TL;DR

Coding is no longer the constraint. It’s now cheaper than ever to make software. But there are supply side constraints on innovation, and getting apps to market. Who dreams up something worth making? How do apps get in front of users? There’s also a demand side constraint on adoption – how do people learn about the new possibilities available to them?

Background

I forwarded this post about multi-agent orchestration (and token exhaustion) to a colleague, and it got me thinking about where the bottlenecks are if agents can code whilst you sleep.

The irony here might be that it was Gene Kim who put Michael Tomcal’s post into my timeline, and he knows a thing or two about Theory of Constraints after re-spinning ‘The Goal‘ as ‘The Phoenix Project‘ and again as ‘The Unicorn Project‘.

Theory of Constraints

Let’s back up a moment… why am I even talking about constraints?

I’m very much a disciple of Theory of Constraints, through the work of Gene Kim and others in the DevOps community. It was the central organising principle for my work at DXC Technology, and continues to be a lens that I often peek at the world through.

Most systems will have a small number of constraints, and it’s a good idea to figure out which is the primary constraint; because if you optimise anywhere except for that constraint you’ll either be piling up work faster at the choke point, or building a wider highway down the road from where all the traffic is stuck.

Constraints and Software

Building software is expensive. I know that because I work in an industry where people get paid a lot (relative to say nurses and teachers, or even doctors and professors). Just take a look at levels.fyi for data.

We often conflate software engineering with coding, but is coding actually the constraint? Over my time in the industry there’s been a succession of (often overlapping) changes that have brought down the cost of coding:

• Higher level languages
• Integrated Development Environments
  • Context aware autocomplete
• Visual programming
• Component libraries
  • Open Source Libraries
• Outsourcing / offshoring / nearshoring
• No Code / Low Code
• AI coding assistants
• Agentic development

Getting from idea to code is cheaper than it’s ever been. But then the cost of getting from idea to code has kept falling (something like) 10x per decade, so arguably no seismic shift is happening.

Where do the ideas come from?

OK, so it’s cheaper than ever to get from idea to code. But who’s even having the ideas, and are they good ideas?

Richard Seroter recently wrote about an agentic adventure with ‘Will Google Antigravity let me implement a terrible app idea?‘. Refuting Betteridge’s Law, the answer here is yes. The AI tools let him implement a terrible app idea. They also let him implement the app terribly, but that’s probably material for another post, another time (meanwhile there’s discussion over on LinkedIn).

Why didn’t Richard implement a great app to show off Antigravity? My guess is that he didn’t have an idea for a great app formed an ready to go; whilst it was easy to dream up a terrible app.

The limit case – personalised apps for everything

I sometimes like to wonder what the limit case is for something – if we take it to the ultimate extreme. In this case, “what if everybody could imagine up perfectly customised apps for their every need?”.

It’s clearly ludicrous, because most people don’t even customise the settings on the apps they have. They don’t have the time, or the inclination to even learn what’s possible; which is why sensible defaults are so important, because that’s what most people will use.

People just want to get on with their lives and work, with minimal friction imposed by the tools they choose to help them with that.

The innovators and change makers spot problems they feel obliged to solve – itches they have to scratch. Everybody else is glad that somebody else is doing that work.

Supply side constraint #1 – innovation

This brings us to a limiting factor – a constraint. The set of people who have ideas for apps worth building is not everybody. It might be a larger set than the people currently making apps, but it’s finite, and probably not much larger.

It’s also worth noting that innovation is generally a team sport[1], which is why it’s great to see my pal Killian (along with his former colleagues from Meta) building tools expressly for teams.

Supply chain friction

Coding is only a small part of engineering, and engineering is only a small part of getting a product to market.

It’s one thing to get my app working at http://localhost:8000, or in the phone emulator on my IDE. Quite another to get it running on secure and robust infrastructure, or through the review process and published on an app store. That might not matter for the limit case above where I’m the only user. But it matters a lot if you want other people to use it; and a whole lot more if you want other people to pay for it. Chris Gregori sum’s this up with ‘Code Is Cheap Now. Software Isn’t‘.

Supply side constraint #2 – syndication

Entry level cloud hosting might be free, but there’s still work involved in using it; and if people show up then the bills will follow.

It’s a similar story for mobile apps. Apple and Google might not charge to get things into their stores. But the review process can often be slow and frustrating; and that can repeat every time there’s an update.

How do people know?

Ok. You’ve had a great idea, you’ve built the app in no time, it’s in a marketplace where people can find it (and maybe even pay). How does anybody with the need for what the app does even know?

This is a demand side constraint. People have limited time and attention; and they’re mostly already at saturation point with everybody else who’s shouting ‘buy my stuff’.

It’s really hard to get noticed. Dare Obasanjo recently posted some X screencaps of a Hendrik Haandrik thread that observed that:

In the last 3 months, about 24k new subscription apps were shipped…

Out of those 24,000 apps, a grand total of 700 (less than 3%) made more than $100.

Read that again
$100, not $100k
The odds are very much stacked against you

Demand side constraint – attention

How’s your better belly button fluff remover app going to get noticed in the sea of other apps? How do people worried about their belly button fluff even know that there’s now salvation? A lot of brands are spending a lot of money to get people’s attention (that’s what’s gotten us ‘filter failure at the outrage factory‘). You want your thing to be a viral hit, but all the social media sites are suppressing organic content in favour of more paid ads. It’s tough.

Conclusion

People have been asking ‘if AI coding is so great, where are all the apps?’. Hopefully I’ve shed some light on answering that question. The apps are stuck at various constraints that exist on both the supply side (having good ideas, and the dealing with supply chain beyond coding) and the demand side (getting people’s attention to know there’s something new that’s worth their time).

Theory of constraints tells us we should move our attention now to unblocking those constraints. It’s going to be a LOT of work…

And…

It would also be remiss of me not to mention Peter Evans-Greenwood’s excellent work on this topic, particularly ‘Are We in 1886? And 1919? ‘ subtitled “When a technology wave requires two grammars that history kept separate”:

The UK 1873-1896: Supply-Side Grammar. The technology worked but deployment was bespoke and expensive. The missing piece was coordination infrastructure for installation.

The US 1919-1925: Demand-Side Grammar. The technology was deployable but unaffordable for the mass market. The missing piece was coordination infrastructure for purchasing.

History kept these gaps separate. They never overlapped. Electrification solved its supply-side problem (1873-1896) decades before automobiles faced their demand-side problem (1919-1925).

Today, for the first time, both gaps must be solved simultaneously.

Note

[1] My friend Jamie Dobson has a great post that includes a rebuttal of ‘The Lone Genius Myth’.