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From Idea to Proof of Concept to MVP – 3 article series

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This is a a developer focused guide in three parts to evolving code, architecture, and processes with the purpose of turning a raw concept into a usable product. This process is one of the hardest parts of software development.

Teams often jump into implementation too early, or they build something polished before testing whether the underlying assumptions hold.

A structured flow—Idea → Proof of Concept (POC) → Minimum Viable Product (MVP)—keeps this journey predictable and reduces waste.

Each stage exists for a specific reason, and each stage demands a different mindset about code quality, design rigor, and security.
For developers, this is also a shift in how code is written, reused, refactored, and prepared for production.
This article explains the journey from the perspective of engineering teams, with practical backend and frontend examples and a clear separation of security activities.

The Idea

A raw concept describing a problem and a possible technical direction. It has no validated assumptions.

At this point, teams focus on understanding why the problem matters and what a potential solution could look like. No production-ready code exists yet.

Read the full article: From Idea to Proof of Concept to MVP: The Idea stage (1/3)

The Proof of Concept (POC)

A disposable implementation created to validate one or two critical assumptions. The focus is feasibility, not quality.

The POC answers narrow engineering questions such as: Can this API be used to implement the idea? or Can the frontend render this interaction reliably?

Code is expected to be thrown away or heavily rewritten later.

Read the full article: From Idea to Proof of Concept to MVP: The POC stage (2/3) .

The Minimum Viable Product (MVP)

A functional, small-scope product that solves a real user need with the minimum set of features.

Unlike a POC, the MVP requires maintainable code, basic architecture, observability, initial security measures, and repeatable engineering processes.

It is the first version that can be deployed and measured with real users.

Read the full article: From Idea to Proof of Concept to MVP: The Minimum Viable Product – MVP (3/3)

The post From Idea to Proof of Concept to MVP – 3 article series first appeared on Sorin Mustaca’s blog.

From Idea to Proof of Concept to MVP: The Minimum Viable Product – MVP (3/3)

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We continue the series of 3 articles with the second one, about the Minimum Viable Product (MVP).

Here is the first article in the series, From Idea to Proof of Concept to MVP: The Idea stage (1/3) and the second article, the From Idea to Proof of Concept to MVP: The POC stage (2/3) .

3. The Minimum Viable Product (MVP)

Once the team has validated feasibility, the work shifts to building a usable, reliable product with a minimal but complete set of features.
The MVP is the first version that serves real users and collects real feedback.

Code quality, architecture, and processes now matter because the MVP becomes the foundation for all future iterations.

Purpose and Scope

The MVP implements the core value with enough stability, scalability, and security to run in production.
It does not include every possible feature—only the essentials—but it must be well-engineered.

Inputs and Outputs

Inputs include the validated POC, UX designs, refined requirements, and mandatory security needs.
Outputs include a deployable product, operational metrics, user feedback, and a backlog for enhancements.

Actors

The full engineering team is involved: backend, frontend, QA, DevOps, Security, UX, Product, and Operations.
Cross-team communication becomes essential, because making the MVP stable requires alignment across all disciplines.

Engineering Expectations at This Stage

Code Quality and Reuse

Developers now take the core logic from the POC and turn it into production-ready modules.
This involves consistent naming, clear responsibilities, robust error handling, schema validation, and test coverage.
The team extracts reusable libraries, shared components, or service interfaces to avoid future duplication.
The MVP becomes the beginning of a long-term codebase.

Required Technical Changes

  • Transform API drafts into versioned, documented REST or GraphQL interfaces.

  • Move throwaway scripts into properly structured modules or services.

  • Add input validation, sanitization, and schema enforcement.

  • Introduce unit tests, integration tests, and E2E tests.

  • Replace temporary mock data with real data pipelines.

  • Add observability: logs, metrics, traces, dashboards.

  • Integrate with continuous delivery pipelines.

Process Evolution

The team adopts formal processes:

  • CI/CD, code reviews with defined guidelines, branching strategies, automated testing, deployment checklists, and observability standards.
  • Documentation becomes mandatory because the product is no longer experimental.

Backend Example

The recommendation engine becomes now a stable service.
The POC endpoint turns into a versioned API with full request validation, structured logging, retry logic, error mapping, and test coverage.
The integration with the ML service now uses proper authentication, rate limiting, and timeouts.
Monitoring dashboards track latency, throughput, and error rates.

Frontend Example

The rough POC component becomes part of the application’s design system.
It uses reusable UI components, handles loading and error states gracefully, and integrates with the global state store.
Unit tests confirm component behavior, tests validate the full user flow.
Telemetry captures user interactions so the team can validate assumptions after launch.

