Many teams believe they're working in Agile, but if value only reaches users at the end of a project, it's still waterfall in disguise. True agility means delivering small, vertical slices of working software early and often, because the real risk lies in human assumptions, not code. Grounded in lean engineering, this post explores why learning, not launching, is the true purpose of an MVP, and how AI makes fast feedback more essential than ever.
Agile delivery is a mindset, not a meeting schedule.
Too often, teams claim they're “doing Agile” while still planning one big, final go-live at the end of the project. The stand-ups are daily. The boards are digital. The terminology is spot on. And yet, value doesn't reach the end user until the very last sprint.
That’s not agile. That’s waterfall in a sprint suit.
True agility is measured not in ceremonies but in delivery. If you’re waiting to deploy until the end, you’re simply waterfalling in slow motion. The longer you delay getting real features in front of real users, the more risk you accumulate, and ironically, the very risk Agile aims to reduce.
At its core, Agile is about responding to change through early and continuous delivery of valuable software - and the agile principles, of course, but more on that another time.
This means breaking work into vertical slices, small, end-to-end pieces of functionality that traverse the full stack. A feature isn’t “done” if it’s only coded. It’s only done if it’s been deployed, used, and learned from.
Agile isn’t about speed. It’s about validated learning. Each sprint should end with something live, something touching the UI, logic, data, and infrastructure. Anything else is a guess in a silo.
Even the most enthusiastic Agile team can find themselves slipping into waterfall patterns without realising.
You start with good intentions, but then the go-live gets pushed to the end. Testing becomes its own phase. Integration waits until 'everything is ready.' And before you know it, you’ve got a six-month build cycle with a “sprint retrospective” after the fact.
The tooling looks Agile. The language sounds Agile. But the delivery is waterfall.
Unfortunately with many large projects, in large organisations, this is often the way.
Every time you defer deployment, even of a basic feature, you’re deferring learning. That delay compounds.
You lose the chance to test assumptions in the real world. You miss user feedback when it's still easy to adapt. And most dangerously, you let teams drift, working in parallel on features that haven't been tested together, based on assumptions that haven't been validated.
When it finally all comes together, it’s not a launch, it’s well known and well documented integration hell.
Agile delivery should be a spike through all the layers, every sprint touching front-end, back-end, data, infrastructure, and deployment. If you’re not pushing code all the way through to production in every cycle, then something’s wrong.
You’re not testing the full system. You’re not getting the full feedback. And you're not reducing the real risk: people and behaviour.
One of the best ways I have seen this idea represented is in Basecamp's Shape Up.
Without deploying anything live, every completed to-do is untested and should be met with some healthy suspicion. By completing one whole feature and deploying it live, something works in total.
Of course coding to interfaces and defining APIs is very powerful and useful from an engineering standpoint. But when thinking of the project as a whole you must think in verticals, or spikes through the whole cake.
(image credit: Basecamp Shape Up)
Of course what these diagrams do not show is the verticals represented by a true product in the wild. I'll again defer to an image to best convey the point. This is from another great book on making things by Tony Fadel - Build.
As makers, entrepreneurs building things, or passionate product owners, it's tempting to forget the whole customer life cycle (and this is true for internal customers, which can be even more challenging as they have other time constraints and demands). You may perfect the product, but onboarding, access, and usage may be a blocker.
Most project risk doesn’t live in your codebase, it lives in your people's heads.
Misalignment. Ambiguity. Assumptions. Unspoken expectations. Unknown or unpredicted behaviour and process. These things are the silent killers of progress, and they don’t show up until real users start doing real things.
That’s why early delivery is so critical. It doesn’t just test your software, it tests your thinking. It forces clarity. It reveals edge cases. It brings assumptions into the open, when they’re still easy (and cheap) to fix. The biggest risk factor on any technical project, and especially transformation, is people and process.
One of the biggest misunderstandings in Agile delivery is what an MVP actually is.
It’s not a trimmed-down list of features. It’s not a teaser before the real launch. It’s a learning device, the simplest thing you can build to test a real-world assumption and validate the direction you're heading.
The “V” in MVP stands for viable, meaning it needs to be complete enough to deliver some value. But the most important value isn’t functionality, it’s insight.
If you’re not learning, you’re not shipping an MVP. You’re just deferring the pain.
Of course, I reference Lean Startup by Eric Ries who coined the term, inspired by agile and what value truly means when customers are hard to define, unknown, or potentially don't know what they want.
Sometimes you can’t release to production immediately. Maybe there’s regulation. Maybe there’s risk. Maybe your users aren’t ready yet.
In those cases, staging environments and internal UAT are understandable. They’re practical attempts to simulate the real world. But let’s not pretend they’re anything more than that: simulations.
Staging helps you catch obvious bugs. But it doesn’t show you how a real user will react. It doesn’t surface how your system behaves under real load, real data, and real pressure. It doesn’t generate the learning you need to adapt and improve.
So yes, use staging, but know it’s a proxy. The real test is production. I have learned to be very suspicious of all proxies for reality. You should never trust a proxy.
High-performing Agile teams don’t just sprint. They flow.
They integrate continuously. They release frequently. They monitor behaviour, learn from users, and adjust. Their pipelines are tight. Their slices are thin. Their feedback loops are fast.
They aren’t waiting for “the big day.” Every day is delivery day.
And importantly, they treat MVP as experimentation, not partial completion. They push code to production early.
These teams don’t fear production - they live in it. Because that’s where the value is.
You can follow all the Agile rituals, the standups, the retros, the Jira boards, and still end up stuck in waterfall.
For me, Agile only works when it's grounded in lean engineering. That means optimising for flow, cutting waste, and learning as early and often as possible. If you’re holding back your go-live until the end, you aren't doing any of those things.
Agile isn’t about building fast. It’s about learning fast.
So ask yourself: are you delivering working software into the hands of users each cycle? Or are you just queuing up features for one big, delayed release?
As AI reshapes how we build software, the core principles of Agile become more important, not less.
AI lets us generate code faster, automate tests, predict outcomes, and even simulate user behaviour. But none of that removes the need to learn from the real world. In fact, it makes fast feedback and tight delivery loops even more critical. Why? Because the cost of overbuilding and the risk of misunderstanding grows when AI accelerates everything.
Agile isn’t just a project management method, it’s an antidote to complexity. And in a world where AI can generate an entire system in a day, the only thing that keeps us aligned with reality is human-centred, iterative validation.
If you’re still planning to deploy everything at the end, you're not just working against Agile, you’re working against the very adaptability that makes AI valuable in the first place.
The future belongs to teams who can integrate AI and stay lean, curious, and relentlessly focused on what works in the real world.
If any of this feels familiar, maybe it's time to take a closer look.
We offer a free, friendly delivery review where we’ll help you map out your flow, spot your blockers, and identify where waterfall may be creeping in.
No judgement. No jargon. Just practical advice to help your team ship better, faster, and with more confidence.
It's often breaking things down into what can be delivered now. The core foundation. Then building iteratively from that. Ensuring each sprint delivers an improvement even if just 1% gain.
👉 Book a free agile delivery review with Newicon
Or just drop me a message on Linkedin. I’m always up for a chat about cutting through the noise and building real value.
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