Danish engineer Christian Rasmussen, 42, has founded and sold three companies — Assemblage to Cisco, Roger to FleetCor, and House of Wonder to a private equity fund — each born from sharp observation of flawed experiences and a drive to build better systems.
The article argues AI's initial easy adoption in high-tolerance, online creative work is saturating, and the next phase requires deep integration with enterprise software infrastructure to handle cross-system SOPs, accuracy, and stability, giving established software companies an advantage over pure model providers.
This article shows how to use Laravel’s event‑driven architecture—events, listeners, and queue jobs—to decouple slow AI calls in a SaaS product, delivering instant HTTP responses, background processing, real‑time WebSocket updates, robust retry/failure handling, and fast, isolated testing.
The article explains how Spring’s latest multitenancy support, combined with Spring Security, JWT and Hibernate’s @TenantId, lets a single Spring Boot application safely serve thousands of SaaS tenants by automatically isolating data, avoiding manual tenant_id filters, and handling indexes, native SQL, and async tasks.
The article analyzes how Feishu’s 30‑billion‑yuan revenue was reclassified as AI infrastructure, detailing ByteDance’s massive AI spending, the shift in enterprise procurement toward bundled AI solutions, and the broader industry move to integrate desktop agents as the next entry point for enterprise services.
The article examines why single‑tenant SaaS incurs exploding cost and operational overhead, explains how logical tenant_id isolation boosts resource density, outlines a spectrum of isolation levels with six shared‑deployment challenges, and presents cell‑based partitioning as a practical solution.
The article explains how product managers often waste resources chasing 100% functional coverage, and shows that mature PMs use a 60%‑for‑80% approach—freezing low‑frequency, high‑cost scenarios, applying ROI formulas, scoring cards, and concrete ERP examples—to deliver core value efficiently.
The article argues that SMEs should avoid blindly copying large enterprises like Huawei in digital transformation due to limited budget, talent, and time, and instead adopt four principles — pain-point first, single-point breakthrough, light assets via SaaS, and boss-led adoption — starting with three low-cost, high-impact scenarios: CRM, inventory management, and financial bookkeeping.
The article reveals that many Chinese software firms overseas end up serving Chinese subsidiaries with low‑margin, high‑cost projects, exposing three core shortcomings—unchanged product core, lost localization advantage, and weak brand trust—while offering concrete steps to build genuine international pricing power.
The article examines four AI agent commercialization models—SaaS subscription, platform ecosystem with revenue sharing, enterprise customization, and Results-as-a-Service—using the outcomes-pricing framework to compare their risk profiles, suitable scenarios, and trade-offs, and offers a quadrant guide for selecting the most efficient approach in 2026.
The rise of AI agents is breaking the seat‑based SaaS pricing model, prompting a shift toward usage‑ and outcome‑based billing, reshaping software moats, and driving a market‑wide valuation plunge as companies scramble to capture value through result‑oriented pricing.
The interview with Anthropic CEO Dario Amodei reveals that as AI makes software generation cheap, the real competitive edge for enterprises will shift from code complexity to mastering real‑world workflows, data permissions, governance, and trustworthy execution within customer environments.
In 2026, fast‑moving consumer goods distributors face inventory overload, shelf stagnation, and cash‑flow crises, but the article shows how a three‑pillar activation framework—Buyable, Visible, Audible—combined with digital SaaS solutions can transform them into data‑driven local service providers and restore profitable sales.
Anthropic CEO Dario Amodei explains how the company’s enterprise‑focused business model, the shifting SaaS moat, explosive compute demand, embedding Claude in R&D workflows, and a balanced AI governance stance together illustrate the practical realities of AI’s impact on businesses, jobs, and policy.
Steve Yegge argues that the exponential growth of large language models is flattening due to dual physical and safety limits, prompting a shift toward AI literacy, token hygiene, and a resurgence of SaaS as developers adapt to the new "Flat Curve" era.
The article analyzes how major cloud providers and networking firms are shifting enterprise software from subscription‑based SaaS to autonomous AI agents, detailing architectural layers, strategic moves, and the resulting impact on integration, data access, and security models.
The article explains how an Extension‑Point mechanism can cleanly isolate tenant‑specific logic in SaaS systems by defining variation interfaces, providing per‑tenant implementations annotated with @Extension, and routing calls at runtime using hierarchical bizCode matching, avoiding tangled if‑else or inheritance explosion.