Security

Security now moves from conceptual and experimental checks to real, enforceable controls.
This includes:

  • Authentication and authorization integration

  • Input validation and output encoding

  • Protection against injection vulnerabilities

  • HTTPS enforcement and secure cookie settings

  • Audit logging

  • Secrets management

  • Data-handling guarantees for sensitive information

The MVP does not need every advanced security feature, but it must meet the minimum standards required for production—especially if it processes personal or regulated data.

Here is the first article in the series, From Idea to Proof of Concept to MVP: The Idea stage (1/3) and the second article, the From Idea to Proof of Concept to MVP: The POC stage (2/3) .

The post From Idea to Proof of Concept to MVP: The Minimum Viable Product – MVP (3/3) first appeared on Sorin Mustaca’s blog.

From Idea to Proof of Concept to MVP: The POC stage (2/3)

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We continue the series of 3 articles with the second one, about the Proof of Concept (POC).

Here is the first article in the series, From Idea to Proof of Concept to MVP: The Idea stage (1/3) .

2. The Proof of Concept (POC)

The POC is where the team tests a specific risky assumption that could make or break the idea.
The aim is not to build a usable product but to verify that a key technical, architectural, or data-processing challenge is solvable.

POC code is intentionally imperfect. It moves fast and cuts corners. However, it should still be written in a way that reduces friction when extracting reusable parts for the MVP.

What Defines a POC

  • A POC is short-lived and narrowly focused. It often tests only one or two questions:
    Can we integrate with this external system?
  • Can this algorithm scale?
  • Can the frontend render a dynamic timeline with the required performance?

The purpose is to generate a clear yes/no answer, not to produce a polished outcome.

Inputs and Outputs

Inputs include the problem statement and hypothesis defined in the idea stage.
Outputs include a working demonstration, documentation of findings, architectural constraints, and a clear decision: continue, pivot, or stop.

Actors

Developers implement the experiment.
Tech leads help evaluate results.
QA may help with validation but does not perform full product testing.
Security engineers review risks that appear during the experiment.

Engineering Expectations at This Stage

Code and Reuse

POC code is disposable, but that does not mean it should be sloppy. Developers should write code that can be extracted later without major re-architecture. This typically means:

  • Avoid hardcoded credentials, external URLs, or secrets.

  • Organize files in a simple but meaningful structure.

  • Implement the core logic in isolated modules instead of burying it inside an ad-hoc script.

  • Use interfaces or adapters to make future dependency injection easier.

The mindset should be: “This code may be thrown away, but if it works well, we want to reuse pieces of it.”

What Must Change Later

Before integrating POC code into the MVP, the team will need to refactor it: add error handling, consistent logging, tests, and proper abstractions.
In other words, the POC shows the core idea works, but the MVP requires turning this into real engineering.

Process Evolution

The POC often introduces small process steps such as:

  • Lightweight code reviews

  • A temporary branch in the repository

  • Simple build scripts to allow teammates to run the demonstration

This is still not production engineering. CI/CD pipelines and test automation usually come only at the MVP stage.

Backend Example

Suppose the team is building a new recommendation engine.
The backend POC might implement a single endpoint that forwards a request to an external ML service and measures latency and response quality.
Logging might be minimal, validation might be non-existent, and error handling might be crude—but the team learns whether the external ML service meets the performance requirements.

Frontend Example

A frontend POC might involve building a rough React component that displays personalized recommendations using mock data.
The component may not follow the design system, may not handle loading states cleanly, and may ignore error cases.
The goal is to check whether the UI interaction model feels intuitive and whether the state updates behave as expected.

Security

Security engineers examine how the POC handles sensitive data, even if the handling is mocked.
They validate risky paths such as authentication flows, data transformation logic, or external integrations.
The POC must identify whether the solution will require additional compliance measures, encrypted storage, or stricter authentication schemes.
This becomes a mandatory input for the MVP.

The post From Idea to Proof of Concept to MVP: The POC stage (2/3) first appeared on Sorin Mustaca’s blog.

From Idea to Proof of Concept to MVP: The Idea stage (1/3)

/in

This is a a developer focused guide in three parts to evolving code, architecture, and processes with the purpose of turning a raw concept into a usable product. This process is one of the hardest parts of software development.

Teams often jump into implementation too early, or they build something polished before testing whether the underlying assumptions hold.

A structured flow—Idea → Proof of Concept (POC) → Minimum Viable Product (MVP)—keeps this journey predictable and reduces waste.

Each stage exists for a specific reason, and each stage demands a different mindset about code quality, design rigor, and security.
For developers, this is also a shift in how code is written, reused, refactored, and prepared for production.
This article explains the journey from the perspective of engineering teams, with practical backend and frontend examples and a clear separation of security activities.

Legend

Idea
A raw concept describing a problem and a possible technical direction. It has no validated assumptions.

At this point, teams focus on understanding why the problem matters and what a potential solution could look like. No production-ready code exists yet.

