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Activant is a research-led global investment firm that partners with high-growth companies.

We partner with founders who have won their initial battles and are ready for the next challenge.

We typically invest when two things come together. First, the company has the potential to achieve escape velocity and transform an entire industry. Second, we believe the founders can lead the company through hyper growth, and our support can significantly increase the probability of this success. 

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Rebecca grew up in Durban, South Africa and later studied at the University of Cape Town, where she found her passion for the world of finance. Rebecca works within Activant’s research team, contributing to its rich knowledge of disruptive markets.

"Activant celebrates continuous learning and collaboration, which really sets it apart from many organisations. The opportunity to work alongside individuals with deep-rooted investment experience, as well as founders, is something that really excites me."

Oceanrock is a provider of high-quality research, analysis and decision-making support to the UK investment community: private equity funds, family offices, hedge funds, asset managers, M&A boutiques and corporates

Trucking is a vital cog in the U.S. economy and a way of life for more than a million over-the-road (OTR) truckers and three million commercial fleet 

 Together these groups spend a combined $200+ billion on diesel and gasoline every year, and another $150+ billion annually on tolls, maintenance, lumpers, taxes, and a host of ancillary 

 For the privilege and convenience of using a fuel card, the issuers take a cut of 1%-2%. Sound like a good deal? Yes, for the card issuer, but not for the trucker.

Once the rubber hits the road, truckers quickly find that the great “in-network” deal they were sold on doesn’t hold up to the pump price across the street. They’re told about extensive fuel card networks, then have to drive an extra half hour to find an in-network station, paying the fuel cost of going out of their way as well as the lost-time cost. Finally at the pump, drivers find themselves waiting in long lines, wasting even more time while the clock continues to tick.

That’s just the on-the-road experience. Add in a host of account maintenance, transaction, and card replacement charges, and all-in fees are more than likely 50% higher than what truck drivers thought they signed up 

 And because Fleetcor and Wex – the two dominant fuel card companies – control nearly 70% of the $375 billion gross spending OTR card market, they have little incentive to innovate or improve their technologies and product offering. The closed-loop systems they operate present a litany of unforeseen expenses.

However, there are some innovative start-ups targeting this $7.5 billion market that is ripe for 

TAM Analysis

Fuel cards emerged in the 1980s to solve the cash flow and tracking challenges that truckers and trucking companies endured. Early leaders like Comdata and EFS were ultimately surpassed by Wex and Fleetcor, which began acquiring and aggregating more than 150 companies to largely consolidate the market. Today, 99% of all truck stops offer payments through either Fleetcor or Wex, and most fuel card agreements in OTR flow through their cards.

Drivers using a plastic charge card issued by Fleetcor or Wex must go through a series of prompts while inputting multiple codes, allowing the card to attribute the transaction to the driver and the specific trip. Importantly, after the transaction is completed, the fleet pays Fleetcor and Wex (i.e. the card issuer) for the fuel, and 

Fleetcor and Wex pay the truck stop, acting as the merchant acquirer. This creates a closed-loop system, in which Fleetcor and Wex act as the card issuer, the transaction processor and the merchant acquirer.

For the truck driver, this has a few notable benefits. First, because the drivers pay Fleetcor and Wex directly for the cost of the fuel, and the card-issuers then pay the truck stops, the card issuers can afford to give drivers cash prices while providing the flexibility and convenience of a plastic charge card. That represents 2-3% in savings per fill-up. When the average fill-up for OTR trucks is 

, or about $500 to $600, the savings can be $10-$20 per fill at today’s 

 Secondly, because Fleetcor and Wex capture both sides of the transaction, they have near-perfect data visibility, which can help to combat fraud. Closed-loop systems can see what type of fuel a driver purchased, how much they paid, and what trip they’re on. If the driver happens to be in Cedar Rapids, Iowa, and a fraudster has used the same card details to buy $1,000 of fuel near Cedar Springs, Texas, they can easily dispute that charge using transaction metadata contained within the system. These are proven positives of closed-loop systems.

