DEV Community: Dev Sk

The Hidden Cost of AI is Now Governance

Dev Sk — Mon, 02 Nov 2026 15:00:00 +0000

For a long time, I thought the biggest cost of AI was the model.
Training costs. Inference costs. Infrastructure costs.

But the more I see organizations move from AI experimentation to AI at scale, the more I realize something else is becoming far more expensive:
Governance.

I recently came across The Hidden Cost of AI is Now Governance, and it highlights a challenge many companies are only beginning to understand.

Source: https://www.itpro.com/technology/artificial-intelligence/the-hidden-cost-of-ai-is-now-governance

Over the past two years, most conversations around AI have focused on:
✅ Which model is best
✅ Which vendor to choose
✅ How to reduce costs
✅ How to improve accuracy
But as AI adoption accelerates, a different question is emerging:
How do we govern AI responsibly at scale?
Because deploying AI is the easy part.
Managing it is where things get complicated.
Organizations now need to think about:
🔹 Data privacy
🔹 Regulatory compliance
🔹 Model transparency
🔹 Human oversight
🔹 Security risks
🔹 Auditability
🔹 Bias and accountability
What stood out to me is that governance is no longer a "future problem."
It's a today's problem.
The reality is that every new AI application introduces another layer of oversight, policies, monitoring, and risk management.
And unlike infrastructure costs, governance costs don't disappear as models become cheaper.
In many cases, they grow.
That's why I believe the next competitive advantage won't come from simply adopting AI faster.
It will come from building the processes, controls, and trust frameworks that allow AI to scale safely.
The companies that win won't just have the smartest models.
They'll have the most trusted AI ecosystems.
As AI professionals, we're entering a new phase:
Less focus on "Can we build it?"
More focus on "Can we govern it responsibly?"

💭 What's the biggest challenge your organization faces with AI adoption today?

Is it the technology itself... or the governance around it?
👇 I'd love to hear your thoughts.

ArtificialIntelligence #AI #AIGovernance #ResponsibleAI #GenerativeAI #EnterpriseAI #AIStrategy #TechnologyLeadership #DigitalTransformation #CyberSecurity #DataGovernance #RiskManagement #Compliance #FutureOfAI #Innovation

One piece of career advice completely changed

Dev Sk — Fri, 30 Oct 2026 15:00:00 +0000

One piece of career advice completely changed how I think about growth in tech:

Hunger beats tenure.
Not experience. Not titles. Not years in the industry.
Hunger.

I recently read Hunger Beats Tenure: Advice for Junior Engineers, and it reinforced something I've observed throughout my career.

Source: https://felixrieseberg.com/hunger-beats-tenure-advice-for-junior-engineers

Early in our careers, it's easy to believe that success comes from simply spending enough years in the industry.
But the engineers who stand out aren't always the ones with the longest resumes.

They're the ones who are relentlessly curious.
The ones asking questions.
The ones building projects after work.
The ones experimenting with new technologies before they're required to.
The ones who stay uncomfortable because that's where learning happens.
I've seen junior engineers with less than two years of experience make bigger leaps than people who had been in the industry for a decade.
The difference wasn't intelligence.
It wasn't talent.
It was ownership of their growth.

In a world where AI is changing software development faster than ever, tenure alone has a shorter shelf life than it used to.
What matters increasingly is:

✅ How quickly you learn
✅ How adaptable you are
✅ How willing you are to explore unfamiliar territory
✅ How often you turn curiosity into action

The reality is that nobody is coming to manage your career for you.
Your manager can guide you.

Your company can support you.
But your growth is still your responsibility.
That's why I believe the most valuable skill for engineers today isn't mastering a specific framework or programming language.
It's maintaining the hunger to keep learning.
Technology will continue to change.
That mindset will always compound.
If you're early in your career, focus less on counting years and more on building momentum.
The years will take care of themselves.

💭 What's one thing you've learned that accelerated your growth as an engineer?

I'd love to hear your advice for the next generation of developers. 👇

SoftwareEngineering #CareerGrowth #EngineeringLeadership #Programming #Developers #TechCareers #LearningAndDevelopment #ArtificialIntelligence #SoftwareDevelopment #CareerAdvice #TechLeadership #GrowthMindset #Engineering #DeveloperCommunity #FutureOfWork

Cognitive Mercantilism

Dev Sk — Wed, 28 Oct 2026 15:00:00 +0000

Lately, I've been thinking about a question that feels increasingly relevant in the AI era:

What happens when cognition becomes the world's most valuable economic resource?

