What 'Done' Actually Means: The Complete Delivery Checklist

The Scenario

You paid $50,000 for a "complete" application. You received a GitHub link with a message: "It's all there. Good luck."

This scenario plays out more often than anyone in the industry wants to admit. A company hires what seems like a reputable contractor, pays good money for a custom application, and receives a repository full of code. On the surface, everything looks complete—the features work, the interface looks polished, and the demo went well. But the moment your team tries to take ownership of the system, the gaps become painfully obvious.

What Happens Next

The predictable nightmare unfolds with frustrating consistency. Your internal team starts the handoff process, and within hours, they’re discovering that what looked like a complete delivery is actually just the beginning of months of remediation work. Here’s what typically surfaces in the first few weeks after contractor handoff:

2 weeks trying to deploy to production

The code runs locally, but production deployment requires undocumented infrastructure, missing configuration files, and secret keys nobody thought to document.

No tests, so every change is a gamble

Without automated tests, your team becomes afraid to modify anything. Every bug fix or feature addition risks breaking something else in ways you won't discover until production.

No monitoring, customers report outages first

You discover problems when angry customers contact support, not from alerts or dashboards. Your mean time to detection is measured in customer complaints.

No runbook, incidents become all-hands emergencies

When something breaks at 2am, there's no documentation on how to diagnose or fix it. Every incident requires waking up senior engineers and improvising solutions.

These aren’t edge cases or worst-case scenarios. This is the predictable outcome of the industry’s broken definition of “done.” The contractor delivered exactly what they promised—working code—and the gaps only become visible when your team tries to operate, maintain, and evolve the system over time.

The Industry Norm

The Unfortunate Reality

Most contractors consider "done" when code is pushed to a repository and the immediate features work in a demo environment. Everything else—deployment infrastructure, operational procedures, documentation, monitoring, testing—falls into a category they'll describe as "out of scope." They're not necessarily wrong according to the industry's standards. They're just operating under a definition of completeness that leaves buyers with months of additional work.

The frustrating part is that this isn’t malicious. Most contractors genuinely believe they’ve delivered a complete product when they hand over working code. The industry has normalized this incomplete definition of “done” to the point where suggesting anything more comprehensive seems like scope creep or gold plating.

The Cost

Understanding the true financial impact of incomplete deliveries requires looking beyond the initial contract price. When you receive code without operational readiness, you’re not saving money—you’re deferring costs in a way that typically makes them more expensive to address later.

Real Financial Impact

3-6 months to make contractor code production-ready internally

Your team spends this time building the missing CI/CD pipelines, writing tests, setting up monitoring, creating documentation, and establishing operational procedures. This is work that should have been part of the original delivery.
$20K-$100K additional engineering time

At $150-200/hour for senior engineers, the remediation work quickly exceeds 20-30% of the original contract value. For complex systems, it can exceed 50%. This doesn't include the opportunity cost of delaying other projects.
Lost opportunity cost while stabilizing

While your team is making the code production-ready, they're not building new features, serving customers, or generating revenue. The system sits in limbo between "delivered" and "operational," creating a gap where value can't be realized.

This brings us to the fundamental question that should be asked before every software contract is signed: What does “done” actually mean? Not in the aspirational sense, but in the concrete, verifiable, operationally-complete sense that allows your team to own and maintain the system from day one.

The Checklist

We believe the best way to answer this question is to make our definition of “done” completely transparent and verifiable. So we published it.

We Published Our Standard

We open-sourced our entire delivery checklist—all eight categories, with specific deliverables and acceptance criteria. You can fork it, use it in your RFPs, judge us by it, or adopt it for your internal teams. It's completely free and requires no registration.

View ioanyt-delivery-standard on GitHub

The IOanyT Delivery Standard

Our standard defines eight categories that must be included in every delivery. This isn’t a wish list or aspirational framework—this is the minimum set of deliverables required for production-ready software. Here’s what each category includes and why it matters:

Category	What’s Included	Why It Matters
Code Quality	80%+ test coverage, linting configured, type safety enforced, code review standards documented	Without automated tests and quality gates, changes become risky and velocity drops as teams become afraid to modify the codebase. Test coverage ensures confidence in future modifications.
CI/CD Pipeline	Automated lint, test execution, security scanning, and deployment on every push	Manual deployments create bottlenecks, introduce human error, and reduce deployment frequency. Automation validates every change consistently and enables continuous delivery.
Infrastructure as Code	Terraform/CloudFormation configurations, environment reproducibility, version-controlled infrastructure	Without IaC, production environments drift from staging, disaster recovery becomes impossible, and spinning up new environments takes days instead of minutes. IaC enables reliable, repeatable infrastructure.
Monitoring & Alerting	Application dashboards, key metrics tracked, alerts configured, PagerDuty/OpsGenie integration	Reactive incident response means customers discover problems before your team. Proactive monitoring surfaces issues immediately and reduces mean time to detection from hours to seconds.
Architecture Documentation	System diagrams, data flow documentation, service dependencies mapped, integration points documented	Tribal knowledge creates single points of failure. New engineers take months to onboard. Departures become emergencies. Documentation enables team scalability and knowledge transfer.
API Documentation	OpenAPI/Swagger specifications, integration guides, example requests/responses, authentication flows documented	API consumers shouldn’t need hand-holding to integrate. Complete API documentation enables self-service integration and reduces support burden while accelerating partner onboarding.
Runbook	Incident response procedures, common issues and resolutions, troubleshooting flowcharts, escalation paths	2am incidents shouldn’t require waking up the original developers. Runbooks enable on-call engineers to diagnose and resolve issues systematically, reducing mean time to resolution.
Handoff Guide	Team onboarding checklist, access setup procedures, local development guide, deployment walkthrough	Your team should own the system from day one without dependency on the contractor. Complete handoff documentation enables immediate operational ownership and reduces knowledge transfer time.

