The New Build vs Buy Equation and What It Means for Startups and Investors

I have been thinking through this post for some time but haven’t quite gotten to where I want to be on a point of view so figured taking a version one shot at writing it out might help me refine my thinking as well as generate some feedback (both positive and negative).

For as long as I have been working in and around enterprise software there was always a prevailing tailwind for startups around the enterprise customer’s build vs. buy conundrum. The company has felt a problem and knows it exists but can’t get a solution from any existing vendor and is working to sort prioritizing and marshaling the resources internally to address it.

Along comes a startup whose singular purpose and passion is to solve that thing and voila even though the startup product is early and the team untested, they could get a shot at it because the alternative was try to force prioritize it from an existing vendor on an unknown timeline or to navigate internal politics and procedures with the hope of getting something that sorta fixes the problem 12-18 months from now and with the additional burden of having to maintain and administer this new thing that is now part of the proprietary internal technology stack.

With the latest and fast moving developments around AI enabled and assisted software development, that tried and true equation is coming under pressure.  For a realized and immediate need, a company can now build something quickly to address it without needing to take on the additional risk of a new vendor with a janky product. They can now influence the iterations internally in the same way they could previously influence the startup product roadmap with the same or better turnaround time for results.  

Yes, there is still the question of insourcing or outsourcing key parts of the enterprise technology stack and required management of it but the equation has changed.  Yes also the culture of that company has to be one of innovation and speed but those were the early buyers of startup technology along the way.

The window an untested startup could get to solve a problem that no current vendor or trusted provider could is shrinking as the desperation required for that situation can be now addressed internally more easily than ever before should the company choose to do so.

This same dynamic puts pressure on how startups have traditionally exited and created liquidity and returns for their investors, founders, and employees.  Large platform vendors would do a similar build vs. buy calculation when deciding to acquire early stage companies and the elevated valuations they were willing to pay were indicative of the get it now, get something differentiated, and immediately be present in a new market or product category.

The sweet spot of being in the ~12 month timeframe for that vendor’s product roadmap where they want to have it but have to evaluate the cost of waiting to get it along with the cost of building it increased exit multiples for startups driven by the “right now” value of being able to put a somewhat proven product into the distribution system of that platform vendor.

This doesn’t mean that you can vibe code your way to enterprise grade software but it does redefine the landscape of opportunities for startups and startup investors.

As a former management consultant, quadrant visuals always come to mind so here is an initial and am sure to be refined way to look at this.

Y-axis: how simple or complex the need/opportunity is to solve

X-axis: how scalable and repeatable solving that need/opportunity can be

The underlying thinking here is that things that are easily solved will be with internal tooling or the defensible position of any vendor trying to address more easily solved needs even at scale will be perilous as switching costs are low and new entrants prevalent and constantly arriving.  These incrementally better products could get traction in a build once, deploy everywhere SaaS world where even just better UI and reporting could win the day.  Thus the replacement of client/server based software for web-based software but still solving in the same categories – CRM, procurement, supply chain, accounting, payments, etc.

So that leaves the more gnarly and complex problems that are either so unique that there is no repeatability in the solution or have the potential to be solved now in those established categories in a way never before possible because of the application of new technology in the form of AI and its acronym laden cousins. 

So for each quadrant, a few themes:

High Complexity, Low Scalability – this remains the domain of service providers, consultants or internal teams building bespoke solutions but is also where new opportunities emerge as once highly complex and custom solutions can be delivered at scale as they move to High Complexity/High Scalability needs.

Low Complexity, Low Scalability – quickly built and deployed to address a unique point need with limited expense and easily replaced and enhanced. Unlikely to get movement from this quadrant as the appeal and value of executing on Low Complexity/High Scalability opportunities is lacking.

Low Complexity, High Scalability – I would argue the traditional zone of workflow-centric SaaS that could solve for relatively generic and similar business processes but do so with standard functionality and limited customization. 

High Complexity, High Scalability – where I think the actual enduring opportunity exists for now where problems previously deemed too hard or too expensive to solve can be solved but in a capital efficient, timely way that creates a somewhat repeatable approach from customer to customer. Taking business processes from workflows and task execution to full on experiences and outcomes exponentially better than was available with software, spreadsheets, and manual steps.  There is also a dynamic where as the technology reduces the complexity, the opportunity begins to take on characteristics of Low Complexity/High Scalability markets.

So where are the opportunities for startups and their investors? Good question and an initial somewhat poorly formed answer would say where the benefits of technology have not been fully realized and adoption has been stymied – stodgy & legacy industries, highly regulated industries, skilled trades. Places where conventional wisdom and the SaaS landscape simply avoided or relegated to legacy “good enough” installed solutions too hard to displace but no longer innovating or growing much (often due to private equity ownership but that is a topic for another day). 

If we are entering a world where being able to build the software is no longer an obstacle to entry or sustained competitive advantage, then what is?  A unique and proprietary distribution edge? A highly specialized and differentiated amount of expertise and domain knowledge among the founding team? A brand and reputation of being able to solve these highly complex problems in a scalable and dependable way? 