Proof of Concept (POC)
A disposable implementation created to validate one or two critical assumptions. The focus is feasibility, not quality.

The POC answers narrow engineering questions such as: Can this API be used to implement the idea? or Can the frontend render this interaction reliably?

Code is expected to be thrown away or heavily rewritten later.

Minimum Viable Product (MVP)
A functional, small-scope product that solves a real user need with the minimum set of features.

Unlike a POC, the MVP requires maintainable code, basic architecture, observability, initial security measures, and repeatable engineering processes.

It is the first version that can be deployed and measured with real users.

Transition: Idea → POC
The transition tests feasibility. Only the highest-risk technical assumptions are validated. Success means the idea has enough technical grounding to justify investment.

Transition: POC → MVP
The transition focuses on turning validated feasibility into a real product. Teams refactor or rebuild the POC code into production-ready components. Architecture stabilizes, security controls appear, and processes become repeatable.

1. The Idea Stage

The idea stage is where the team defines the problem and shapes the first version of the solution direction. The discussion is broad, and uncertainty is still high.

At this point the team is not writing code in any meaningful sense, but rather exploring possibilities, boundaries (technological, legal, usability related), and early risks.

The goal here is not to “design the whole system”. The goal is to understand whether the idea is worth testing and whether the technical foundation appears feasible. This prevents teams from sinking time into something that cannot work or is not worth the investment.

What Makes This Stage Unique

The idea stage is low-cost, low-risk, and exploratory. Developers participate mainly by assessing feasibility, identifying potential architectural constraints, and sketching which components might be reused later. The conversation stays intentionally shallow. Nothing should be implemented that the team cannot abandon without regret.

Inputs and Outputs

Inputs include the product need, early UX sketches, discussions about the problem, and high-level constraints such as data privacy, integration requirements, or performance expectations.
Outputs include a defined problem statement, a preliminary solution outline, and a clear hypothesis that the POC must validate.

Actors

Product managers frame the problem. Engineering leads assess feasibility. UX designers shape initial user interactions. Security architects provide early warnings about potential data-handling or compliance pitfalls.

Engineering Expectations at This Stage

Code and Architecture

No production code is written. If developers create anything, it is lightweight and disposable:
simple mock APIs written in Postman collections, small HTML/JS mockups, or rough OpenAPI drafts.
Nothing created at this stage is meant to be reused directly, but these drafts help teams align on concepts.

However, developers should already think about potential reuse paths.
For instance, if the solution will likely need a shared data-access layer or a reusable front-end state-management module, this is the time to name those opportunities—even if nothing is implemented.

Process Implications

The team documents assumptions, potential dependencies, and cases where reuse might save time later.
There is no review process, no CI pipeline changes, and no branching strategy decisions.
This remains a design and exploration stage.

Backend Example

A backend developer might sketch a future architecture in AWS or draft a sequence diagram showing how the system would communicate with an external payment service.
They might explore the integration constraints by reading documentation and checking rate limits, but no or very little code is produced.

Frontend Example

A frontend developer might draft wireframes and map out how new UI states could fit into existing structures.
They might also check whether existing UI components can be repurposed to avoid re-inventing layout patterns later.

Security and Privacy

Security work is limited to conceptual analysis. No real data is supposed to be used in this stage, so privacy concerns should not exist.
Security architects identify which data categories will be processed, assess whether regulatory frameworks apply, and highlight technical constraints that must be tested in the POC.
No security implementation takes place at this stage, but early awareness helps avoid blind spots later.

The post From Idea to Proof of Concept to MVP: The Idea stage (1/3) first appeared on Sorin Mustaca’s blog.

Delivering often in small increments with Scrum

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Agile software development, particularly using Scrum, has revolutionized the way software is built and delivered.

At its core, Agile embraces iterative and incremental development, a stark contrast to traditional “waterfall” methodologies.

The primary objective is to deliver working software frequently and in small increments, ensuring continuous feedback, adaptability, and rapid value delivery.

However, we know from experience that this is not always the case, and if you have worked long enough in the software development industry, you know that usually, it is not the case.

I wrote before about this and the articles were well read (on LinkedIn), but I still see the need to summarize those articles:

Guide for delivering frequently software features that matter (series) #1/2: the Pillars of successful frequent delivery

Guide for delivering frequently software features that matter (series) #2/2: Challenges and the path forward

 

Key principles and practices

In order to frequently deliver small-increment you need to implement several key principles and practices:

Decomposition and User Stories

Break down large features or requirements into smaller, manageable user stories.
A well-formed user story describes a desired functionality from the perspective of an end-user, following the format: “As a [type of user], I want [some goal] so that [some reason].”
These stories are then estimated and prioritized.

