive Maintenance Example
Why predictive maintenance still needs vibration analysts: scarce matched training data, missing operational context, noisy sensors.
- HackerNoonIndustrial Technology · Data · AI
Mathematics, Big Data, and AI: How Predictive Maintenance Works Using a Bearing as an Example
How a PdM pipeline turns bearing vibration into FFT spectra and alerts, plus six infrastructure steps an IT team must prepare.
- ForbesIndustrial Technology · Data
Predictive Maintenance: Five Ways To Enhance Data Quality
How a predictive-maintenance team keeps AI diagnostics accurate: field-experienced analysts, three time zones, two-tier triage, custom tooling.
- HackerNoonData · Business
5 Major Business Mistakes When Working with Big Data: Lessons from a Company Managing 16 TB of Data
Five big-data mistakes from running a 16 TB, ten-billion-records-a-day platform: retention, quality, uncapped autoscaling, surplus fields, wrong database.
- Embedded Computing DesignIndustrial Technology · Data
What Big Data Can Reveal About Your Equipment: The Case of an Electric Motor
Per-sensor fault signatures for an electric motor: vibration, temperature, current and motion amplification, with thresholds and six implementation steps.
- ForbesLeadership · Business
How To Find And Retain Product-Minded Specialists
Four traits that mark product-minded engineers, and the retention practices behind five-to-eight-year average tenure.
- Automation.comIndustrial Technology · Data
Analyzing Production Data to Eliminate Downtime
A role-by-role plan for starting production data analytics and predictive maintenance, with the barriers and the expected downtime reduction.
- IoT For AllIndustrial Technology
From Vibrometers to Sensors, Cloud, and AI: How Modern Predictive Maintenance Works
From Waddington's RAF bombers to a four-stage IIoT pipeline: how modern predictive maintenance works and why it is bought as a service.
- ForbesIndustrial Technology · Data
How IIoT And Big Data Are Transforming Equipment Maintenance
The business case for IIoT predictive maintenance: downtime costs, ROI, implementation challenges, and build versus buy.
- HackerNoonEngineering · Data
How to Speed up Your Database so Your Business Doesn't Lose Money
Why queries slow down at IIoT scale, and how a PdM platform cut latency from 10 s to 2 s by moving to TimescaleDB.
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