Recent innovations in credit card technologies and metadata tracking have, however, made it easier and cheaper to automate expense tracking and fraud protection, making one of the major benefits of fuel cards redundant. Closed-loop systems also have significant downsides for truck-drivers and for the truck stops in their networks.

To understand the drag fuel cards place on the industry, it’s helpful to look at the end-to-end process and highlight the many inefficiencies and unnecessary costs of filling up a vehicle.

Before a driver can fill their vehicle, they need to use the Fleetcor or Wex app to figure out which truck stops are in their fuel card network. Conversations with industry leaders suggest that drivers often need to travel up to 30 minutes off their path to fill up at an “in-network” fuel station. This costs them twice: first, in the extra gallons spent driving to the truck stop and, secondly, in the time eaten out of their 11-hour daily limit.

Truckers often find that the price posted at a “Big 3” stop (Love’s, TA, Pilot Flying J) is meaningfully higher than at small, regional chains. For large fleets, which negotiate directly with the truck stops and operate on a cost-plus model, this isn’t really an issue. But for the smaller fleets and owner-operators, who get price-minus costing, this means a higher “discounted” price for in-network fuel than they could get across the street at a regional chain.

Besides potential waiting time at the truck stop island, the average driver takes between five and 15 minutes to enter the long list of numbers and selections required to identify their trip: mobile app codes, reward card details, unit numbers, trip numbers, fuel types, DEF selections, and more. And while the actual pumping of fuel takes less than four minutes, if the driver gets any number wrong, they will have to restart the whole process.

All of this time is on the clock, adding to the driver’s 11-hour maximum behind the wheel. When drivers are paid by the mile, this translates directly to lost earnings.

Away from the pump, a driver might be hit with a late fee, a card recharge fee, a toll fee or even an unused money code fee. On average, we found that smaller carriers and owner-operators pay up to 50% more in fees than they expected. In any given month, this can add up to thousands away from a small carrier’s bottom line.

Card theft or skimming is always a risk. Fraudulent charges are common and drivers reporting unusual transactions may have their cards frozen for up to 60 days as Fleetcor and Wex investigate before sending a new card, leaving the driver back at square one using cash. Also, because Fleetcor and Wex are struggling to push chip cards, most drivers are stuck with old technology magstripe cards, years after their personal credit cards got the more secure chip.

Many of these pain points are a feature — not a bug — endemic to the current fuel card duopoly. In addressing these challenges, Activant research highlights the opportunity for open-loop alternatives.

New solutions are emerging to address the pain points drivers face.

Over the past few years, both Visa and Mastercard have rolled out better data requirements for fuel merchants wanting to accept their cards. Now, 98% of truck stops offer Level 3 data to Visa and Mastercard, meaning the price per gallon, the gallons pumped, the DEF and refrigerant selections can all be logged in one open-loop 

 The result is that the long-time expense management benefits of having a closed-loop network are disappearing, as open-loop cards can offer the same visibility without the network lock-in.

Electronic Logging Devices (ELDs) come standard in all new OTR trucks (by law) and in most commercial vehicles used in fleets. These devices can be connected to a cellular signal and can provide real-time data about the GPS location, mileage, fuel level and MPG of the vehicle remotely. The natural next step is to integrate this data into the fuel payment workflow, which can immediately eliminate buddy fraud by allowing only the necessary gallons and stop theft-driven fraud by verifying where the truck is filling up.

Newer fuel cards can provide a modern workflow that eliminates the long codes a driver currently punches into the keypad when they fill. The industry has already seen some early versions of this, with apps that let drivers make selections with a tablet instead of the keypad, but this has further potential. Imagine a world in which your integrated ELD system already knows how much fuel a truck needs, what load it’s carrying, and whether the driver needs to fill up DEF. This future is being built today by some of the players mentioned below.

As data visibility increases, Activant anticipates a cardless world in which RFID tagging and GPS geo-locating identifies the vehicle at the pump, knows the number of gallons to pump from the ELD system, and accepts ACH direct-debit (cash-priced) payments from a known account without the need to swipe a card. To realize this vision, core infrastructure at truck stops and gas stations will need to be reworked to accommodate the technology, but it will ultimately have to happen.