Time-boxed Sprints

Scrum operates in short, fixed-length iterations called “sprints,” typically 2-4 weeks long.
Each sprint has a specific goal and a defined set of user stories to be completed.
The time-box ensures a consistent rhythm of delivery and prevents scope creep within an iteration.

Definition of Done (DoD)

A clear and shared “Definition of Done” is crucial.
This defines the criteria that a user story must meet to be considered complete, including coding, testing, documentation, and integration.
This ensures quality and prevents partially finished work from accumulating.

 

Cross-functional Teams

Scrum teams are self-organizing and cross-functional, meaning they possess all the skills necessary to take a user story from conception to delivery.
This reduces dependencies and streamlines the development process.

 

Frequent Feedback Loops

Scrum incorporates several built-in feedback loops:

  • Daily Scrums: Short daily meetings where the team synchronizes, discusses progress, and identifies impediments.
  • Sprint Demo: At the end of each sprint, the team demonstrates the “potentially shippable increment” to stakeholders, gathering feedback for future sprints.
  • Sprint Retrospectives: The team reflects on the past sprint to identify what went well, what could be improved, and creates actionable plans for the next sprint.

Prioritization and Backlog Refinement

The Product Owner is responsible for maintaining and prioritizing the Product Backlog, a living list of all desired features.
Regular “backlog refinement” sessions ensure that upcoming user stories are well-understood, estimated, and ready for development.

 

Now, if you think that by doing this solves all your problems, well, you are not entirely wrong, but also not entirely right. 🙂

As with any methodology, there are challenges.

Challenges and Solutions

Large, Undifferentiated Requirements

Stakeholders often present high-level, monolithic requirements that are difficult to break down into small, shippable increments. This can lead to long development cycles and delayed feedback.

Solutions

  • Invest in User Story Mapping: Collaboratively map out the user’s journey and identify smaller, deliverable “slices” of functionality.
  • Employ techniques like “Splitting User Stories”: Learn patterns and techniques to effectively break down large stories into smaller, valuable pieces (e.g., by workflow steps, by data type, by role).
  • Product Owner Focus: The Product Owner plays a critical role in collaborating with stakeholders to refine and decompose requirements, ensuring they are “INVEST” (Independent, Negotiable, Valuable, Estimable, Small, Testable)

Technical Debt and Integration Issues

Rapid delivery can sometimes lead to accumulating technical debt (shortcuts taken for speed) and integration headaches if not managed carefully.

This can slow down future development and make small increments harder to achieve.

Solutions

  • Prioritize Technical Excellence: Bake in time for refactoring, code quality, and automated testing within each sprint. The Definition of Done should include these aspects.
  • Continuous Integration and Continuous Delivery (CI/CD): Implement robust CI/CD pipelines to automate builds, tests, and deployments, ensuring that the software is always in a releasable state.
  • Pair Programming and Code Reviews: collaborative development and peer review usually catch issues early and maintain code quality, but they also slow down delivery. Use with care.

Lack of Clear Prioritization

Without a clear and stable Product Backlog and a Product Owner empowered to make decisions, teams can struggle with shifting priorities, leading to wasted effort and delayed delivery.

Solutions

  • Empower the Product Owner: Ensure the Product Owner has the authority and understanding to prioritize the Product Backlog effectively, balancing business value, risk, and dependencies.
  • Regular Backlog Refinement: Conduct frequent and collaborative backlog refinement sessions to ensure upcoming stories are well-understood and ready for development.
  • Transparency: Make the Product Backlog visible and accessible to everyone, fostering understanding and aligning expectations.

 

External Dependencies and Silos

In larger organizations, external dependencies (e.g., other teams, external vendors, compliance departments) or internal silos can hinder a team’s ability to deliver independently and frequently.

Solutions

  • Active Stakeholder Management: The Product Owner and Scrum Master should proactively identify and manage external dependencies, facilitating communication and coordination.
  • Cross-team Collaboration: Encourage regular communication and collaboration between teams, potentially through “Scrum of Scrums” or other scaling frameworks if applicable.
  • Shift to a “Value Stream” Mindset: Focus on optimizing the flow of value across the entire organization, identifying and removing bottlenecks that span multiple teams or departments.

The post Delivering often in small increments with Scrum first appeared on Sorin Mustaca’s blog.

Guide for delivering frequently software features that matter (series) #2/2: Challenges and the path forward

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Click below for the podcast version (AI generated):


Challenges that stop teams to deliver and how to solve them

Objection 1: “Our features are too complex for short sprints”

This is the most common objection I hear, and it reveals a fundamental misunderstanding. The solution isn’t longer sprints or more sprints — it’s better feature decomposition.

Take an e-commerce checkout flow. Instead of trying to build the entire process in one Sprint, break it down: first, just shopping cart management; next, shipping information; then payment processing; finally, order confirmation.