After reading Cognitive Mercantilism, it challenged how I think about competition in the age of AI.

Source: https://contraptions.venkateshrao.com/p/cognitive-mercantilism

For centuries, nations competed for land, natural resources, manufacturing power, and capital.

Today, we're entering a different game.
A world where the most valuable asset may not be oil, factories, or even data.

It may be cognitive capacity.

The ability to generate ideas. The ability to reason. The ability to make decisions. The ability to amplify human intelligence through AI.
What struck me most is that we're no longer just building tools.
We're building systems that can increasingly participate in knowledge work itself.

And that changes the economics of value creation.
As AI capabilities expand, the competitive advantage of organizations may come from:

✅ How effectively they combine human and AI intelligence
✅ How quickly they can transform knowledge into action
✅ How well they can scale decision-making
✅ How they create unique cognitive advantages that are difficult to replicate

This made me rethink a common assumption.
Maybe the AI race isn't just about having the best models.
Maybe it's about creating the strongest ecosystem for producing, directing, and compounding intelligence.

The companies that win may not be the ones with the most data.
They may be the ones that best orchestrate human expertise and AI capabilities together.

That's a very different game.

And honestly, I think we're only beginning to understand its implications.
What's your perspective?

Are we moving toward an economy where cognitive capability becomes the primary source of competitive advantage?

👇 I'd love to hear how you're thinking about this shift.

ArtificialIntelligence #AI #GenerativeAI #FutureOfWork #DigitalTransformation #Innovation #AIEconomy #KnowledgeWork #AgenticAI #AIAgents #TechnologyLeadership #BusinessStrategy #FutureOfAI #Leadership #TechTrends

NCM vs LLM

Dev Sk — Mon, 26 Oct 2026 09:30:00 +0000

A few months ago, I thought the future of AI was straightforward:
Build bigger models. Train on more data. Get better results.
Now, I'm not so sure.
The more I read about AI advancements and the more I use these systems daily, the more I feel we're hitting a point where simply predicting the next word isn't enough.
That's why Next Concept Modeling (NCM) caught my attention.
Most of today's AI systems are powered by Large Language Models (LLMs).
Their strength is predicting the next token, the next word, based on patterns they've seen before.
And to be fair, they're incredibly good at it.
But when humans think, we don't process life one word at a time.
We think in ideas.
We connect concepts.
We build mental models.
That's what makes NCM interesting.
Instead of asking:
👉 "What's the next word?"
It asks:
👉 "What's the next concept?"
That may sound like a small change.
I think it's a massive one.
Imagine AI that understands the intent behind a discussion, follows the flow of ideas more naturally, and reasons at a higher conceptual level instead of continuously predicting the next token.
Will NCM replace LLMs?
I don't think so.

In fact, I believe the next generation of AI will be built on both.
🔹 LLMs for language fluency
🔹 NCMs for conceptual understanding
🔹 Agents for action and execution

The winners in AI may not be the systems that generate the most text.
They may be the systems that understand meaning the best.
I'm genuinely curious where this goes over the next few years.
Are we witnessing the next evolution after LLMs, or is token prediction still the path forward?
What's your take?

👇 I'd love to hear what developers, AI practitioners, and tech leaders think.

ArtificialIntelligence #AI #GenerativeAI #LLM #NextConceptModeling #MachineLearning #AIAgents #AgenticAI #FutureOfAI #DeepLearning #DataScience #TechInnovation #EmergingTechnology #AITrends #DigitalTransformation

🚀 Cloudflare Introduces Clairic: A New Type of AI Model for Data Extraction

Dev Sk — Wed, 21 Oct 2026 09:30:00 +0000

Most AI conversations today revolve around generating text. But what if you don't need text at all?

Cloudflare has introduced Clairic, a new "System One" extraction model designed to extract, compute, estimate, and forecast structured values from unstructured data such as invoices, emails, receipts, and reports. Unlike traditional LLMs, Clairic focuses on returning typed values directly instead of generating paragraphs of text.