When we studied the market, we chose to segment the players based on the stakeholders served and where on the spectrum from a point solution to a full platform offer the product fit.

Trucking Payments

Three categories of start-ups emerged, each tackling the pain points in unique ways.

These are open-loop cards, targeting owner-operators and small-to-midsize fleets (~1-100 vehicles). They offer universal acceptance, modest discounts, lower fees, and better product user interface and flexibility. We believe they offer a differentiated value proposition, both from a product and a cost perspective, and they have seen solid traction (to the tune of tens of thousands of cardholders). It’s worth noting that most of these challengers are powered by Visa, which is committed to growing their fuel card payments network, to catch not just Fleetcor and Wex, but also to compete with similar efforts from Mastercard.

, which is mainly focused on mid-market OTR carriers, 

, which targets non-trucking commercial fleets, and 

Another category of challengers are logistics tech companies that are starting to offer fuel cards. Usually, these companies already have an existing adjacent solution targeted at carriers and are looking to expand their value proposition.

Emerging winners in this segment include companies like 

, which started out handling lumper, warehouse, repair and accessorial payments, all of which are much simpler than fuel. Relay just launched its own fuel card and Roadsync could follow suit. Other companies, such as 

, which offer a broader trucker workflow solution (often including load boards), as well as discount fuel networks such as 

, are also offering fuel cards. Brokerages like 

 have launched fuel solutions with existing partners like AtoB. Even 

, one of the ELD leaders, has started offering their own cards. New fintech issuer processors such as 

 have led the way on powering logistics payment solutions.

There are challengers looking to fundamentally reinvent the experience, offering a platform solution comprised of various combinations of hardware and software

 has built its own fuel payment network and is actively signing on carriers and truck stops in a very cost-effective manner. Similarly, 

 links commercial and personal cars to its own digital payment method, allowing drivers to pay for fuel without the need for a card.

If you’re an owner-operator or part of a fleet, you should seriously consider switching your card. You’re paying too much in hidden fees, higher prices, lost time, extra miles, and unnecessary fraud exposure.

We’re excited about the future of fuel cards and what it means for the industry. There hasn’t been enough innovation in the last 30 years, but things are changing – one card at a time – and we have no doubt that open-loop winners will emerge in the near-term to challenge the entrenched (and very profitable) duopoly. If you're building in this space, 

The information contained herein is provided for informational purposes only and should not be construed as investment advice. The opinions, views, forecasts, performance, estimates, etc. expressed herein are subject to change without notice. Certain statements contained herein reflect the subjective views and opinions of Activant. Past performance is not indicative of future results. No representation is made that any investment will or is likely to achieve its objectives. All investments involve risk and may result in loss. This newsletter does not constitute an offer to sell or a solicitation of an offer to buy any security. Activant does not provide tax or legal advice and you are encouraged to seek the advice of a tax or legal professional regarding your individual circumstances.

Opportunities to innovate with fuel cards

Pain at the Pump

If you’re a sneaker fan, you’ve probably wondered how Nike knows what style you want, when you want it, and where you might buy it. The answer likely has something to do with one of Activant’s former portfolio companies: 

. Nike acquired the forward-looking inventory management platform in 2019 to bolster their direct-to-consumer strategy by harnessing Celect’s optimization of merchandising planning to match customer purchasing behaviors. Direct sales grew to 39% by the end of the 2021 fiscal year.

 Compare this to the 16% achieved in 2011, and you’ll agree they’re doing something right.

When Celect was acquired, it was one of the only demand-predictive tools in the market that didn’t take a full inventory cycle to adjust purchasing and allocation parameters. With Celect’s technology integrated into Nike’s mobile apps and website, the shoemaker had the ability to serve consumers more personally at scale without any data-related delays.

Demand forecasting, an essential part of end-to-end supply chain management, is simply a process that predicts customers’ future demand for a product or service. This is essential for businesses to develop informed perspectives and ensure that the appropriate volume and type of stock flows to minimize the risk of understock, overstock, or obsolescence. 