Each piece provides immediate value and teaches you something about user behavior.

The key insight? Users will happily use a partial feature if it solves a real problem for them. Of course, some things can be used, some others don’t.

In the above example, it makes no sense to allow ordering without being able to pay or to enter a delivery address.

It’s important to apply common sense and decompose features in such a way that they provide some value to the user or stakeholder.

Another aspect here is that sometimes you maybe don’t deliver the feature to the users, but you accumulate a few deliverables and then you ship them together, when it makes sense.

The key take out is: there is no receipt for how small or big the features should be in order to allow delivery. Try to decompose them and use common sense when to deliver them: individually or in sets.

 

Objection 2: “We can’t maintain quality at this pace”

Quality isn’t something you add at the end—it’s built into every step. The teams with the highest delivery frequency actually have the fewest quality issues because they’ve automated their quality checks and made them part of their daily workflow.

But this has a mandatory requirement the fact that automation is there.

If you postpone automation you run eventually in technical debt, which is more expensive to implement later.

 

Objection 3: “Our stakeholders don’t understand this approach” or “they don’t know what they want”

Stakeholder education is crucial. They need to understand that their active participation is what makes frequent delivery valuable. Regular “show and tell” sessions where stakeholders can actually use the software create enthusiasm and provide immediate feedback.

One technique that works well: frame frequent delivery as risk reduction. Instead of betting everything on a big release, you’re placing smaller, safer bets that can be adjusted based on market response.

Ask for feedback about you delivered and what you plan to deliver. You will see that even if the stakeholders don’t know exactly what they want, they will find it easier to provide feedback or corrections to your plans.

 

Advanced strategies for teams

Release planning without rigidity

While Scrum focuses on Sprint-level planning, successful teams also think several Sprints ahead. I use story mapping to visualize how features relate to user workflows, which helps identify what should be delivered together versus what can stand alone.

Think of it as planning a road trip—you know your major destinations but remain flexible about the exact route based on what you discover along the way.

Manage dependencies

Dependencies kill delivery predictability. The best teams minimize them through smart architecture choices (like microservices) and careful Sprint planning. When dependencies exist, make them visible through dependency boards that show how different teams’ work interconnects.

Define and collect metrics that actually matter

Velocity is useful for Sprint planning, but business metrics tell the real story.

  • Did you receive any feedback or complains from customers/users/stakeholders?
  • How quickly can you respond to customer requests?
  • How often do users engage with new features?
  • How many bugs did you have in the last delivery?
  • Were the features delivered used?

These metrics ensure frequent delivery, which translates to business success.

Building the culture that makes it work

Creating psychological safety

Frequent delivery requires teams to take risks and experiment. This only works when people feel safe to voice concerns, make and admit mistakes.

The goal is not to make mistakes, but to be aware that they might occur and react accordingly.

In my retrospectives, I focus on systems and processes, not individual performance.

When problems arise, we ask “how do we prevent this?” not “who caused this?”

Yes, sometimes it is needed to get direct feedback, but in general, I try to focus this feedback on me and less on other team members.

 

Real customer collaboration

The Agile Manifesto’s emphasis on customer collaboration isn’t just philosophy—it’s practical necessity.

Whenever possible and feasible, try to involve actual end users in sprint reviews, not just business stakeholders. Their feedback often reveals usability issues that internal teams miss.

Implement user analytics directly in your application to provide continuous insight into how people actually use your software.

 

Instead of conclusions

Mastering frequent delivery is a journey, not a destination.

The teams I’ve worked with who succeed share three characteristics:

  • They embrace change as opportunity,
  • They prioritize working software over comprehensive documentation (who doesn’t ?), and
  • They value collaboration over rigid processes.

Start with the fundamentals—reliable Sprint execution and solid engineering practices—then layer on advanced techniques as your team matures.

The goal isn’t perfection; it’s continuous progress toward more effective value delivery.

Organizations that master frequent delivery gain significant competitive advantage. They respond quickly to market changes, incorporate user feedback rapidly, and create more engaging work environments where team members see the immediate impact of their efforts.

Your journey starts with the next Sprint. Focus on delivering something valuable to users, measure their response, and use that learning to make the next Sprint even better.

That’s the path to software that actually matters.

The post Guide for delivering frequently software features that matter (series) #2/2: Challenges and the path forward first appeared on Sorin Mustaca on Cybersecurity.

Guide for delivering frequently software features that matter (series) #1/2: the Pillars of successful frequent delivery

/in

Click below for the podcast version (AI generated):

Guide for delivering frequently software features that matter: the three Pillars of successful frequent delivery

If you’re a software engineer older than 30 years, then you definitely have worked following a non-agile methodology.