🔑 Why This Matters

✅ Faster than traditional LLM workflows
✅ Lower cost for structured data extraction tasks
✅ Returns typed outputs like dates, amounts, durations, lists, and forecasts
✅ Designed for real-world business use cases such as invoice processing, delivery tracking, and cost estimation

What I find most interesting is the growing trend toward specialized AI models. Instead of using one large model for everything, we're beginning to see purpose-built AI systems that can solve specific problems more efficiently.

💡 The future of AI may not be bigger models, but smarter and more focused ones.

🔗 Read the full article:
https://blog.cloudflare.com/clairic-extraction-model/?utm_source=tldrnewsletter

💬 What do you think?
Will specialized AI models like Clairic become the preferred choice for enterprise workflows, or will general-purpose LLMs still dominate most use cases?

ArtificialIntelligence #AI #Cloudflare #MachineLearning #GenerativeAI #LLM #DataExtraction #WorkersAI #AIEngineering #EnterpriseAI #DataEngineering #Automation #AIAgents #DeveloperTools #TechInnovation #FutureOfAI #SoftwareEngineering #AIProducts #TechTrends #AgenticAI

🛠️ Are Harnesses Worth the Cost?

Dev Sk — Mon, 19 Oct 2026 09:30:00 +0000

Martin Fowler’s latest article dives into the trade-offs of building test harnesses — those scaffolding systems that make testing easier but come with their own overhead.

🔑 Key Insights
Harnesses add structure → They simplify complex testing scenarios and improve reliability.

Cost vs. benefit → Building and maintaining harnesses requires effort, but the payoff can be significant in long-term quality.

Team alignment → Harnesses encourage consistent practices across engineering teams.

Strategic decision → Not every project needs them — the value depends on scale, complexity, and future growth.

💡 Takeaway: Harnesses aren’t free, but when used wisely, they can be a powerful investment in sustainable software quality.

👉 Read the full article: https://martinfowler.com/articles/are-harnesses-worth-the-cost.html

SoftwareEngineering #TestingStrategies #CodeQuality #DeveloperExperience #EngineeringCulture #SystemDesign #TechLeadership #AgileDevelopment #DevCommunity #Productivity #TechInnovation

📊 Inference: The Most Important Market in Software

Dev Sk — Fri, 16 Oct 2026 09:30:00 +0000

Tom Tunguz makes a compelling case that the future of software isn’t just about building models — it’s about inference. The ability to run models efficiently, at scale, and in real-time is quickly becoming the defining competitive edge for enterprises.

🔑 Key Insights
Inference at scale → Running models in production is where real value is created.

Cost & efficiency → Optimizing inference pipelines directly impacts margins and accessibility.

Market shift → Companies that master inference will lead the next wave of AI-driven innovation.

Strategic importance → Inference isn’t just technical — it’s a business-critical capability.

💡 Takeaway: Training models may grab headlines, but inference is where the real market battle will be fought.

👉 Read the full article: https://tomtunguz.com/inference-is-the-most-important-market-in-software

AI #Inference #ArtificialIntelligence #MachineLearning #TechInnovation #SystemDesign #FutureOfWork #DeveloperExperience #EngineeringCulture #BusinessStrategy

⚡ Improving Site Performance by Shipping More CSS

Dev Sk — Wed, 14 Oct 2026 09:30:00 +0000

GitHub’s engineering team recently shared an interesting optimization story: instead of reducing CSS, they actually shipped more of it — and the result was faster page loads and better performance.

🔑 Key Insights
Counterintuitive approach → More CSS can mean fewer runtime calculations, leading to speed gains.

Architecture optimization → Smart bundling and delivery strategies matter as much as code size.

User experience first → Performance improvements directly translate into smoother interactions.

Engineering culture → Sometimes the best solutions challenge conventional wisdom.

💡 Takeaway: Performance tuning isn’t always about cutting down — it’s about making smarter architectural choices that scale.

