Solwey

08/27/2026

One of the biggest misconceptions about AI in product development is that it helps teams build faster.

It does. But that's not where the biggest value comes from.

The real advantage is that AI helps teams learn faster.

Too many organizations have optimized product delivery while neglecting product discovery. They ship features efficiently, yet many of those features never deliver meaningful customer value. The problem isn't ex*****on. It's building the wrong thing.

AI can dramatically accelerate customer research, analyze thousands of support tickets and user conversations, identify recurring pain points, generate prototypes in hours, and help teams validate ideas before engineering resources are committed.

But AI doesn't replace product judgment.

It amplifies whatever discovery process already exists. If teams are asking the wrong questions, AI helps them move in the wrong direction faster. If they're grounded in customer needs and disciplined experimentation, AI compresses the time between insight and validation.

More in our blog: https://solwey.com/blog/what-is-ai-powered-product-discovery-and-how-can-it-reduce-the-risk-of-building-the-wrong-features

08/25/2026

Most AI projects never make it past the pilot phase. Yours shouldn't.

08/20/2026

When people talk about AI in manufacturing, the conversation usually starts with automation.

It should start with quality.

One of the most expensive problems manufacturers face isn't finding defects - it's how long it takes to understand them. By the time teams connect warranty claims, service notes, production records, supplier data, and sensor logs, months may have passed. Meanwhile, the same issue continues to make its way into the field, driving up warranty costs and eroding customer trust.

This is where AI creates real business value.

Not by replacing quality engineers, but by accelerating the work that slows them down. AI can detect early warning signals, connect data across disconnected systems, identify likely root causes, and surface the issues that matter before they become costly.

That changes the role of quality teams. Instead of spending weeks collecting evidence, they can spend their time making decisions, implementing corrective actions, and improving products.

And in today's market, the speed at which you respond to customer issues may become one of your strongest competitive advantages.

More in our blog: https://solwey.com/blog/how-is-ai-changing-manufacturing-quality-management

08/18/2026

For the past few years, the AI conversation has been dominated by chatbots, copilots, and productivity tools.

According to a new report from Goldman Sachs, shared exclusively with Axios, the next AI boom won't happen on our screens. It will happen in the physical economy - factories, utilities, mines, warehouses, and industrial operations.

We couldn't agree more.

The biggest opportunity for AI isn't helping employees write faster emails or summarize documents. It's helping businesses run better.

Imagine AI that identifies production bottlenecks before they impact output, optimizes scheduling based on real-time constraints, coordinates maintenance across facilities, or orchestrates work across ERP, MES, CRM, and operational systems without manual intervention.

That's where the next wave of productivity gains will come from. The future of enterprise AI isn't just digital. It's operational.

Great article:

AI has made technology companies increasingly dependent on non-tech firms.

08/13/2026

One of the biggest mistakes B2B startups make is leading with their product.

Customers don't buy technology because it's impressive. They buy because it solves a problem they care about, reduces risk, and delivers a measurable outcome.

Founders spend months perfecting features, while buyers are asking completely different questions:

-Will this fit into the way we work?
-Can we trust this company?
- Is the ROI worth the investment?
-Will this make my job easier - or more complicated?

A great product is essential. A great go-to-market strategy is what turns it into a business.

More in our blog: https://solwey.com/blog/a-practical-guide-to-avoid-go-to-market-failure-from-first-principles-to-ex*****on

08/11/2026

AI success isn't just about building models. It's about building the right process.

08/06/2026

The conversation around AI-generated code is missing the bigger picture.

The question isn't whether AI will replace software engineers. It's whether AI is changing the economics of building software.

For years, businesses accepted expensive SaaS subscriptions because building custom software was too costly and too slow. Today, AI-assisted development is changing that equation. Building software tailored to your business is becoming faster, more accessible, and, in many cases, more economical over the long term.

That doesn't mean every company should build everything from scratch.

It does mean leaders should start questioning whether they're paying for platforms filled with features they'll never use while forcing their teams to adapt to someone else's workflow.

The biggest misconception is that AI makes software development "automatic." It doesn't. AI accelerates development, but architecture, security, scalability, and business context still require human judgment.

AI isn't replacing software strategy. It's making good software strategy more valuable than ever.

More in our blog: https://solwey.com/blog/knowing-when-to-build-the-signal-that-custom-software-makes-more-sense-than-another-saas-subscription

08/04/2026

The conversation around AI has officially shifted.

For the past two years, companies have been asking, "How can AI help us?" Today, the question is becoming, "How can AI do the work?"

A recent article referencing Gartner's latest research highlights just how quickly agentic AI is moving into the enterprise. By the end of 2026, Gartner expects 40% of enterprise applications to embed task-specific AI agents, yet more than 40% of agentic AI projects are also expected to be cancelled by 2027.

Why? Because building an AI agent isn't the hard part anymore. Turning it into measurable business value is.

The companies seeing real results aren't trying to automate everything at once. They're focusing on high-value workflows, connecting AI securely to business systems, putting governance in place, and measuring outcomes instead of activity.

Enterprise AI shouldn't stop at generating answers. It should execute workflows, orchestrate work across systems, and help businesses move faster with less manual effort. That requires more than a powerful model. It requires the right architecture, trusted data, secure integrations, and governance from day one.

Great article: https://economictimes.indiatimes.com/ai/ai-insights/how-agentic-ai-is-growing-and-how-enterprises-can-make-the-best-of-it/articleshow/132109550.cms

07/30/2026

Customers don't care why your application is slow. They care that it is slow.

One of the biggest challenges in operating modern software platforms is distinguishing between problems caused by the application itself and problems caused by the underlying infrastructure. At scale, that's far more difficult than it sounds. Thousands of services, changing traffic patterns, infrastructure updates, and millions of requests can make root cause analysis incredibly complex.

What's interesting is that reliability isn't just about uptime anymore.

A system can be available 99.99% of the time and still deliver a poor customer experience if performance becomes inconsistent.

Users don't compare your application to an industry benchmark. They compare it to how it performed yesterday. Even small changes in latency can erode trust long before traditional monitoring tools detect a problem.

That's why the future of platform reliability isn't just measuring whether systems are up or down.

It's understanding when the customer experience starts to change - and identifying those signals before customers need to tell you something is wrong.

More in our blog: https://www.solwey.com/posts/when-my-app-is-slow-becomes-a-platform-problem

07/28/2026

Most AI tells you what to do. The best AI does it with you.