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Blog · AlterSquare

Blog

Notes from the build.

Field notes on shipping AI-native systems with human engineering judgement: architecture, modernisation, automation, and the tradeoffs in between.

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Blog·09 Feb 2026·20 min read

Designing Trust and Feedback in AI-Driven User Interfaces

Design AI interfaces that build calibrated trust through transparency, user control, feedback loops, and ethical safeguards.

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Blog·07 Feb 2026·24 min read

How Teams Incrementally Modernize Large Frontend Codebases

Step-by-step guide to modernize large frontend codebases without full rewrites. Covers assessment, metrics, modular refactoring, modern frameworks, and performance.

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Blog·06 Feb 2026·17 min read

Why AI Outputs Need Domain Context to Be Useful

AI needs domain-specific context-data, RAG, expert review, and testing-to avoid hallucinations and deliver reliable, actionable outputs for startups.

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Blog·04 Feb 2026·15 min read

Why AI Adoption Is Harder in Domain-Heavy Software

Domain-heavy industries struggle with AI due to scarce, fragmented data, complex workflows, and bias; solutions include domain data, RAG, custom models, and human oversight.

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Blog·03 Feb 2026·15 min read

Why Frontend Modernization Often Fails in Enterprise Projects

Why enterprise frontend modernizations fail-misaligned teams, technical debt, and big‑bang rewrites-and how phased, modular strategies cut risk and cost.

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Blog·02 Feb 2026·18 min read

Frontend Modernization Without Rewriting Everything

Step-by-step tactics (Outside-In, Inside-Out, Strangler Fig), component libraries, performance fixes, and micro frontends to modernize without full rewrites.

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Blog·31 Jan 2026·17 min read

Why Legacy Frontends Are Harder to Modernize Than Backends

Explains why updating legacy frontends is harder than backends, covering UI coupling, performance risk, migration strategies, and KPIs.

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Blog·30 Jan 2026·12 min read

Why AI Architecture Decisions Are Hard to Reverse

Early AI architecture choices often lock systems into technical debt, tangled data pipelines, and legacy dependencies-use audits, modular design, and planning to avoid costly rewrites.

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Blog·28 Jan 2026·22 min read

When AI Belongs in the Frontend vs the Backend

Compare frontend and backend AI trade-offs - latency, privacy, cost, and scalability - and learn when to run models on device or on servers.

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Blog·27 Jan 2026·17 min read

Why AI Systems Create New Forms of Technical Debt

How AI creates opaque models, data drift, and integration failures that add costly technical debt - and practical ways to manage it.

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Blog·26 Jan 2026·15 min read

Where AI Fits (and Doesn’t) in Product Architecture

AI excels at ambiguous, unstructured, and multi-step workflows; use traditional engineering for predictable, security‑critical, and CRUD tasks.

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Blog·24 Jan 2026·21 min read

What Changes in Frontend Architecture When AI Enters the Product

AI makes frontends handle model downloads, split AI/UI state, dynamic design systems, edge caching, and strict security.

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