Category creation is really, really, hard. Most fail at it.

I have been part of some second and third base hits - possibly some home runs (1B+ outcomes) but also a lot of startups who will never reach first base (startups that never reached PMF and will fizzle out over time). In this series I will cover the five guide lines to category creation which are first principles that I developed, across the 20+ AI startups I have invested in, scaled, advised, and founded. I use these and improve them daily.

My Five Guide Lines To Category Creation Are:

1. Market timing

2. Community

3. Technical feasibility (ease of use, scalability, stability, and enterprise readiness)

4. Founder market fit

5. Business market fit

Market Timing

Market timing can make or break a new startup's path to hyper-growth. Enter too early, and you're stuck in an uneducated market where buyers don't know a product like yours exists. Enter to late and your one of many lost at sea. I honestly think most technical founders and angel investors get this wrong.

Founders, before you decide where to spend 5-10 years of your life, pulling your friends, family, and network into what you're building, it's so important to validate proper market timing. Angels, before wiring your hard-earned money into risky bets, read this to better understand and validate proper market timing. Here is four areas I look at: Massive companies with an alternative, Open-source alternatives, Propensity to buy NOW, and Market evolution.

1. Massive companies with an alternative: I would not launch a new startup if there are massive companies for which your product, even after you have fully built it out, will only be 1x or 3x better than. That is the baseline; if your product is not 10x better than the large incumbent, you do not have a chance. You usually know if this be the case or not based on how much product nuance is required to build, grow, and scale your product. Take Slack, for example; they had a great product, but almost overnight Teams was released and ended up beating Slack by 10x. That is because, in the end, Slack was not better than Teams, yet Microsoft has such a massive distribution advantage that if at launch or at any point down the road of scaling, your product is not 10x better than the large incumbent's, you really have no chance.

   

   So when considering launching, be 100% positive about how and why you will be 10x better; this will make everything you are about to do so much easier and more likely to succeed.

2. Open-source alternatives: I have seen this cut both ways. I have seen founders and investors waste millions of dollars making a bet that a paid and dedicated SaaS company will thrive because it will be better than the open-source alternative. For founders and angel investors, this comes down to, "Will this product, when fully built, and very soon be 10x better than the open-source alternatives and why?" Answering this clearly is critical. I have seen founders raise $50M+ from top-tier VCs to build products that are truly not needed because the open-source alternatives will drive 99% of the value that the same product is trying to solve, meaning there is no market opportunity for those founders and investors. I have also worked with founders who clearly knew the open-source alternatives were severely lacking in core functionality and that they could build a huge business over time to fix this.

3. Propensity to buy NOW: In sales ops, when you territory plan, you look backward to review past data, on top of using your intuition to plan out what a given plot of territory can produce in sales; then you set the quota and plan to get there. As a founder and angel investor, you have to do this same exercise but in reverse order with little to no data. This comes down to truly understanding if what you are about to build or invest in will be a top two priorities for the companies you want to target to buy and fix NOW. It is okay if not every single account in the marketplace wants to buy NOW, but at least 5% of your TAM should want to buy NOW, and the rest of the 95% you need to be sure why the pain points and urgency will increase over time tipping into your favor as you convert them.

4. Market evolution: I have seen this done well and not so well. I have seen founders completely know where the future was heading and get it right way before anyone else (HuggingFace, OpenAI), and many others completely mispredict how the market was going to evolve, like MLOps platforms closed off to the swift shift to LLM's models. These companies built entire products not even anticipating the shift to and power of LLM's, therefore, they did not capture the market and built dead-end, death-of-a-thousand-cuts startups. The key here is to truly understand how your market will evolve and be at the forefront of the innovation curve and market shift curve.

I hope you enjoyed this. Next week we will cover community for SaaS Category Creation.

About Me

For context, on who I am I got my start at the beginning of the MLOps market, joining as the first revenue hire at MissingLink.ai, which was acquired by Samsung in 2018. This was at the start of the multi-billion-dollar model management MLOps market with the first-to-market experiment management platform for data science teams.

After MissingLink, I joined Comet.ml as the sixth employee, serving as the VP of Sales, and the first revenue hire (again). In twenty-one months, I scaled the company through a $14M Series A led by Scale Ventures and a $50M Series B led by OpenView, achieving over 500% ARR growth and closing deals like Uber, Etsy, and Netflix while hiring 20 GTM people globally.

After Comet, I started Awrabi Consulting and Banyan Capital, which have invested in or advised over 20 startups, resulting in over $1B in enterprise valuation and $250M in venture funding raised in less than four years.