How Software Gets Built
A Field Guide to the Lifecycles

Chapter 7 of 18 Practitioner · 11 min

I have shipped software through four of these and watched the other four arrive. A stand-up that quietly replaced a sign-off gate. An API contract that seventeen squads built against at the same time. An evening last week when I handed an agent a goal and reviewed what it had written. The same phases underneath every time. Only the choreography changed.

// the crux

Every team builds through some lifecycle – Waterfall, Agile, Lean, and now the agentic loop. Eight approaches, one SDLC spine, and a single ruler they all answer to: working software in front of a real user. AI changes the loop, not the spine.

// in one breath
  • Nine names get thrown around. Sort them into three layers and most of the confusion goes away.
  • Only two are rival lifecycles. Three are priority lenses. Three are ways an AI does the building. And the SDLC is none of those – it is the spine the rest rearrange.
  • One feature, eight ways; a fingerprint for each; and the exact point where every one of them tends to break.

Ask ten engineers how software gets built and you will hear the same handful of words, usually as if they were nine competing answers to one question. Waterfall. Agile. Mobile-first. API-first. AI-first. Spec-driven. Vibe coding. Agentic. And the plain old SDLC underneath all of them. Lined up like that, they look like a menu you choose one item from. They are not. They are not even the same kind of thing.

That is the single idea that makes the rest of this guide easy. These nine names live on three different layers, and once you can see the layers, you can stop arguing about which one is right and start asking which one fits the work in front of you.

Layer A · Methodology
How the whole delivery is organised
A full lifecycle, end to end. These are the genuine rivals: pick one and it shapes every phase.
Waterfall · Agile
Layer B · Stance
What you optimise for first
A priority lens that layers on top of a methodology. It does not replace Agile; it tells you what wins when something has to give.
Mobile-first · API-first · AI-first
Layer C · Execution
How the building itself happens
New ways to move through the build now an AI is in the loop. They change how code appears, not how the project is run.
Spec-driven · Vibe coding · Agentic

Read it once more from the top: only Waterfall and Agile are full, rival lifecycles. The three first stances are lenses you hold over whichever lifecycle you already run. The three AI-era styles change how the build phase happens, not how the whole thing is steered. And the SDLC is not a tenth contender at all. It is the spine the other eight rearrange, which is exactly why we will come back to it at the end.

the line of descent

Where Each One Came From

None of these arrived in a vacuum. Each was a reaction to the pain of the one before it, and you can read the whole history as a single line bending toward shorter feedback loops and faster correction. Here is the lineage, in the order it actually happened.

1970 WaterfallMethodology
Plan the whole thing, then build it once, top to bottom. Named in a 1970 paper that actually held it up as a cautionary example.
2001 AgileMethodology
Stop pretending you can specify it all up front. Ship a thin slice, learn from it, repeat. Formalised in the 2001 manifesto.
~2010 Mobile-firstStance
As the smartphone took over, design for the smallest, most constrained screen first, then scale up to the desktop rather than down to the phone.
2010s API-firstStance
As the API economy matured, agree the contract before anyone writes the code, so many teams and many clients can build against it at once. The ancestor of spec-driven development.
2016 AI-firstStance
Around 2016 Google publicly reframed itself from a mobile-first to an AI-first company: assume a model is the core of the product and design around what it can do.
2024 Agentic codingExecution
As coding agents arrived, hand a goal to a system that plans, edits across the repo, and runs the tests, while you set the goal and hold the gates.
2024–25 Spec-driven devExecution
Push AI past autocomplete: write the specification precisely and let the model implement it and be checked against it. API-first generalised from one endpoint to a whole feature.
2025 Vibe codingExecution
Named by Andrej Karpathy in early 2025: describe what you want in plain language, run what the model writes, and keep tuning by feel without reading every line.

Notice that the colours cluster. The blue era was about organising people. The amber era was about choosing a constraint to respect. The purple era is about who, or what, is holding the keyboard. Three different questions, which is why they never really competed.

same destination, eight routes

One Feature, Eight Ways

Abstractions are slippery, so make it concrete. Take one small, universal job: let a user who forgot their password get back into their account. Here is how each of the eight named approaches would actually go about it. Same destination every time. Very different journeys.