👉 Read the full article: https://github.blog/engineering/architecture-optimization/improving-site-performance-by-shipping-more-css

Suggested Hashtags

GitHub #WebPerformance #CSS #FrontendDevelopment #SystemDesign #PerformanceTuning #DeveloperExperience #EngineeringCulture #TechInnovation #WebOptimization

🚀 Goodbye to the Hard Parts That Never Mattered

Dev Sk — Mon, 12 Oct 2026 09:30:00 +0000

Jake Goldsborough’s latest blog is a refreshing reminder that not every “hard part” in software development is worth obsessing over. Sometimes, the industry gets caught up in complexity that doesn’t actually move the needle for users or teams.

🔑 Key Insights
Focus on impact → The hardest problems aren’t always the most important ones.

Simplification wins → Cutting through noise helps teams deliver faster and smarter.

User-first mindset → What matters is solving problems that create real value.

Letting go → Saying goodbye to unnecessary complexity is a sign of maturity, not weakness.

💡 Takeaway: Engineering isn’t about proving how tough a problem is — it’s about solving the right problems that matter.

👉 Read the full article: https://jakegoldsborough.com/blog/2026/goodbye-to-the-hard-parts-that-never-mattered/

SoftwareEngineering #DeveloperExperience #EngineeringCulture #TechLeadership #SystemDesign #CleanCode #Productivity #Innovation #DevCommunity #TechStrategy

🤝 Human-AI Partnerships: It’s About Alignment, Not Just Capability

Dev Sk — Wed, 30 Sep 2026 09:30:00 +0000

Sean Goedecke’s latest blog challenges a common assumption: AI partnerships aren’t only about boosting raw capability — they’re about ensuring alignment with human goals, values, and context.

🔑 Key Insights
Capability ≠ alignment → AI can be powerful, but without alignment, it risks going off-track.

Partnership mindset → Humans provide direction, context, and judgment; AI provides scale and speed.

Trust & responsibility → True collaboration means designing systems that reflect human intent.

Future of AI → Success will depend less on “how smart” AI is, and more on how well it aligns with us.

💡 Takeaway: The real challenge isn’t building more capable AI — it’s building AI that works with us, not just for us.

👉 Read the full article: https://www.seangoedecke.com/human-ai-partnerships-are-for-alignment-not-capability

AI #HumanAIInteraction #AgenticAI #ArtificialIntelligence #FutureOfWork #TechLeadership #SystemDesign #Innovation #AIAlignment #EngineeringCulture

🛠️ Fallow Tools — Building Smarter Workflows

Dev Sk — Mon, 28 Sep 2026 13:13:57 +0000

Fallow Tools is designed to help developers and teams streamline their processes with clear documentation, practical utilities, and workflow-first design. It’s not just about tools — it’s about enabling better collaboration and productivity.

🔑 Key Highlights

Developer-focused → Simple, well-documented utilities that reduce friction.

Workflow-first → Tools built to integrate seamlessly into real-world projects.

Scalable design → From small teams to enterprise setups, flexibility is baked in.

Open & accessible → Documentation that empowers rather than overwhelms.

💡 Takeaway: Great tools don’t just solve problems — they make solving problems easier. Fallow Tools is a step toward building systems that work with developers, not against them.

👉 Explore here: https://fallow.tools/docs

DeveloperTools #Productivity #WorkflowAutomation #TechInnovation #SoftwareEngineering #SystemDesign #DevCommunity #OpenSource #EngineeringCulture #TechTips

🤖 Analyzing JEV — A New AI Model

Dev Sk — Fri, 25 Sep 2026 09:30:00 +0000

Senko’s latest blog takes a closer look at JEV, a new AI model that’s stirring conversations in the developer and research community. The piece explores how JEV differs from existing models, its potential applications, and the challenges it raises for the future of AI.

🔑 Key Insights
Fresh perspective → JEV introduces unique design choices worth studying.

Performance trade-offs → Understanding where it excels and where it struggles.

AI ecosystem impact → New models like JEV push innovation and force us to rethink assumptions.

Critical analysis → It’s not just hype — the article digs into strengths and limitations.

💡 Takeaway: Every new AI model is more than just technology — it’s a chance to reflect on how we build, evaluate, and adopt intelligent systems.

👉 Read the full article: https://blog.senko.net/analyzing-jev-a-new-ai-model?pk_campaign=rss-feed

AI #ArtificialIntelligence #AgenticAI #MachineLearning #TechInnovation #SystemDesign #DeveloperExperience #AIResearch #FutureOfAI #EngineeringCulture