Supply Chain Optimization Software

With new channels, increased demand signals, shorter product life cycles, and growing economic uncertainty, many firms are finding their current demand forecasting capabilities inadequate. This is exacerbated because supply chain leaders still cling to manual systems and antiquated software. 

Close to 75% of supply chain functions run operations using spreadsheets

. The remainder use IT planning solutions that are part of large enterprise systems offered by incumbents like SAP, E2Open, and Blue Yonder. More than 50% of supply chain planners use SAP Advanced Planning and Optimization (APO), which was introduced in 1998 and will no longer be supported from 2027.

 The imperative for a new solution could not be clearer.

Sellers in the traditional B2B world often struggle with poor forecasts. Even the most successful companies typically deal with 20% to 30% dead or obsolete inventory.

This dead stock costs sellers and manufacturers as much as 11% of their revenue.

 Estimates indicate that stale inventory in the US retail industry totals $50 billion a year,

and that a staggering 5 billion pounds of retail returns end up in US landfills annually.

There is a growing call to address this sustainability issue.

With inefficient legacy systems lacking the capabilities required and the very significant cost of poor forecasting, the market is ripe for disruption. 

Ferdinand Stockmann, Co-Founder & COO, Syrup

What pain points do winners need to address?

As retailers grow their omnichannel presence, they’ve started to prioritize forward-looking inventory management. Demand plans must align with multiple areas across the business, such as marketing, sales, and finance as well as external third parties. This means that the planning process requires additional workflow tools to enable collaboration with internal and external partners.

The need for demand forecasting to be dynamic and resilient is evident. Many solutions, however, are little more than pure regression models (often with seasonal overlays) for predictive forecasting. In a crowded market, this is unlikely to provide the differentiation and distinctiveness required to win. 

The vast majority of the solutions we identified target the SME market to avoid the challenges of integration and long sales cycles that McKinsey claims average 2.8 years from vendor selection to complete rollout in the Enterprise market.

These solutions tend to be narrowly focused on demand planning, but those offering a wider array of supply chain workflow tools are gaining traction in the Enterprise market. With large companies reluctant to replace ERP systems, integration of point solutions or suites is essential.

When we studied the market, it became clear that innovators differentiated themselves based on their sector focus or breadth of solutions. We also identified a range of solutions, from pure demand forecasting solutions to those with additional supply chain workflow tools. These tools include solutions that address elements such as supplier collaboration, production planning, and purchase order management.

We have, therefore, mapped the landscape using a vertical market vs. horizontal market focus on the one hand and a pure demand forecasting solution vs. a suite of demand forecasting and related workflow tools on the other hand. Most of the players mapped are system agnostic and are thus able to integrate with existing ERP or alternative sources to get historical and real-time internal data to use in their demand forecasting models and algorithms.

Demand Forecasting Software

It is early in the race, despite the clear imperative for next-generation solutions. The early winners are embracing AI, machine learning, and data analytics to speed up decision-making and lay the groundwork for autonomous planning. We like the solutions offered by:

, with a vertical market focus and a pure demand forecasting tool that is focused on providing a plug-and-play solution to support inventory decision-making in commerce. They’re enabling brands and retailers to accurately determine thousands of color-style-size-location combinations.

 which allows Shopify brands to take control of their inventory operations. The additional features embedded in the solution, such as purchase order management and financing, set them apart from competitors as they automate tasks that sit within adjacent supply chain workflows. 

, a pure demand forecasting tool with a horizontal market focus. This solution uses AI features to predict out-of-stock and warehouse product shortages, accurately forecast consumer demand, identify sales, and deliver supply chain insights.

, which leverages operational principles (such as the 

) with AI to offer an end-to-end solution. They use Demand Sensing to determine actual rather than forecast demand and then identify, manage, and automatically address potential bottlenecks. The solution delivers better operational and financial results. 

Our analysis revealed a landscape fraught with both challenges and opportunities to shape the future of demand forecasting software. Gone are the days of a company’s historical data being the single source of truth. The need for change is clear and the opportunities are vast. We have no doubt that there are start-ups building these solutions. If you are in this camp–we want to talk. 

