Noodling on platform engineering, AI, and 'time to market'

tl;dr: the onset of rapid prototyping dev crews will increase both the speed and size of the organizational foot-gun. ("Survival is not mandatory." - Deming)  Platform eng folk should consider time-to-onboard-a-service as an inbound KPI.  All software engineering should rejoice that competent orgs will, c/o rapid prototyping, provide a somewhat more regular flow of meaningful work.

One of the chief concerns of enablement, devex, and frankly what has probably been the secret actual goal of software orgs for the last 10-20 years has been 'time to market'.  Gotta get the MVP out the door before the competitor!  And this has spawned the soul-crushers 'velocity metrics' and 'developer efficiency', which have only really led to purposeless stress and anxiety.

Things have changed - as did before, and will tomorrow - and suddenly there is plausible tech available to accomplish rapid prototyping of MVPs (or whatever you want to call them) - and thus 'time to market' can be reduced significantly.  You can spin up a dozen flavours of your idea for validation without an army of developers, and without the haunting sunk cost fallacy tempting you to production-ize them.  

You are enabled to delete your prototypes once you have learned from them - a superpower!! - and then set to work building the right thing, which is, frankly, also a superpower.

I think this is a paradigm shift then, for enablement and platform engineering folks.  The goal for so long has been cycle-time-ahhh-panik! and now there's effectively some breathing room - easier to be invested in the work when it matters.  Feedback loops are still crucial, but for better reasons now.

Having written all of this, we will still be dealing with realities of modern software development - namely, dependency stagnation (platform decay), sociotechnical momentum, and the ever-changing market landscape.  The sociotechnical momentum is worth pausing on - by this I mean to describe what happens when you get a whole bunch of people centered around a specific mission and goal and you build and build and build and one day wake up to the reality that the market pivot you'd hoped would be farther out is here...and you can't turn the ship fast enough.

And so another enabler - superpower - of AI is going to be the opportunity to truly treat code as disposable.  The whole rising and falling of organizations c/o disruption curves suddenly can be internalized at low cost, no longer requiring superstar tiger teams and blind luck.

Yet, the only thing being solved for right now is 'day1' stuff.  Which means that platform engineering/enablement isn't going anywhere.  The complexity of handling a growing business, unique customer needs (I have yet to see an org avoid pandering to high-roller customers), boons/limitations of internal skillsets and experiences, high variation in languages/frameworks, and the constant need to be keeping systems updated and secure - never mind the realities of compliance ecosystems that are only going to proliferate more as time goes on - all of these things are beyond the wild AI dreams of today, even knowing what we have already seen.  

We would do well to remember that silver-bullet thinking does not lead to adaptive systems.

So, the mild noodling I've done leads me to posit that we have a shift in platform engineering coming/here:

  • The advent of said superpowers will create fantastical amounts of debt across all ends of the system in incompetently managed organizations - this mis-management will rapidly destroy the ability for organizations to adapt.
  • Internal startups should start to become more of a normal thing (maybe a new era for branding?), where parent organizations create child orgs and absorb them back in to the parent brand (consider the ramifications of AI law clerks).
  • Disciplined deletion of prototypes will become a proxy metric for AI-competency.
  • Performance of an engineering org will hopefully be considered through how well they balance the rapid prototyping and sustainable core-business systems - so a core part of platform engineering will be 'how quickly can we get these prototypes into users' hands?', i.e. automation of ingestion/distribution/deletion.
  • Cost management will need to be more firmly established as a cultural norm - sprawl is designed in to 'rapid'; nasty cloud spend surprises await the fool-hardy here.
  • Velocity metrics will shift over to the rapid prototyping crews - who are we kidding, they are not going away.
  • Developer efficiency-focus will always be a thing, but perhaps now it'll actually mean something.  Being efficient at shipping the right thing isn't such a bad endeavour.
That's as far as I'll take 'describing complexity' for today.  Interesting times ahead.

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