The article analyzes real‑world account system architectures across online car rental, offline amusement, tourism stores, housekeeping, ETC, e‑commerce points, and bank acquiring, showing how reusing validated designs reduces development cost, improves reliability, and adapts to diverse business models through configurable rules and multi‑account handling.
Former Sequoia partner Mike Vernal argues that the traditional three‑act SaaS growth model is obsolete, citing AI‑native companies like Cursor that achieve $100 M ARR in 12‑24 months, and urging founders to abandon protective wedges in favor of ambitious, full‑product launches.
The article explains how product managers can avoid the perfect‑perfection trap by focusing on the most common user scenarios, using a simple ROI formula, a three‑step decision process, and a practical “freeze” framework that delivers 80% of value with only 60% of the effort.
The author recounts how they leveraged the engineering structure, common capabilities, documentation standards, and AI‑assisted workflows from an existing ERP SaaS project to build a vertical, headquarters‑partner system, highlighting the need to define boundaries, adapt business logic, and use AI for support rather than blind code copying.
The Tsinghua University 2026 AI Elder Care report forecasts China's 60‑plus population reaching 400 million by 2035, outlines a three‑layer AI architecture, four core care loops, compliance as a moat, and a shift toward home‑centric SaaS business models.
Amid a 90% drop in banquet bookings during the May Day period, Wuliangye adopted a SaaS‑based digital banquet system that links brands, distributors, stores, hosts and consumers through QR codes and mini‑programs, creating tiered incentives, transparent cost flows and real‑time data loops that drove a 139% increase in customer acquisition while solving traditional pain points of paper registration, channel fee leakage and blind brand decisions.
In a recent podcast, NVIDIA’s Jensen Huang rebukes sensational AI‑replacement and extinction forecasts—citing Anthropic’s Dario Amodei, Elon Musk, and others—arguing that industry leaders should ground discussions in facts rather than dramatic, god‑like predictions.
The article analyzes how B‑side SaaS agents must extend isolation beyond the data layer to the execution layer, introducing a tenant control plane, tiered compute isolation, pre‑retrieval RAG filtering, versioned prompt loading, and a detailed launch checklist to ensure every inference, retrieval, and action respects a verifiable tenant boundary.
The article analyzes OpenClaw’s shift from GUI to API, its continuous workflow capabilities, the competition for high‑frequency user scenarios, the prospect of per‑device Claw instances, data‑context security concerns, and the potential fragmentation of SaaS software in the emerging AI agent market.
The article outlines practical methods for ensuring SaaS system stability, covering resource‑related issues, middleware reliability, pre‑release gray deployments, automated release procedures, comprehensive monitoring, load‑balancing strategies, degradation handling, rate limiting, chaos engineering, and SRE implementation.
Anthropic’s Claude Mythos preview scored a perfect Cybench benchmark, uncovered multiple zero‑day bugs, and sparked a steep plunge in Cloudflare’s stock, prompting a warning that AI‑accelerated vulnerability discovery could collapse SaaS business models and force a shift to AI‑driven security practices.
Amid the hype that SaaS is dying, Linear’s co‑founder and CEO argues that AI won’t eliminate SaaS but will transform its core value from feature lists to context‑driven decision‑making, making workflow design, organizational memory, and intelligent agent orchestration the new competitive moat.
Obsidian, a globally popular Markdown note‑taking app valued at $350 million, operates with just three full‑time engineers, no venture capital, and a meeting‑free culture, relying on an open‑source plugin ecosystem, a "Ramblings" communication channel, and paid add‑ons to sustain its growth while contrasting sharply with Notion's cloud‑first approach.
In a deep conversation between Atlassian executives and investors, the article debunks the SaaS apocalypse myth by showing how AI reshapes software from static data stores into dynamic process engines, redefining pricing, value, and the future of SaaS companies.
The article details a mid‑size SaaS growth team’s transformation from manual, experience‑driven A/B testing to a fully automated, auditable end‑to‑end decision flow, describing the pitfalls of pseudo‑automation, a three‑layer automation engine, and cultural shifts that boosted experiment adoption from 41% to 89% and cut decision latency from 3.7 days to 4.2 hours.