Nike’s New Business Model Focusing on DTC: What Business Students Stand to Learn,

To improve your supply chain, modernize your supply-chain IT

The dead stock survival guide for manufacturers

The Cost Of Dead Inventory: Retail’s Dirty Little Secret

How Returns Drag Down Sustainability Efforts (and what Retailers can do About it)

This content may not under any circumstances be relied upon when making a decision to invest in any fund or investment, including those managed by Activant. Certain information contained in here has been obtained from third-party sources, including from portfolio companies of funds managed by Activant. While taken from sources believed to be reliable, Activant has not independently verified such information and makes no representations about the current or enduring accuracy of the information or its appropriateness for a given situation.

Activant does not solicit or make its services available to the public. The content provided herein may include information regarding past and/or present portfolio companies or investments managed by Activant, its affiliates and/or personnel. References to specific companies are for illustrative purposes only and do not necessarily reflect Activant investments. It should not be assumed that investments made in the future will have similar characteristics. Please see “full list of investments” at https://activantcapital.com/companies/ for a full list of investments. Any portfolio companies discussed herein should not be assumed to have been profitable. Certain information herein constitutes “forward-looking statements.” All forward-looking statements represent only the intent and belief of Activant as of the date such statements were made. None of Activant or any of its affiliates (i) assumes any responsibility for the accuracy and completeness of any forward-looking statements or (ii) undertakes any obligation to disseminate any updates or revisions to any forward-looking statement contained herein to reflect any change in their expectation with regard thereto or any change in events, conditions or circumstances on which any such statement is based. Due to various risks and uncertainties, actual events or results may differ materially from those reflected or contemplated in such forward-looking statements.

A balancing act between innovation and market realities

The Future of Demand Forecasting Software

We think that internal tooling technology has reached an inflection point. 

What was already a fast-growing category of software is getting more sophisticated by the day. And in today’s macroeconomic environment where everyone – engineering teams included – has to do more with less, 

The recent Cambrian explosion of infrastructure platforms has been a boon to all builders of technology; but in today’s market, it’s a survival of the fittest. We believe that no-code and especially low-code platforms can now materially affect the age-old build vs buy question for startups and enterprises alike. Because what once was a clear 

, and at lower long-term cost with more flexibility, with the use of these platforms.

And with the even more rapid rise of Large Language Models, it’s clear that the way that everyone – technical and non-technical users alike – interacts with and builds software is subject to change. It’s an exciting time for internal tooling – let’s dive in.

Some problems can be perfectly solved with off-the-shelf software. Some can’t. Companies spend over 30% of their developer resources building internal software

to solve the unique challenges that only their business faces. These challenges could be anything from exposing databases to non-technical users through analytics dashboards or creating user management portals with CRUD functionality. Teams may need to create automations for complex workflows, professionalize the execution of regular scripts or build custom applications like CRM’s that fit their needs in a way that Salesforce can’t.

of developer resources dedicated to building internal software

Most internal tools are mediocre to use and even less enjoyable to build – for those that have the technical ability.

 Often with no clear link to revenue, internal projects are often under-resourced; the best developers want to work on customer-facing projects. User feedback is weak due to the lower user counts from users who have no alternative solutions if they’re unhappy with the software. Where developers on customer-facing problems get quantitative metrics on how well every feature in their app performs, developers of internal tools might have an interview with someone from HR. Finally, the people who are closest to the underlying problems, business users, can’t build the solutions that they need.

 (LCNC) tools emerge. Focused exclusively on internal tools, these products are all about function over form. Products from companies like 

 get builders to a professional, scalable solution fast with 

 are opening up app development to a whole new world of potential builders with 

And it’s about time. There are only 31.1 million trained software developers, amounting to a global shortage of 1.4 million, which is set to rise to 4 million by 2025.

 Firms that we’ve spoken to have seen an 80% reduction in the time taken to ship a product developed with low code. Meanwhile, developers amount to less than 3% of total global knowledge workers.

 One can only imagine the possibilities of bringing the remaining 97% into software development.