Waterfall
Write the full reset specification, get it signed off, then design, build, and test it as part of a release that ships months later.
Agile
A "reset password" story enters the next sprint and ships in a week or two, then gets refined from how real users actually fare with it.
Mobile-first
Design the phone flow first – a tap straight through from the email, an autofilled code – then widen it to the desktop, not the other way round.
API-first
Define the reset endpoints and payloads as a contract, and let web, mobile, and backend teams build against it in parallel from day one.
AI-first
Ask whether it needs a password at all – passkeys, a risk score, a model deciding when to demand a second factor and when to wave a known device through.
Spec-driven
Write a precise spec – token lifetime, rate limits, every state and error – and have the AI generate the implementation and its tests directly from it.
Vibe coding
Prompt "build me a password reset with an email token," run it, and nudge it until it works. Perfect for a prototype. Not, on its own, for production.
Agentic
Hand an agent the repository and the test suite, let it plan and edit across files and run the tests, and review the pull request it opens.

Read top to bottom and you can feel the loop tightening. Months, then weeks, then an afternoon, then minutes. That tightening is the whole story of the last fifty years, and the bottom three rows are simply where it has reached now.

the shape of each one

What Each One Feels Like to Work In

A methodology has a texture. You can tell which one you are in by the rhythm of your week long before anyone says its name. Here is each approach by its characteristic shape – what it feels like, what it is genuinely good for, and the moment it tends to fall apart. The colour of each card tells you which layer it belongs to.

Waterfall Methodology

A staircase you walk down once. Each phase finishes and is signed off before the next one begins, and turning back up the stairs is expensive.

BestFixed, well-understood scope, often where a contract or a regulator demands the plan up front.
BreaksThe day the requirement changes – which, on a long enough project, is every day.
Agile Methodology

A short loop you run again and again. Plan a slice, build it, ship it, learn, and let what you learned reshape the next slice.

BestEvolving scope with a real feedback channel to users you can act on quickly.
BreaksWhen the ceremonies stay but the engineering is weak. No framework saves a team that cannot build.
Mobile-first Stance

Designing for the hardest seat in the house first – the small screen, the thumb, the flaky network – on the bet that if it works there, it works anywhere.

BestWhen most of your users arrive on a phone, which for most consumer products is now the default.
BreaksWhen dense, desktop-class workflows get cramped into a compromise built for a phone.
API-first Stance

Agreeing the handshake before anyone builds. The contract is the product, and teams build against it in parallel. The direct ancestor of spec-driven development.

BestMany consumers and many parallel teams that need a stable interface to share.
BreaksWhen you freeze a contract before you understand the domain, and every team inherits the guess.
AI-first Stance

Starting from what the model and the data can do, and designing the product around that capability rather than bolting a model onto something already shipped.

BestWhen an AI capability is the actual value, not a garnish on it.
BreaksWhen "AI" is a label with no real capability or data underneath it.
Spec-driven Execution

Writing the blueprint so precisely that the building falls out of it. The spec is the source of truth; the AI implements it and is measured against it.

BestWhen you can actually specify the thing, and you want AI speed without losing the rails.
BreaksA vague spec produces vague code, generated faster than you can review it.
Vibe coding Execution

Conducting rather than typing. You describe intent, the model writes, you keep what feels right. Karpathy's phrase for giving in to the vibes and barely reading the diff.

BestPrototypes, throwaways, weekend experiments, and learning a new corner of the stack.
BreaksThe moment it reaches production unreviewed and the unread lines start to matter.
Agentic Execution

Delegating to a tireless junior that plans, edits across the repository, and runs the tests, while you own the goal and stand at the gates where it matters.

BestWell-scoped, verifiable tasks with strong tests and clear guardrails.
BreaksFuzzy scope, or no review gate to catch a confident mistake before it ships.
the fingerprint

Eight Approaches, Side by Side

If the cards are for feel, this is for decisions. The same five questions asked of every approach, so you can scan down a column and compare like for like. Read across a row and you have its fingerprint.