The article explains the definitions, core differences, and practical use cases of IaaS, PaaS, and SaaS, using a simple "meal" analogy and real‑world DevOps platform scenarios to help programmers and ops engineers quickly grasp each service model and its appropriate audience.
The author recounts a two‑year journey from early AI demos to a fully‑featured SaaS inventory system, detailing product architecture, multi‑platform development, AI tool selection, SDD/DDD practices, Git‑based review, and the limits of current AI assistance, offering concrete guidance for engineers aiming to commercialize AI‑augmented software.
The article analyzes how AI agents that operate directly via APIs are eroding the UI‑centric SaaS model, reshaping developer roles, collapsing seat‑based pricing, and shifting value toward infrastructure and deep‑vertical solutions while highlighting transitional friction and future opportunities.
The rise of AI Agents in early 2026 triggered a market‑wide SaaSpocalypse, collapsing software stocks, upending the seat‑based SaaS pricing model, and prompting a shift toward usage‑ and outcome‑based billing, as illustrated by real‑world cases from Klarna, Palantir and Salesforce.
After years of using Java Spring Boot, the author rewrote a SaaS microservice in Go, discovering a 60 % AWS cost reduction, simpler deployment, and easier concurrency, while also noting scenarios where Java's rich ecosystem remains preferable, offering practical guidance on when to choose Go for SaaS.
From AI chatbots to desktop coworkers, the article examines how Claude Cowork, OpenClaw and other emerging tools let AI control screens, keyboards, and files, reshaping workflows, sparking a competitive race among tech giants, and raising security and trust challenges for users and SaaS providers.
The recent plunge in software stocks reveals that large‑model AI is eroding the core value of traditional SaaS, forcing a shift from GUI‑driven products to language‑based interfaces, prompting firms to focus on token efficiency, plugin architectures, and outcome‑based pricing to survive.
The article argues that the SaaS model is collapsing as AI agents can replace traditional front‑end, back‑end, and middleware layers, driving a shift toward a simple Agent + Database architecture, reviving CLI tools, and redefining the role of GUIs in the era of large language models.
The article argues that the SaaS model is dying as AI agents become universal translators, flattening the traditional middle layers of frontend, backend, and middleware, leading to a new software paradigm where only agents and databases remain, while CLI tools experience a resurgence.
The article breaks down IaaS, PaaS, and SaaS by defining each model, explaining the responsibilities of providers and users, illustrating typical products and use‑cases, and offering a practical decision framework for enterprises to select the most suitable cloud service.
The article presents a step‑by‑step, code‑driven design of a Spring Cloud SaaS multi‑tenant solution that balances resource sharing and strict data isolation by using a shared‑database, shared‑schema approach with tenant_id filtering, ThreadLocal context, MyBatis‑Plus interceptors, Redis key prefixing, Sa‑Token session segregation, and Spring Boot auto‑configuration.
Samuel, a former optician turned solo developer, shares how he leverages AI tools to identify proven SaaS products, make a 1% improvement, and build three applications that collectively generate $35,000 in monthly revenue, outlining his project‑driven learning, four‑step idea validation, and four‑wheel growth model.
Intercom reversed a year of strategic, financial, and cultural stagnation by launching a founder‑led “Founder Mode”, concentrating on AI, building an elite AI pioneer team and fast‑execution squads, launching the Fin AI Agent with outcome‑based pricing, and reshaping its competitive positioning.
A new BCG report reveals that software expenses now consume over one‑fifth of enterprise IT budgets, driven by exploding SaaS options, M&A‑induced price pressure, and hidden infrastructure costs, and proposes a three‑pronged strategy—business measures, demand management, and technical optimization—to regain control and fund high‑value AI initiatives.
This article explains the core concepts of cloud service models (PaaS, IaaS, SaaS), outlines SaaS system characteristics, compares SaaS with traditional and internet services, describes B2B2C, classifies SaaS solutions, and details multi‑tenant architectures and deployment patterns.
This article examines why small‑and‑medium businesses consider cloud‑based inventory solutions, outlines their key benefits such as real‑time data sharing and finance‑business integration, highlights risks like data security and limited customization, and provides practical criteria for deciding whether a cloud inventory system fits your company.
The article argues that the vague term “user” misleads software design, illustrates the problem with airline reservation, Unix, and SaaS examples, shows how it creates security flaws like the Confused Deputy issue, and urges precise terminology early in projects to avoid costly rework.