Projected shortage of software developers by 2025

Reduction in time taken to ship a product developed with low code

These tools promise to speed up building things like customer dashboards, but we have also spoken to younger start-ups who are building their entire software infrastructure on LCNC for absolute control.

We are seeing the early signs of mass adoption of no-code/low-code development tools for internal software.

The End of ZIRP and Beginning of New Build or Buy Decisions

Where interest rates will be a year from now is anyone’s guess, but one thing is clear – the period of excess is over. Its 

 and many start-ups are now serious about getting burn under control. Every expense on the income statement is going to come under scrutiny. We’ve 

discussed the ever-expanding the number of apps that companies use

, and this could be an area for some easy cuts. There is definitely some low hanging fruit here but we believe that the existence of low-code tools fundamentally changes the build vs buy decision. If you can cut build time by 80% with the advent of low-code tools like Airplane, Retool or Superblocks, it suddenly becomes 

 more attractive to build internally vs buying the next flashy SaaS tool.

Take Meta and their "Year of Efficiency." In Mark Zuckerberg's 

"investing in tools that will make us most effective over many years, not just this year — whether that’s building AI tools to help engineers write better code faster, enabling us to automate workloads over time, or identifying obsolete processes that we can phase out."

He cites that their new open source compiler, 

engineers using Buck2 often produced meaningfully more code"

And as infrastructure investors, this is something that we care deeply about. While the infrastructure layer of any tech stack can be a great place to be, many early-stage infrastructure businesses face graduation risk – the point where it’s cheaper for your customers to build the solution for themselves. Again, the advent of low-code might drastically change the economics of the build vs buy decision. 

There could be large ripple effects through broader software markets.

Automation-Enabling Technologies

Revisting the Activant Thesis Map we presented in our 

, we see internally focused LCNC tools as a deeply innovative and high-growth emerging area.

Generative AI is undoubtedly the most innovative technology that we have seen in the recent past. Large language models are exploding, both in their computing capacity requirements and their capabilities. The most well-known Generative AI application is ChatGPT, whose model is based on GPT-3, a 175 billion parameter machine learning model that is guestimated to have cost $10mn - $20mn to train (exact figures are unknown).

 However, it is unclear where the competitive advantage lies, and if it is in sheer scale or distribution advantages, then the benefits of this AI wave are likely to be captured by existing mega-cap technology companies. Ultimately, we see a large degree of variation in potential outcomes here.

Andrey Kurenkov, Last Week in AI, GPT-3 is No Longer the Only Game in Town

The growth of modern data infrastructure is more certain. Humanity continues to grow the creation of data at exponential rates and simultaneously place ever greater requirements for the operationalization of that data, in real-time. Another infrastructure play, 

, are providing exciting tools for machine learning engineers to enhance productivity & improve model explainability. While the tools inherent in providing a visual interface to produce code are slightly less innovative and more deeply wedged into existing workflows, we see this as a key growth area going forward, for all of the reasons already discussed.

 to develop software by using out-of-the-box templates, pre-built UI components and API connectors. Development is done in intuitive visual environments with the principles of point and click & drag and drop. Essentially, no-code abstracts away the complexity of code and presents it to the user in the form of a graphical user interface. True to the name, anyone in the organization can build software without writing a single line of code.

Low-code tools are aimed at developers, who can augment their traditional coding using the principles of no-code to rapidly speed up development. Low-leverage activities are powered by the low-code environment so that developers can focus on their highest-leverage activities. Fundamentally, low-code enables developers to 

Internal Tooling

Employees at LCNC start-ups have made it clear to us, the choice to be either low-code or no-code is a critical philosophical decision. This early positioning creates organizational ripples from go-to-market strategy to company culture.

Another key defining trait in this market is whether tools focus on powering dashboards and data visualization (

) or automating workflows and scheduled tasks (

As we see it, the no-code vs low-code and data vs workflow orientation becomes a key differentiator across the market. Software buyers should be sure of exactly what they want to achieve and who their users are.

