# About Name: The AI Startup Studio Description: Join me as I build an AI Startup Studio to systematically generate, evaluate and execute startup ideas using AI URL: https://vikramnayak.com # Navigation Menu - Home: https://vikramnayak.superblog.cloud/ - Topics: https://vikramnayak.superblog.cloud/topics - Search: https://vikramnayak.superblog.cloud/search - Connect: https://www.linkedin.com/in/vikramnayak85/ # Blog Posts ## #2. Systematic Ideation Author: Unknown Published: 2025-07-28 Category: Building with AI Tags: formulaite, startup system URL: https://vikramnayak.com/1-systematic-ideation/ **Pre-2024 startup pundits:** > "Everyone has an idea. Execution is where you win".  **Post-2024 pundits:**  > "Everyone can execute. The quality of your idea is where you win" **Me:** > "Ideas and execution are both bloody hard to do _well,_ but AI makes it easier to do so". A hodgepodge of thoughts about ... ideas ---------------------------------------- * What exactly is an idea? Is it a problem or a solution or a market opportunity or a technology shift or something else? Or is it a combination of all of these? * Where do ideas come from? From observing the world, or a personal pain point, or a top-down analysis of the market, or somewhere else? * How do you flesh out an idea? Customer segments, competitors, alternatives, market size/trajectory, trends, head winds, tail winds, technology shifts, strategic angle, bigger picture, positioning. * What differentiates a bad idea from a good idea? Is there an objective way to score ideas based on your goals / constraints * How do you refine or enrich an idea? Is there a way to reason through what adjacent / analogous idea would score higher? * How do we evaluate the impact of an idea? What change would happen in the world if this idea were successful?   * When is an idea good enough to act on? What are the criteria that signal that we can proceed with validation? Can we be objective about it? How do we incorporate our goals and constraints into this score? Turning "idea clutter" into clarity ----------------------------------- ### ​1\. The **seed of an idea** * It can come from anywhere (personal pain point, observing the world, news, "wouldn't it be cool if ...", etc)  * It can be anything (problem, solution, tech capability, market opportunity, etc) * It can be good or bad, from the point of view of your goals  ​ ### 2\. Fleshing out the idea  That seed of an idea still needs to be fleshed out. There's a lot of relevant context locked away in the entrepreneur's head, which has to be extracted so that you can figure out "_What exactly does this idea mean?_"  * Personal experiences and observations that might have led to this idea * Thoughts around who will benefit, what are their pains, how do they solve it currently, etc * Potential avatars that the solution might take. Eg. mobile app, AI agent, API, etc * Competitors that you might have been tracking * How you view / split the market. Eg companies that make charts for client deliverables vs companies that make charts for internal reporting. Another important concept that helps me is the "_idea tree_". It gives context about where exactly an idea "sits" in the market. Very often, we get too micro with our ideas without really understanding where they sit in the hierarchy. Too broad, and you will be playing a different game and fighting a different league of competition. Too small, and you will find yourself in a niche that has very little demand where it's hard to find / locate your customers. Here's an example of the idea tree for ChartBoss - it makes me realise that my product is quite far down this idea tree: Data + UX -> Data UX -> Charts -> Product -> Excel. ![](https://assets.superblog.ai/site_cuid_cmdicp5d90003loa3dl278m48/images/chartbossideatreeedited-1755592046652-compressed.png) ​ ### 3\. Getting to a "c**omplete idea"** It takes some hard thinking to make an idea complete - you can either use an existing framework like "Lean Canvas" or make your own.  In the Lean Canvas for example, the dimensions you would consider are Customer, Problem (functional + social + emotional jobs-to-be-done), Solution, Alternatives, Unique Value Proposition, Unfair Advantage, Channels, Key Metrics, Revenue Streams and Cost Structure. You could also include additional elements like Market Size / Trends, Timing, Size of Outcome, Unit economics, competitive landscape, etc.  Some of these dimensions above are informed by our own hypotheses and context, some of them come from conversations with people connected to the problem, and some of them can be completed using the help of AI.    ### 4\. Generating "**idea variants"** The key is to generate variants of the idea while still keeping it's essence intact. AI excels at this, so this is where we should be bringing in massive parallellization.  * What if there's another customer segment that experiences this pain even more acutely?  * What if there's an adjacent market where this solution would work even better?  * What if this tech has a better use case in a different problem?  * If we deliver the solution in a different form factor, will it unlock a bigger market?  * Is there a broader / more holistic use case that makes more sense?  ​ ### 5\. Evaluate / score the idea Just like we needed a framework to evaluate if the idea is complete, we also need a framework to evaluate if the idea is _good_. And "good" means different things to different people, so calling any idea "good" is entirely contextual.  If we can first understand our own goals, then we can understand how this idea helps us achieve those goals. And that let's us assign a score to the idea.  If the goal is to "build a portfolio of bootstrapped, profitable, AI-first, micro-saas B2B products", then you will find a very different type of idea rising to the top, versus if the goal was to "build a venture-scale vertically-integrated b2c company in the organic food segment".  So, finalise some dimensions along which to score each idea, and an objective way to assign a score for each dimension. Now, we can score the idea along with its variants, to see if any of them make the cut.     ### 6\. What comes next? Validation! Ideas that score above our cutoff value make it to the next stage - validation. And not _just_ validation, but _systematic validation._ Which we'll explore in our next blog. See you there! --- This blog is powered by Superblog. Visit https://superblog.ai to know more. --- ## #1. A system to build startups Author: Unknown Published: 2025-07-25 Category: Building with AI Tags: formulaite, startup system URL: https://vikramnayak.com/a-system-to-build-startups/ Fun fact: startup-building goals that seemed ridiculous until a couple of years ago are now very much within reach. One such thought that has stuck with me over the years: _"What would it take to build one or more million-dollar (revenue) companies with 1 person?"_.  "What would it take?" --------------------- In my view, achieving this audacious goal would need 2 main things mainly: 1. **A full-stack AI-first builder** - someone good _enough_ across multiple things that a tech product startup needs to be successful. Someone who can start from scratch and learn to use AI effectively. Most importantly, someone resilient. 2. **A system,** a method, a framework, a way to build in a structured manner. Without this, everything is ad-hoc, nothing is repeatable, learning loops are too slow, and network effects don't kick in. I'm not talking about a formula or process here, strictly a system. 15 years of solopreneurship does have it's benefits --------------------------------------------------- The year 2025 marks 15 years of entrepreneurship for me. 15 years of:  * making a wide variety of startup mistakes, and learning a lot in the process.  * going very deep on consulting, analytics, BI, tech, product, UX and data storytelling.  * going _nowehere near_ deep enough on validation, experimentation, growth, selling, marketing, evangelism and distribution.  * honing my survival skills, not losing my mind, and learning how to manage life while building.  But there's a silver lining ... What seemed like a disjointed, disconnected and disparate set of experiences is now coming together into something meaningful. As a founder, it sometimes feels like you need to bend to the "ways of the world" when nothing is going your way. Then there are those rare times when it seems like the world has magically moved in a way that aligns with you. This feels like one of those times for me. _The age of the generalist is here -_ AI has made sure of that.   **Nett:** Do I believe that I fulfil both the criteria I listed above (good-enough skills _and_ a system)? You bet I do!   What's left to do, but get started? ----------------------------------- The first venture I'll put through this system is ChartBoss, my data visualization add-in for Microsoft Excel. It's been built with a lot of love, but I suspect with a lot of inefficiency as well.  The focus will be on systematically evaluating where we are, understanding what we know vs what is an assumption, speaking to prospects to validate what we have assumed, and then going all out on commercializing it.  The core product has already been built - any further development will only be done after getting customer feedback. And this is the _last time_ that any product of mine will be developed without first validating.    So join me, as I experiment, learn and most importantly, move! --- This blog is powered by Superblog. Visit https://superblog.ai to know more. ---