This article examines Scale AI’s $29 billion valuation by analyzing its US government contracts, estimating total revenue through multiple valuation methods, evaluating its business model and growth prospects, and comparing its multiples with peers to assess whether the price reflects genuine potential or speculative hype.
This article explains the three main cloud service models—Infrastructure as a Service, Platform as a Service, and Software as a Service—while detailing key cloud concepts such as resource pooling, service quantification, rapid elasticity, and automated management including backup and security.
This article provides a comprehensive overview of Software‑as‑a‑Service, outlining its key advantages and disadvantages, detailing common pricing strategies such as free trials, per‑user, per‑feature, usage‑based and hybrid models, and describing typical SaaS front‑end, tenant, and admin modules.
Permission control is a critical, often overlooked component of SaaS products; this article explains why it matters, outlines core concepts, compares ACL, RBAC, and ABAC models, discusses SaaS-specific challenges like multi‑tenant isolation, and offers practical design, implementation, and performance‑optimization guidelines.
This article explains how SaaS products transition from serving individual consumers to enterprise customers, detailing differences in user focus, pricing, product features, multi‑tenant architecture, scalability, security, compliance, and API integration, and why this shift is essential for sustainable growth.
Cloud computing, a pivotal technology of the future, delivers on-demand computing resources via the internet, encompassing virtualization, storage, parallel processing, and automation, and is offered through three service models—Infrastructure as a Service, Platform as a Service, and Software as a Service—each illustrated with clear analogies and diagrams.
An in‑depth analysis of China’s domestic management software market reveals why soaring cloud revenues have not translated into profits, outlines three major market barriers, and proposes a pragmatic “survival triangle” strategy focused on niche tools, SaaS first, and metric‑driven governance.
The article examines Glean’s evolution from an enterprise‑search startup to a comprehensive Work AI Platform, detailing its market growth, competitive positioning, technical architecture—including data connectors, knowledge graphs, custom models, and agent reasoning—and the strategic challenges it must overcome to sustain its lead.
This article explains how a SaaS company leveraged large language models to automatically ingest, enrich, and analyze stability alerts, turning noisy notifications into actionable insights through configurable pipelines, Feishu integration, and a streamlined AI workflow that boosts incident response speed and reduces manual effort.
This article explains the concept of SaaS multi‑tenant architecture, compares three data‑isolation designs, and demonstrates how to implement elegant tenant‑level data isolation in Java using MyBatis‑Plus’s tenant plugin, complete with configuration, handler code, SQL examples, and troubleshooting tips.
This article demystifies the cloud service models SaaS, PaaS, IaaS and the emerging aPaaS by using a pizza‑making analogy, outlining their core features, typical application scenarios, and the benefits of low‑code platforms for accelerating digital transformation in enterprises.
Understanding SaaS architecture involves grasping cloud service models—PaaS, IaaS, SaaS—recognizing its subscription‑based, hosted nature, classifying business, efficiency, and hybrid solutions, and implementing core components such as security, data isolation, configurability, zero‑downtime upgrades, and multi‑tenant designs using vertical, shared, or domain‑segmented isolation.
This guide explains the concept of multi‑tenant architecture, compares isolation strategies such as separate databases, shared schemas, and shared databases, and demonstrates how to configure and enforce tenant‑aware RBAC using the PHP‑Casbin framework with example models, policies, and PHP code.
This article explains five common multi‑tenant implementation patterns—independent databases, shared database with separate schemas, shared tables, hybrid approaches, and containerized isolation—detailing their isolation levels, cost implications, scalability, and suitable use cases for SaaS applications.
This article dissects the end‑to‑end payment ecosystem for new‑retail, detailing business flows, channel aggregation, payment‑middle‑platform architecture, merchant onboarding, and account configuration to help SaaS providers build scalable, multi‑channel payment solutions.
The article distills five key insights from a SaaStr panel with leaders from GitHub, Ramp, Cloudflare and Figma, highlighting AI as an enabler, the need for rapid experimentation, rigorous evaluation, flexible roadmaps, and democratization, and compares each company’s product strategy, UX, value addition, and AI team structures.
This article provides a comprehensive overview of SaaS systems, covering cloud service models (PaaS, IaaS, SaaS), key characteristics, differences from traditional and internet services, classification into business, efficiency, and hybrid types, SaaSification steps, core components, and multi‑tenant architectures with various isolation models.