, on the no-code, data-oriented end of the spectrum, should find success within their niche, by giving non-technical users in the organization the ability to monitor data that is stored in databases which those users would otherwise be locked out of without learning SQL.

 will unlock app development for the whole organization to automate and manage workflows like service requests, risk assessments and document reviews.

 will allow developers to build sophisticated admin panels and dashboards with access to key database & data warehouse integrations like PostgreSQL, MySQL and Snowflake.

, for example, have made it very clear that they are geared toward developers. While the company does provide UIs for classic dashboards, their key value proposition is to professionalize workflows being run with cron jobs and ad-hoc scripts.

For these products to be fit for the enterprise, they need to be delivered within the context of quality features primarily in security and compliance. We have seen a large portion of the landscape adopt single-sign on, granular permissions management and audit logging. 

 have built request and approval flows into the product, while also being deployable on premise, often a key consideration for customers regulated by GDPR.

 appear to have pulled ahead with enhanced features like version control with git, automated testing and observability integrations. Built to bring developers and product managers together into one tool, companies like 

 lead the way with collaboration features. A common issue with low-code apps has been the ability to debug code that is hidden behind pre-built UI’s. 

 and Appsmith have built debugging and troubleshooting tools into their editors.

There is an inherent trade-off between extensibility and accessibility. No-code tools like 

 provide a huge library of templates to allow business users to build software in minutes. But apps can become limited by available templates and components. Many companies extend functionality by allowing code-based editing, such as Superblocks who support front-end editing with Javascript and back-end editing with any language. Airplane’s approach to this problem is noteworthy - their product sacrifices accessibility by being accessed as code, but by embedding itself within their customer’s codebase, removes the limits of what developers can build.

Many tools provide seat-based pricing at the lower tiers with a freemium model. The freemium model is highly favorable for driving growth through testing and iterating. However, seat based pricing can become prohibitive as the number of users scaled and potentially difficult to validate for simple use cases making a few database queries.

We started writing this piece last fall, and the extent to which the conversation around LLMs has changed has been astonishing. The internet is buzzing on 

 and its ability to assist programmers, while the 

 now turns natural language prompts into code. Its suggested that co-pilot is writing up to 40% of the code for its users. Low-code/no-code has the explicit goal of rapidly speeding up application development, and we expect to see the application of AI to this space to accelerate rapidly.

. LCNC presents users with a graphical user interface, which is how the vast majority of humans interact with machines, but a natural language interface (i.e., a chat conversation) might be a far superior model. Integrating tools as powerful as co-pilot into existing LCNC tools might be an immense accelerator. Further, it could be just the step change in capabilities that will allow no-code software development to have a moment.

Speaking at Berkeley last month Nvidia CEO Jensen Huang said:

“For the last 40 years, we have made computers harder and harder for people to program and that's why the technology divide has been so large and the technology divide is getting larger and larger except till 1 day, all of a sudden, everyone can program a computer. You just have to prompt this thing to write a program for you, do something for you, automate something for you."

 We wholeheartedly agree – but take it with a grain of salt coming from a key supplier that stands to benefit from the coming AI wave.

The promise of bringing one billion knowledge workers into the software development flow would represent a complete phase transition in software markets – but we’re still a ways out. While no-code users are extracting immense value from these tools, they don’t have the capability to transform the market. Product managers that we have spoken to note that the primary issues that these tools run into is the fact that they are 

. As we dig into later, there is an inherent trade-off between ease of use and extensibility. Today, that is a major hurdle that no-code is bumping into. As the market is structured today, it's really low-code that promises to be an exciting area for the future.

Based on our conversation with spoken to product managers, who we believe that the world is 

 going to move in the direction of LCNC, but a few factors limit this. Where an organization has already built the majority of their software, it is tough to implement low-code/no-code tools that live outside of the codebase, which would require building everything from scratch. Developers tend to love using low-code tools, but can only deeply embed them into organizational development flows with the buy-in of product managers. Without overcoming these hurdles, software built with LCNC techniques tends to live in siloes, being used only for a few discrete tasks. A paradigm where the world’s software is built on LCNC, will require deep organizational buy-in. 

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Hometown

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Rebecca Rodseth

Research Analyst

Office

Hometown

Residence

Research

Relevant Experiences

Rebecca
Rodseth