Approach Layer Unit of work Who drives Loop length Where AI sits
Waterfall Methodology A signed-off phase document Analyst and project manager Months Absent
Agile Methodology A user story in a sprint A cross-functional team One to two weeks Optional assistant
Mobile-first Stance The smallest-screen experience Designer and front-end Rides the host method Assistant
API-first Stance / bridge The API contract Architect and API designer Contract up front, then parallel Assistant
AI-first Stance The model capability and its data Product with ML and data Experiment-driven The core of the product
Spec-driven Execution A precise feature spec Author writes spec, AI builds Hours to days Pair, then driver
Vibe coding Execution A natural-language prompt The developer and model, by feel Seconds to minutes Driver, loosely held
Agentic Execution A goal handed to an agent The agent acts, a human checks Minutes to hours Driver, gated

One column repays a slow read: where AI sits. It moves from absent, to a helper at your elbow, to a pair at the keyboard, to the thing actually driving while you watch the road. That migration is the real reason the old process questions feel unsettled. We changed who holds the keyboard without changing the road.

the spine underneath

The One Ruler They All Measure Against

So where did the SDLC go? It never left. The software development lifecycle is not a ninth approach you would choose instead of Agile or vibe coding. It is the set of phases that every one of them rearranges. Strip away the branding and the same nine stages are always there, from first conversation to long-lived change. The methodology decides how you move through them; it does not get to skip them.

Here is the spine in full – the same nine phases this series uses elsewhere – with who acts, the gate that says a phase is done, and what it leaves behind.

Phase Who acts Milestone gate Deliverable
01 · AnalyzeAnalyst, product, stakeholdersRequirements agreedAcceptance criteria
02 · DesignArchitectDesign signed offArchitecture, domain model, contracts
03 · DevelopEngineers, increasingly with AICode completeThe implementation
04 · TestQA and engineersQuality gate passedA passing suite and coverage
05 · BuildRelease engineeringArtifact producedA deployable artifact
06 · DeployDevOps and SREReleased to productionA running system
07 · MonitorSRE and on-callObservability in placeDashboards, alerts, SLOs
08 · DeliverProduct and deliveryValue accepted by usersThe outcome, demo, sign-off
09 · ChangeThe whole teamChange managed safelyVersioning and a rollback path
↳ see also · Chapter 13 – The SDLC Practitioner's Map takes these nine phases and crosses them with eight structural forces, one reference grid for where AI helps and where it bites.

Now the trick that makes the whole landscape click. Every approach in this guide is just a way of weighting and reordering these nine phases. Lay them side by side against the same spine and the differences stop being slogans and become choices about where the work goes.

Waterfall
Runs all nine once, in order, with a hard gate between each. Heavy on Analyze and Design, because going back is so costly.
Agile
Runs all nine inside every sprint, lightly, then runs them again. The gates become conversations instead of sign-offs.
Mobile-first
Reweights Design and Build around the most constrained client, and makes the store-review wait a first-class fact of the Build phase.
API-first
Pulls the contract to the front of Design, so Develop and Test can run in parallel across teams against a shared interface.
AI-first
Starts Analyze from the model and the data, and rebuilds Monitor to watch output quality, not just uptime.
Spec-driven
Loads the weight onto Analyze and Design, the spec, then lets AI carry Develop and Test directly from it.
Vibe coding
Collapses Design, Develop, and Test into one fast loop, and often skips Monitor, Deliver, and Change entirely. That omission is why it is prototype-grade.
Agentic
Lets the agent run Develop and Test and propose Design, while humans keep Analyze and stand at the Deploy, Monitor, and Change gates.

Look at the bottom three rows again. The AI-era styles do not invent new phases. They move the human's attention to different ones. Vibe coding bets you can skip the back half. Agentic coding bets you can delegate the middle if you guard the ends. Both bets are about the spine, not about the model.

// why this matters more than the tool you pick

The choreography changed. The phases did not. Which is why teams that struggle with AI rarely have a tooling problem. They have a process pointed at the wrong phase – writing for the spine they used to have, not the one they are standing on now.

A field guide tells you what you are looking at. It does not tell you it is easy. The hard part was never choosing a name off the menu; it is knowing which phase of the spine your current trouble actually lives in, and being honest about which approach quietly skips it.
// carry forward

You have the lifecycles. Next, the pressures reshaping them: the eight forces the AI era puts on how software gets built – the overview map before the next four chapters walk it phase by phase. That is Chapter 8.