Satya Nadella predicts that conventional software applications, including SaaS, will disappear as AI agents directly interact with databases, reshaping how we work, access data, and automate tasks, while raising new questions about trust, permissions, and the future of the software industry.
This article analyses the subscription and pay‑as‑you‑go pricing models of Midjourney and OpenAI, detailing plan tiers, feature differentiation, psychological pricing tactics, and how these strategies shape user acquisition, retention, and revenue for AI SaaS products.
This article examines how SaaS products evolve from consumer‑focused (ToC) to enterprise‑focused (ToB) models, detailing differences in target users, pricing, product features, multi‑tenant architecture, scalability, high availability, security, compliance, and API integration strategies required for successful business‑to‑business transformation.
This article analyzes Baidu’s vertical‑search architecture team’s one‑stop development platform, detailing the background challenges, the FaaS and SaaS mechanisms introduced, design decisions, performance optimizations, dynamic form and DAG visualisation, and the resulting cost reductions and productivity gains.
This article explains the architecture, deployment process, and custom node configuration of dedicated Kubernetes clusters for SaaS and ToB scenarios on public cloud, highlighting differences from internal setups, networking challenges, and resource‑optimization solutions.
This article introduces cloud computing fundamentals, explaining its core concept and detailing the three service models—Infrastructure as a Service, Platform as a Service, and Software as a Service—along with examples, benefits, and how they together form modern cloud solutions.
This article uses everyday scenarios such as making pizza, building a house, running a pig farm, and playing on a computer to clearly explain the differences between IaaS, PaaS, and SaaS service models in cloud computing.
This article examines the QiaoFang SaaS platform’s multi‑tenant database architecture, tenant data governance, multi‑partition service design, and operational practices such as database operations, cleanup, and monitoring, highlighting the challenges and solutions for large‑scale real‑estate brokerage services.
This article provides a comprehensive overview of SaaS, covering cloud service models (PaaS, IaaS, SaaS), the two main characteristics of SaaS systems, differences from traditional software, various SaaS classifications, steps to SaaS-ify a product, core components, and multi‑tenant architectures with deployment models.
This article provides a comprehensive overview of cloud computing, covering its definition, core design principles such as resource pooling, virtualization, containerization, on‑demand services, elasticity, and the three main service models—IaaS, PaaS, and SaaS—while illustrating each concept with clear diagrams.
This article explains the concept, advantages, design considerations, and step‑by‑step implementation of a multi‑tenant architecture using Spring Boot and Spring Cloud, covering tenant isolation, database strategies, dynamic routing, security configuration, deployment scenarios, and provides complete code examples for building SaaS‑ready applications.
This guide outlines a complete security strategy for SaaS startups, covering external threats such as network attacks and data leaks, as well as internal risks like access control, host protection, code safety, log management, and third‑party integration, providing practical solutions and best‑practice recommendations.
This article explains the three main cloud service models—Infrastructure as a Service, Platform as a Service, and Software as a Service—by defining each, illustrating their analogies, describing their typical applications, and outlining how to choose the right model for business needs.
The author argues that, to revive China’s stagnant traditional software sector, SaaS must be reshaped through standardized business‑scenario APIs, real‑time business‑module visualization, and open‑domain architectures—augmented by AI‑driven code generation—to enable scalable customization and unlock new growth opportunities.
This article explains the stages of SaaS product development, introduces multiple methods for measuring product‑market fit—including retention, revenue, market perception, and Sean Ellis's survey—provides a questionnaire template, outlines calculation logic, and offers practical tips for applying the framework to drive growth.
The article analyzes recent Chinese enterprise SaaS market trends, examines the shift toward customized solutions for large customers and integration approaches for mid‑market clients, and offers strategic recommendations on product positioning, architecture openness, and service models to balance growth and sustainability.
This article outlines a three‑step framework—building consensus, setting shared goals, and establishing a clear communication channel—to close the collaboration gap between product‑development and business teams in a SaaS company, backed by real‑world results and practical PMO tactics.
The article details a SaaS company's two‑month development of an AI‑powered skin‑analysis solution, illustrating how DDD’s four‑color modeling split health services into aggregates, integrated Face++ APIs, and delivered a 30‑second, 30‑dimension skin report that attracted over 80 000 users and 9 000 orders.