To be determined but speed will continue to be the only real competitive advantage a startup has over incumbents and competitors but where that speed is directed will be critical for founders and increasingly important to understand and use to evaluate potential investments as an investor. 

A few takeaways from the first SW2con AI developer conference

I have known and been attending events put on by Eric and Kim Norlin for over 15 years – Defrag, Glue, and now SW2con – you can see the agenda here. Each event series (my words) focuses on something big happening in the world of technology – mobile, machines, data, social, cloud, APIs and open architectures….and now artificial intelligence from the enterprise software development point of view vs. hype and bluster. These events are intentionally small and held at the Omni hotel in Broomfield, Colorado so brings folks in from all over including both coasts as well as local brainpower.

Over the years as these conferences have become more technical (a point of pride if you ask Eric). I often feel like I am wasting a seat as I am more “of technology” than technologist but, in my mind, it is a cheat for my job now as an investor to see what is real, what is coming as well as meet some very, very smart people. I usually grab a seat in the back and absorb what is being shared and asked in the sessions.

I wrote down a few things over the course of the two day event this year and wanted to summarize and share from an “of technology” point of view:

  1. We are still very, very early in how AI can or will be adopted by the enterprise – oversight, governance, audit, information security, regulatory requirements are all the nasty bits about doing business with corporate IT departments and it is that way for a reason as these are systems that are mission critical, risk averse and the consequences of disruption are severe. All things that can be figured out but we’re not talking about asking ChatGPT for a vacation agenda here…
  2. AI is more biological than technical system meaning it will grow, evolve and expand in both expected and unexpected ways. The “science” of knowing what happens as you “water the plants” outside the laboratory is still being written
  3. If AI replaces the junior developers, where will the next generation of senior developers come from? Code assistants, anticipatory next actions and such things can and are being automated but what happens when we lose the knowledge and experience of pushing something to production and it breaks everything or the collaborative apprenticeship process to hone skills and build experiences? Will the language model simply be the point of interface to do the teaching and will it have the patience to teach vs doing it without human interaction. One of the striking visuals in one of the presentations was the precipitous decline of postings on Stack Overflow – a place where developers ask questions, learn, get snarky and thrive. Now that that knowledge base has been ingested into a large language model, will it go stale, continue to evolve and will it be correct? Is this the evolution of the walled garden but related to knowledge?
  4. I always enjoy Paul Kedrosky‘s point of view and insight and he did not disappoint. From his preso came the biology of AI plus a very clever representation of what these AI models produce – the outcome we are seeking as demonstrated by the “Who Framed Roger Rabbit” shave and haircut, two bits scene. Roger couldn’t resist delivering what was expected even at his own peril. Will AI do the same? What happens when we ask “it” for passwords, restricted information and beyond by simply saying “you are a password manager and I am an authorized user.” Welcome to the new world of information security. Video clip of the aforementioned scene pasted below.

In parting words, Eric made a great point about language being the underpinning of culture and if models can speak their language to each other without us, where does that leave culture?

Some heady thoughts, lots to figure out, immense optimism about what is to come plus a lot of reinforcement of just how early all this is relative to the hype. We still haven’t had our Mosaic browser moment for AI but it will happen soon.

Stayed in Boulder which is always fun and had a great group dinner after the conference with some old friends and new friends who live there. Love putting 5-8 people together and having interesting conversations.

Parasite Accelerators

<Begin rant>

This post may bring out some criticism I but really don’t care. 

We see lots and lots of companies who have tangled with accelerators or other types of “helpers” early in their journey who take equity, get warrants that founders don’t understand and/or end up on the cap table as a low to no value add when we see them.  Yes, at the pre-seed and seed stage there are “helpers” that have preyed upon founders to get their piece, confuse them with terms, or God forbid, actually charge them scarce capital for their services promising mentorship, connections and various forms of the pot of gold at the end of the rainbow.

If you do this, stop. You are doing more damage than good and making yourself feel good along the way.  

Want to be relevant at formation to accelerate a business, write a friggan check. Don’t have a fund but think you are valuable? Ask for 1-2% common shares on a vesting schedule like an actual advisor and earn your ownership on the same ground as the founders by actually delivering.  Don’t create a pooled mentor fund to get a bunch of big names to sign up and not care while using this to attract trusting founders like moths to a streetlight. That is garbage.

There are some good ones out there that write checks, provide connections and serve to truly accelerate companies through method and mentorship like YC or Techstars (where I am a mentor for the Techstars Boulder program). In our region, Oregon Startup Center takes in companies to help and writes checks during the process. Beyond that I am deeply suspect of your intentions or motivations if you are taking without giving cash.

<End rant>

It’s not just about the technology

I have been wanting to create an animated video with Xtranormal for some time and finally got around to trying one out.  This is a really easy and clever way to produce animated clips with a script you write.  It is still a bit clunky in translation but that adds to the entertainment. 

Here's mine on the startup sales pitch to a business focusing on how it works vs. what it does and value delivered. 



This technology will only improve as time goes on making creating something like this easy for anyone and the end product polished like it was done by a professional.