Those methodologies are based on a fixed structure, a lot of planning, and hope that everything will go as planned. And they never worked 🙂

 

Small bets, less risk

After helping many teams transform their delivery approach over the past 2 decades, I’ve learned that the most successful software projects share one trait: they deliver working software early and often. Think of it like learning to cook—you taste as you go rather than waiting until the entire meal is prepared to discover it needs salt – or to discover that it has too much salt.

Scrum’s power lies in its ability to turn software development from a high-stakes gamble into a series of small, manageable bets.  It basically lowers the risk of creating something that is a failure before it is even released.

Instead of spending months building features that might miss the mark, you deliver value every 2 weeks and course-correct based on real user/stakeholder feedback.

 

The Three Pillars of successful frequent delivery

1. Sprint Planning that actually delivers value

Here’s where most teams go wrong: they focus on completing tasks instead of delivering outcomes.

In my experience, the magic question that transforms Sprint planning is: “What could we deliver to users at the end of this Sprint that would make them say ‘this is useful’?”

Or maybe, if you’re not that far, think in terms of: what do we have to do in order to be able to have something to show to customers/users/stakeholders?

This shift in thinking leads to what I call “vertical slicing”—delivering complete, end-to-end functionality rather than building in horizontal layers.

Think of instead of spending a sprint on “database framework,” you deliver a complete feature like “user login” that touches database, business logic, and user interface.

Or, instead of having a “GUI framework”, implement a GUI element and make it testable. You will still need to put the base of the GUI framework, but you will likely (or hopefully) implement only those elements needed to deliver that one element.

 

2. Your Definition of Done (DoD) is your safety net

The Definition of Done isn’t bureaucracy—it’s your insurance policy against the dreaded “90% complete” syndrome. I’ve seen too many teams rush to demo features that weren’t actually ready for users, creating technical debt that haunts them for months.

A solid Definition of Done includes peer reviews, automated tests, security checks, performance validation, and sometimes stakeholder approval.

Think of it as your quality gateway: nothing passes through unless it meets production standards.

 

3. What enables speed

CI/CD

Continuous Integration isn’t just a nice-to-have—it’s the foundation that makes frequent delivery possible. When code is integrated and tested multiple times, you eliminate the integration nightmares that plague traditional development.

Anything that is manual, especially testing, takes more time on the long run. And in software development you are running a multi stage marathon. Invest in automated End-To-End testing and you invest the time once, not every release cycle.

 

Main branch development

The teams who excel at frequent delivery have embraced “trunk-based development” where everyone works from the main branch. This forces smaller, more frequent commits and prevents the merge conflicts that can derail Sprint goals.

You might say that this is not always possible – and I even agree. Sometimes you need to branch in order to allow parallel development of larger features, which you don’t want to deliver step-by-step. While I don’t like this approach, I understand that sometimes it makes sense.

But, even in such cases, you can apply the same strategy on the parallel branch: make many small commits so that you can release often and test often.

 

I’ll stop here for now, but as you can see, there are many challenges that stop teams from releasing often.

I’ll address this in the next article from this series.

The post Guide for delivering frequently software features that matter (series) #1/2: the Pillars of successful frequent delivery first appeared on Sorin Mustaca on Cybersecurity.

Guide for delivering frequently software features that matter (series)

/in

If you’re a software engineer older than 30 years, then you definitely have worked following a non-agile methodology.

Those methodologies are based on a fixed structure, a lot of planning, and hope that everything will go as planned. And they never worked 🙂

 

Small bets, less risk

After helping many teams transform their delivery approach over the past 2 decades, I’ve learned that the most successful software projects share one trait: they deliver working software early and often. Think of it like learning to cook—you taste as you go rather than waiting until the entire meal is prepared to discover it needs salt – or to discover that it has too much salt.

Scrum’s power lies in its ability to turn software development from a high-stakes gamble into a series of small, manageable bets.  It basically lowers the risk of creating something that is a failure before it is even released.

Instead of spending months building features that might miss the mark, you deliver value every 2 weeks and course-correct based on real user/stakeholder feedback.

 

The Three Pillars of successful frequent delivery

1. Sprint Planning that actually delivers value

Here’s where most teams go wrong: they focus on completing tasks instead of delivering outcomes.

In my experience, the magic question that transforms Sprint planning is: “What could we deliver to users at the end of this Sprint that would make them say ‘this is useful’?”

Or maybe, if you’re not that far, think in terms of: what do we have to do in order to be able to have something to show to customers/users/stakeholders?

This shift in thinking leads to what I call “vertical slicing”—delivering complete, end-to-end functionality rather than building in horizontal layers.

Think of instead of spending a sprint on “database framework,” you deliver a complete feature like “user login” that touches database, business logic, and user interface.

Or, instead of having a “GUI framework”, implement a GUI element and make it testable. You will still need to put the base of the GUI framework, but you will likely (or hopefully) implement only those elements needed to deliver that one element.

