Skip to main content

An Interest in Lean Startup Approach?

[PLACEHOLDER]
Image property Beolle Blog

That moments when we have that “idea” and get yourself excited believing that it will be your big break. This gets us thinking about “starting” a project and possibly building a business. This is a great feeling and it is part of the creative process. However the “passion” should be combined with a methodology, a framework, a tool that can help us evaluate, guide and measure the progress in order to build and make your dream a reality.

There are several school of thoughts that we can study and even combine together to plan for our entrepreneurial endeavors of building software products and/or services that we have envisioned.

One approach that I found very interesting in the product development business is the concept of “Lean Startup”. Below are a few points that got me interested in this subject (if you are looking for an introduction or find more info I encourage you to follow the links in our reference section), all elements part of the “Lean Startup” approach:
  1. The tough and important questions that we should ask ourselves: “Can this product be built?” vs “Should this product be build?”
  2. The concept of Minimum Viable Product (MVP): a product that has the core features that allows the product to be deployed. You can see it as a strategy to have your product available to a subset of customers in order to get feedback. It is part of an iterative, prototyping process. 
  3. Involve measurement and learning and actionable metrics that can demonstrate cause and effect questions.
  4. The use of the “5 why’s”. The intention is to attack the problematic items of the idea. It is an investigate method based on asking the question “why?” five times for understanding the root cause of the problem. 
  5. The “Lean Startup” has 5 principles. 2 of them I found it very:
    • 3rd principle -> Validated learning: “Startup exists not to make stuff, make money or serve customers. They exist to learn how to build sustainable business. This learning can be validated scientifically by running experiments that allow us to test each element of our vision”.
    • 5th principle -> build – measure – learn: “Fundamental activity of a startup is to turn ideas into products, measure how customers respond and then learn whether to pivot or persevere. All successful startup processes should be geared to accelerate the feedback loop”.
So if you are looking to build something then remember to use a method that helps you organize, measure and get feedback. Keep it simple and "fail-fast and often". Perhaps take a look at the "Lean Startup" and see if this method can fulfill the needs of your startup.

Reference:



Trending posts

Rethinking Canadian Economic Sovereignty Amid Foreign Acquisitions

About a year ago, I attended the Elevate Festival in Toronto, which I recommend if you haven't had the chance to experience it. The event was very inspiring because of its focus on business, technology, and entrepreneurship. It was interesting to see people at various stages of their careers; some executives, others developing their startups, a few in between, and some simply there to gain insights and knowledge. There was a unique atmosphere, influenced by the current political situation between Canada and the US. Many discussions centred around data sovereignty, cloud infrastructure independence, and ensuring that Canadians' data remained safe and secure within the country's borders or trusted allies. Building trust requires considerable effort, yet it can be shattered very quickly… and once broken, repairing it becomes extremely difficult, if not impossible. Considering the current geopolitical landscape, it is unclear where we go from here... but it seems the rules hav...

Reimagining Digital Experience Management: How Agentic AI is Transforming Adobe Experience Manager

 Adobe Experience Manager (AEM) has introduced powerful new Agentic AI capabilities designed to continuously improve and adapt digital experiences at the speed of AI. By integrating advanced AI orchestrators through Agent-to-Agent (A2A) and Model Control Protocol (MCP) tools, AEM enables brands to automate complex workflows and enforce compliance seamlessly across enterprise ecosystems. Through a suite of specialized agents, teams can transition from manual, weeks-long processes into fast, AI-assisted workflows powered by simple natural language prompts. Photo by Tunahan KALAYCI via Pexels   Here is a breakdown of the key agents driving AEM’s new Agentic capabilities, their value propositions, their guardrails, and their current availability status. 1. Brand Experience Agent. Overview. The Brand Experience Agent accelerates digital modernization through specialized sub-agents—the Experience Modernization Agent, Experience Production Agent, and Experience Development Agent. Tog...

Steer for a talent transformation strategy (and avoiding AI fatigue)

 There was a debate on whether to feature the term “AI” in the title of this article. Honestly, a key motivation for pursuing the research that led to this post was sparked by the widespread excitement about AI appearing constantly in our LinkedIn feed, to the point of feeling the fatigue, and even a bit disappointed in the algorithm of this, and the others, social media and content curated apps.  We soon discovered that there is an entire concept called "AI fatigue", not exactly how we were feeling it, but more about the mixed emotions people in the workforce have regarding the use of AI tools. Photo by Mart Production via Pexels (background updated with AI and Adobe  tech) From micro blog posts to video podcasts, lately, most of the tech content we encounter revolves around AI. They often sound or read very similar, usually mentioning the same few top providers. The articles (and social posts... at least the popular ones with paid-campaigns behind it) tend to focus less...

AI Beyond the Hype: Responsible Adoption for Lasting Impact

 These days, simply mentioning “AI” isn’t going to win anyone over. Clients expect authentic, data-driven results—not just bold claims or industry jargon. The expanding reach of AI brings some real concerns with it, such as errors, bias, and privacy risks are all in the mix. If those issues aren’t addressed, trust can erode quickly. It also affects an organisation’s dynamics, operations, and culture—regardless of size—including shifts in client relationships as expectations evolve. What can set a tech-consulting firm apart, among other things, is the dedication to building AI solutions on foundational values like fairness, transparency, accountability, privacy, security, and reliability. In other words, Responsible AI can be hard work, and it is a genuine differentiator. If an organisation can ensure the solutions implemented are ethical, clear, and consistently trustworthy, then it is likely it will foster customer confidence and loyalty. Photo by Google DeepMind from Pexels ...

This blog uses cookies to improve your browsing experience. Simple analytics might be in place for pageviews purposes. They are harmless and never personally identify you.

Agreed