Entexis Insights

Perspectives on AI, SaaS,
Software & Domain.

Software decisions compound. A pricing model picked in week three of a SaaS launch sets the unit economics for years. A custom CRM that fits your sales motion saves a hire by month three. An AI layer scoped well in month one delivers measurable lift by quarter one. Three solid pieces from this archive should remove at least a week of guessing from the next decision in front of you.

Walk in mid-decision and walk out with a sharper view of it. Whether you are weighing build vs buy, picking a framework, scoping an AI layer that looked easy in the demo, redesigning a UX flow that loses users at step three, or deciding whether to keep patching a migration that quietly grew over months. The next decision should feel less guesswork-shaped.

Topics here range across AI implementation, SaaS strategy, custom CRM, HR tech, e-commerce, software engineering, data and analytics, design and UX, and domain-specific software for financial markets, TradingView, and real estate. Plus inside stories: short reads on what we learned building real products for real businesses.

Latest Insights

Latest
Insights

25
Design & UX

Where Generative UI Wins and Where Traditional Front-End Still Beats It

Generative UI shines for long-tail user needs. Traditional front-end still wins for happy paths, marketing pages, and brand-sensitive landings. Here is where each fits.

26
Artificial Intelligence

What an AI Procurement Assistant Does: Supplier Proposals, Scoring Suppliers, and Renewals

Procurement teams handle many supplier contracts but read only the top 20 carefully. The AI assistant reads every proposal, scores every supplier, and watches every renewal.

27
Artificial Intelligence

What an AI Engineering Assistant Does Beyond Coding Tools: Incidents, Code Review, and Deployments

Coding assistants help write code. AI engineering assistants handle the operational work: incidents, code review, dependency risks, and deployment coordination.

28
Artificial Intelligence

What an AI Product Management Assistant Does: Feedback, Feature Requests, and Roadmap Planning

Product managers read 5-20% of customer signals because they have no time for the rest. The AI assistant reads everything and pulls out the themes with source links.

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Thinking on SaaS, CRM &
Domain-Led Software.

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