 

2. Your Definition of Done (DoD) is your safety net

The Definition of Done isn’t bureaucracy—it’s your insurance policy against the dreaded “90% complete” syndrome. I’ve seen too many teams rush to demo features that weren’t actually ready for users, creating technical debt that haunts them for months.

A solid Definition of Done includes peer reviews, automated tests, security checks, performance validation, and sometimes stakeholder approval.

Think of it as your quality gateway: nothing passes through unless it meets production standards.

 

3. What enables speed

CI/CD

Continuous Integration isn’t just a nice-to-have—it’s the foundation that makes frequent delivery possible. When code is integrated and tested multiple times, you eliminate the integration nightmares that plague traditional development.

Anything that is manual, especially testing, takes more time on the long run. And in software development you are running a multi stage marathon. Invest in automated End-To-End testing and you invest the time once, not every release cycle.

 

Main branch development

The teams who excel at frequent delivery have embraced “trunk-based development” where everyone works from the main branch. This forces smaller, more frequent commits and prevents the merge conflicts that can derail Sprint goals.

You might say that this is not always possible – and I even agree. Sometimes you need to branch in order to allow parallel development of larger features, which you don’t want to deliver step-by-step. While I don’t like this approach, I understand that sometimes it makes sense.

But, even in such cases, you can apply the same strategy on the parallel branch: make many small commits so that you can release often and test often.

 

I’ll stop here for now, but as you can see, there are many challenges that stop teams from releasing often.

I’ll address this in the next article from this series.

The post Guide for delivering frequently software features that matter (series) first appeared on Sorin Mustaca on Cybersecurity.

Beyond “Move Fast and Fail Fast”: Balancing Speed, Security, and … Sanity in Software Development (with Podcast)

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Move fast and fail fast

In software development, the mantra “move fast and fail fast” has become both a rallying cry and a source of considerable debate.

It champions rapid iteration, prioritizing speed and output, often at the perceived expense of meticulous planning and architectural foresight. This approach, deeply intertwined with the principles of agile development, presents a stark contrast to the traditional model of lengthy planning cycles, rigorous architecture design, and a focus on minimizing risk through exhaustive preparation.

Fail fast

The allure of “fast” is undeniable. In today’s competitive market, speed to market can be the difference between success and failure. Rapid prototyping allows for early user feedback, facilitating continuous improvement and ensuring the product aligns with real-world needs. In essence, it’s about validating hypotheses quickly and pivoting when necessary. This iterative approach, inherent in agile methodologies, fosters a culture of adaptability and responsiveness, crucial in environments where change is the only constant.

So, “fail fast” refers mostly to a fast validation of the MVP (minimum viable product) and drop it if the results are unsatisfactory. This is, in general, very good because it is an optimal usage of resources.

Speed vs. Integrity

However, the emphasis on speed can raise legitimate concerns, particularly regarding security and long-term architectural integrity.

The fear is that a “move fast” mentality might lead to shortcuts, neglecting essential security considerations and creating a foundation prone to technical debt.

This is where the misconception often lies: “fast” in this context does not necessitate “insecure” or “bad.” Rather, it implies a prioritization of development output, which can, and should, be balanced with robust security practices and a forward-thinking architectural vision.

But, how can this forward-thinking be achieved, when the team is focused mostly on delivering value to validate with customers the assumptions made?

The key lies in understanding that agile development, when implemented effectively, incorporates security and architecture as an integral part of the process.

Concepts like “shift left security” emphasize integrating security considerations early in the development lifecycle, rather than as an afterthought.

Automated security testing, continuous integration/continuous deployment (CI/CD) pipelines with security gates, and regular security audits can be woven into the fabric of rapid development, ensuring that speed does not compromise security.

Validating early in the process means also that the not only the product is proven to meet the expectations, but also the architecture it is built upon.

The traditional approach

On the other hand, the traditional approach, with its emphasis on extensive planning and architecture, offers the perceived stability of a well-defined blueprint.

However, this approach carries its own risks. The extended planning phase can lead to delays, rendering the final product obsolete by the time it reaches the market. Moreover, the rigid nature of pre-defined architectures can hinder adaptability, making it difficult to respond to unexpected changes in user needs or market dynamics. The risk of “failing due to delays and lack of adaptation” is a real threat in fast-paced environments.

The modern software developer must navigate this tension, finding a balance between speed and stability. This involves adopting a pragmatic approach, leveraging the benefits of agile methodologies while mitigating the associated risks.