Sugar BI, evolving from the internal ShowX platform to versions 2.0‑4.0, now offers a zero‑code, drag‑and‑drop visual editor, support for over 30 data sources, AI‑powered automatic analysis and the Sugar Bot Q&A module that transforms multi‑day data tasks into minutes, delivering containerized SaaS BI with intelligent chart recommendation and rapid, code‑free decision‑making for enterprises.
This article provides a comprehensive overview of cloud computing, explaining its definition, major service models (IaaS, PaaS, SaaS), key advantages and challenges, and the essential technologies such as virtualization, distributed systems, automation, security, storage, and big data that enable modern cloud solutions.
The article analyses the low efficiency problems faced by Chinese SaaS firms across product, development, customer acquisition and after‑sales, identifies root causes such as homogenous offerings, poor demand management, weak R&D processes, and proposes strategic, cultural, architectural, procedural and metric‑driven solutions to boost overall performance.
Cloud computing delivers internet‑based compute, storage, and networking as services, and this guide explains its core architecture—including compute, storage, network, and monitoring—plus the three service models (IaaS, PaaS, SaaS) with examples from major providers such as AWS, Azure, GCP, and Alibaba Cloud.
The article defines user assets, explains why protecting them is vital for SaaS companies, and outlines organizational, procedural, technical, and emergency-response measures—plus common challenges—to help enterprises build comprehensive user asset security programs.
Cloud computing, once a vague industry buzzword, now underpins modern IT by offering scalable storage and processing on remote servers, and this article explains its core concepts, service models (SaaS, PaaS, IaaS, FaaS), deployment types, benefits, security considerations, and leading providers.
Learn how to design a multi‑tenant SaaS platform using a shared database with independent schemas, covering isolation levels, Oracle and MySQL schema concepts, DNS‑based routing, dynamic connection switching in PHP with Webman, ThinkORM configuration, custom functions, and data synchronization strategies.
The article explains how SaaS companies can design and implement a comprehensive metric system that aligns business and technical indicators, supports data‑driven decision‑making, improves resource allocation, and drives continuous improvement across all organizational levels.
This article explains Geoffrey Moore’s ‘Crossing the Chasm’ framework applied to SaaS products, detailing the five technology‑adoption stages—from innovators to laggards—and provides strategic guidance on product development, market fit, scaling, support, and security challenges at each phase.
This article explains how to design a SaaS system that isolates each subsidiary's data by adding a tenant_id column to a shared MySQL table, converting the table to LIST‑partitioned storage, and enforcing tenant‑level access through stored procedures and a MyBatis interceptor, complete with code examples and testing steps.
This article provides a comprehensive overview of cloud architecture, detailing its definition, three-layer model (SaaS, PaaS, IaaS), key advantages and disadvantages, and essential management functions such as user, monitoring, billing, security, and resource management, while also offering promotional resources for deeper learning.
Model-as-a-Service (MaaS) reshapes AI deployment by turning machine-learning models into plug-and-play cloud services, lowering barriers, cutting costs, and enabling rapid innovation; this article compares Patil’s 2012 practical view with Chamath’s future-oriented vision, outlines core features, provider requirements, and the disruptive potential versus traditional SaaS.
This article provides a comprehensive overview of cloud computing architecture, covering service models (IaaS, PaaS, SaaS) with real‑world examples, deployment models (public, private, hybrid), key components such as virtualization and containers, and essential management and automation practices.
The article traces Salesforce’s transformation from a simple CRM SaaS with basic APIs in 2000 to a comprehensive, multi‑layered cloud platform featuring AppExchange, Force.com, Lightning, Einstein AI, Heroku integration, MuleSoft, and Hyperforce, highlighting the strategic shifts in SaaS, PaaS, and IaaS openness.
This article demonstrates how to convert a single‑tenant MySQL application into a multi‑tenant SaaS solution by adding a tenant_id column, using shared‑database partitioning, creating tenant tables, writing stored procedures for dynamic partition management, and implementing a MyBatis interceptor for hierarchical data permissions.
This article walks through converting a single‑tenant MySQL application into a SaaS solution by adding a tenant_id column, using shared‑database table partitioning, creating tenant metadata tables, writing stored procedures to add columns and partitions, and implementing a MyBatis interceptor for automatic data‑permission enforcement.
