When I began as OpCo’s first Founder in Residence, my main mission was to connect our incredible community of experienced operators with promising early-stage startups. When I was a senior operator at a large company, I was eager to get a view into exciting emerging technologies that I didn’t see in my day job. Later on as a startup founder myself, every opportunity to get feedback from potential customers was gold. I wanted to build OpCo programs that create these valuable connections more programmatically.
OpCo’s Technical Product Showcase is an exciting new program designed to create and foster these connections. On February 12, in partnership with Orrick, we held our first showcase at the Ironclad offices in San Francisco. This inaugural event focused on startups making products for technical teams, and our expert operator panel included CIOs, CTOs, and engineering executives from startups and enterprises alike.
We wanted the showcase to be maximally useful for everyone attending, so we kept the guest list focused and conversations off the record. After a highly competitive application process that included both current OpCo portfolio companies as well as other promising startups from the broader ecosystem, we invited six companies to present to our operators for feedback.
What’s happening in the ecosystem?
We reviewed applications from a variety of startups, ranging from companies in stealth to those who have begun to crack seven-figure contracts. Looking at the full set of applicants helped us uncover trends among the hottest companies currently serving developers, engineers, and other technical leaders. Feedback from our operator panel on the six companies we selected as showcase participants further illuminated what’s going on in the ecosystem.
Here are a few things we saw.
AI is everywhere.
This is no surprise, and validates a trend that we didn’t need hard data to understand. Among these startups that are aiming to serve technology teams with their solutions, 75% of them incorporate AI into their value propositions.
In some cases, startups are using AI to solve traditional software problems, as with the many startups trying to automate software testing with AI. In other cases, they are building solutions to help technology teams deploy AI in their own products, as with the many startups aiming to optimize AI data management and model selection.
Our expert operator panel emphasized the importance of demonstrating real value with AI implementations, rather than just adding to the hype. Buyers need to see integration with existing workflows and evidence of recurring usage to be convinced of the value of AI solutions.
Everyone is going after software testing.
It was striking how many applicants are trying to automate software testing. Among the full set of companies that applied to the Technical Product Showcase, nearly a third of the group is trying to automate software testing as a key part of their offering.
This makes sense, as most technology teams still use highly manual approaches for last-mile deployment testing. But even within this context, this space is very crowded.
On-prem deployment is more common than it has been in years.
In the first several waves of SaaS, cloud storage, usage, and deployment were the center of many companies’ value propositions. Cloud made it possible for organizations to work with more agility and flexibility Cloud was also more reliable and cost-effective in many cases, since companies using cloud solutions no longer had to manage their own servers,
With the rise of AI, companies are increasingly concerned about the security and privacy of their proprietary data. Several startups that do various aspects of data management are deploying their solutions on prem in a way that we haven’t seen in several years. Large enterprises especially appear to find this reassuring.
There is little consensus on when to use RAG and when to build something more fine-tuned.
Most technology teams are integrating other foundation models into their solutions rather than building their own. Regardless of a team’s mix of model choices, nearly everyone is using RAG (Retrieval-Augmented Generation) somewhere.
Most of the technical leaders who reviewed companies for the showcase are trying to figure out where to invest in fine-tuning capabilities internally, with little agreement so far. That’s probably why the startup ecosystem is fractured on the point, with some companies building off-the-shelf RAG and others building bridge solutions designed to help enterprises that use both RAG and their own fine-tuning.
Sometimes, technology teams are the tip of the spear.
We saw a number of startups that currently sell to engineering and technology leaders, but the core of their solution can be extended to support other dimensions as well. In these cases, startups see tech buyers as the tip of the spear. In particular, we saw a number of startups taking on aspects of engineering performance management, with clear aspirations of expanding beyond tech customers down the line. All the experts agreed that having a clear view on time to value is incredibly important to securing the deal.
There’s a mix of top-down and bottoms-up GTM.
Even among our six showcase finalists, we saw every possible GTM permutation: companies selling to the CIO or CTO top-down, others starting with individual teams, and still others building on a successful open source foundation. In news surprising to no one, cold outreach rarely works. Successful enterprise sales typically come through trusted referrals or existing relationships.
Land and expand sales are a classically effective way to sell, but this approach isn’t as lightweight as it once was; even team-level purchases need to go through rigorous data privacy reviews when they include AI. Many teams are trying to work around this by making significant open source investments that individuals may adopt on their own before proposing the solution to their workplace more formally. Procurement processes are still catching up; legal and technical teams often have misunderstandings, which has made it difficult to get to standard, commonly accepted terms for AI contracts.
Regardless of your GTM model, your relationship with your initial buyer remains central. Our experts reinforced how critical it is to keep your initial buyer at the center of your land and expand motion, rather than going around them.
Our first Technical Product Showcase was a fantastic opportunity for startups and operators to exchange feedback and build meaningful business relationships. Thank you so much to everyone who participated and applied.
More to come so stay tuned!