This can involve:

  • Establishing clear security guidelines and incorporating them into the development process. Having a SSDLC is mandatory when having to deliver fast.
  • Prioritizing a modular and adaptable architecture that can evolve with changing requirements. Modules should be possible to be implemented quickly and dropped without a lot of pain if they prove to be unsuccessful.
  • Implementing robust testing and monitoring to identify and address issues early on. A CI/CD pipeline will allow the team to focus more on delivering new features than testing and integrating all the time.
  • Fostering a culture of continuous learning and improvement, where developers are encouraged to experiment and innovate, while also being accountable for security and quality.
  • Utilizing threat modeling and risk assessment early in the design process. Threat modeling contains a risk assessment, which when done properly will prevent major issues later.

Instead of Conclusions:  my experience

Ultimately, the most effective approach is not about choosing between “fast” and “slow,” but about finding the right cadence of delivering value for each specific project .

The goal is to deliver constantly small pieces of code that bring value while avoiding failure altogether. If deliverables are constantly validated, a failure can only be of a small deliverable increment, which can be either quickly improved, completely removed or entirely replaced with something else.

Important is to learn from it quickly and adapt, ensuring that software development remains a dynamic and evolving process.

When I run a project, I define the goal and the high level path to achieve that goal. Sometimes this path is clear, sometimes many experiments are needed, and some will fail, some will succeed.

The post Beyond “Move Fast and Fail Fast”: Balancing Speed, Security, and … Sanity in Software Development (with Podcast) first appeared on Sorin Mustaca on Cybersecurity.

Project management with Scrum (with Podcast)

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They can’t mix, can they?

Seems like a contradiction to talk about classical project management and the best agile software development methodology ?

But let me ask you this: ever feel like traditional project management is great for mapping out the big picture but falls short when it comes to the nitty-gritty of execution?

And conversely, while Scrum is fantastic for rapid iteration and delivering value quickly, it sometimes lacks that long-term strategic view?

If you feel this, then you’re not alone!

Yes, they can mix

Let’s talk about how to get the best of both worlds when managing projects: having a solid long-term plan and the flexibility to adapt and deliver quickly.

Sometimes it feels like traditional project management is great for the big picture but not so hot on the details, right?

And Scrum is awesome for getting stuff done in short bursts, but can sometimes lose sight of the overall direction.

Turns out, a lot of teams are finding a sweet spot by mixing these two. Think of it like having a good map for your road trip and a sturdy vehicle to handle any bumps along the way.

So, what does each approach bring to the party?

Classical Project Management: The Grand Plan

Imagine classical project management as your strategic guide. It’s all about figuring out the project’s scope, setting those long-term goals, marking important milestones, and creating a project plan.

We’re talking budget, resources, timeline – the whole thing.

It’s about answering the big questions:

  • What are we trying to do?
  • When does it need to be finished?
  • How much will it cost?
  • Who’s in charge of what?

This is great for having a clear vision and a roadmap. It helps everyone stay on the same page and lets you track progress.

The tricky part? Sometimes those detailed plans can go out of date pretty fast. Because things change, right?

 

Scrum: Getting Things Done

Now, Scrum is your agile friend. It’s built for doing things in short bursts, perfect for navigating the twists and turns of, well, pretty much any project.

You break the project into smaller chunks – sprints – usually 2 weeks long. Each sprint has specific goals, and the team works together to deliver something useful by the end.

Scrum is all about talking to each other a lot, having quick daily meetings, and checking in regularly. It’s about being flexible and delivering value bit by bit.

Scrum is great at handling feedback, adding new stuff, and showing real results quickly.

The thing is, on its own, Scrum might need that long-term direction that classical project management provides.

The Perfect Mix: Working Together, Delivering Fast

The magic happens when you put these two together:

  • You use classical project management to set the long-term vision, make the initial plan, and decide where you’re going. This gives you a good map.
  • Use Scrum to actually get there, one sprint at a time. Scrum becomes your engine for delivering value along the route laid out by classical project management.

Here’s a simple way to think about it:

  1. Big Picture: Classical project management sets the overall project scope, goals, and timeline. Everyone knows what the target is.

  2. Breaking it Down: The project gets broken down into smaller pieces, often using the classical project management approach. This makes the work manageable.

  3. Sprint Time: The Scrum team takes a chunk of work and plans it out for a sprint. They figure out what they can realistically do in that time.

  4. Daily Check-ins: The team has quick daily meetings to talk about progress, any problems, and adjust as needed. Keeps everyone in sync.

  5. Show and Tell: At the end of each sprint, the team shows what they’ve built and gets feedback. This feedback helps plan future sprints.

  6. Getting Better: Regular team meetings let everyone think about how they’re working and find ways to improve.

So, by mixing classical project management and Scrum, you get the best of both worlds. You have a clear long-term plan and the flexibility to adapt and deliver quickly. It’s a great way to work together, deliver fast, and make sure projects stay on track while being able to handle whatever comes up.

The post Project management with Scrum (with Podcast) first appeared on Sorin Mustaca on Cybersecurity.