The Key Insight

This isn't "gold plating" or over-engineering. This is the minimum requirement for production software that a team can actually operate and maintain over time. Everything in these eight categories represents work that has to happen eventually—the question is whether it happens during the contractor's engagement or becomes your team's problem afterward. Deferring this work doesn't eliminate it; it just makes it more expensive to address later when the original developers are gone and context is lost.

Why Code Alone Is Technical Debt

Let’s break down the real cost of incomplete delivery by examining what happens when each category is missing. These aren’t theoretical concerns—they’re the predictable operational consequences that surface within weeks of taking ownership of code-only deliveries.

1. No Tests = Change Fear

Without automated test coverage, every modification to the codebase becomes a risk calculation. Developers can't confidently refactor code or fix bugs because they have no way to verify that their changes didn't break something elsewhere in the system. This fear leads to conservative development practices where teams avoid touching existing code even when it needs improvement.

The consequences compound over time. Technical debt accumulates faster because nobody wants to address it. Quick fixes get layered on top of existing problems rather than solving root causes. The codebase becomes increasingly fragile, and development velocity drops as teams spend more time manually testing and debugging unexpected side effects.

Impact: Development speed drops 60% over 6 months as fear of breaking things slows every change.

2. No CI/CD = Manual Deployments

Manual deployment processes mean someone on your team has to "run the deploy script" every time you want to release changes. This person becomes a bottleneck, and deployment timing gets dictated by their availability rather than business needs. Weekend deployments become the norm because teams are afraid to deploy during business hours without extended rollback windows.

Human error becomes the primary deployment risk. Someone forgets a step in the deployment runbook, deploys the wrong branch, or misconfigures an environment variable. Each deployment becomes an event that requires coordination, communication, and stress rather than a routine operation that happens transparently in the background.

Impact: Deployment frequency drops from weekly to monthly due to fear and coordination overhead.

3. No IaC = Environment Drift

Without infrastructure defined as code, production environments gradually drift from staging as manual changes accumulate over time. Developers make "quick fixes" directly in production that never get applied to staging. New services get added to one environment but not others. Configuration files diverge. "Works on my machine" becomes a daily occurrence because nobody can reproduce the exact production setup.

Disaster recovery becomes impossible because nobody can definitively document the exact configuration of the production environment. Creating a new staging environment for testing takes days of manual work and inevitably differs from production in subtle but critical ways. The lack of environment reproducibility makes it impossible to validate changes before they reach production.

Impact: 3+ days required to reproduce environments, making disaster recovery and scaling prohibitively slow.

4. No Monitoring = Reactive Operations

Without monitoring and alerting, customers discover problems before your operations team does. Users experience errors, performance degradation, or complete outages and contact support to report them. Your first indication of a production issue is an angry customer email or a spike in support tickets, not an automated alert that fired when metrics crossed a threshold.

Every incident starts with "what happened?" rather than "here's what's broken." Your team spends the first hour of incident response trying to understand what's failing and how long it's been broken. Mean time to resolution extends from minutes to hours because the diagnostic phase has no data foundation. Incident response becomes reactive firefighting rather than systematic problem resolution.

Impact: Average 4-hour incident response time due to lack of monitoring data and proactive alerts.

5. No Documentation = Tribal Knowledge

Without architecture documentation, the original developer becomes a single point of failure for understanding how the system works. Critical knowledge about design decisions, integration patterns, and system behavior exists only in their head. When they leave the project or company, that knowledge leaves with them. New engineers face a months-long archaeological dig through code to understand systems that should have been documented from the start.

Onboarding new team members takes three months instead of three days because there's no written context to accelerate learning. Engineers have to reverse-engineer architecture decisions from the code itself, often without understanding the original requirements or constraints that shaped those decisions. Team scaling becomes prohibitively expensive because knowledge transfer happens through tribal knowledge and mentoring rather than documentation.

Impact: 3-month ramp time for new engineers, making team scaling expensive and contractor departures risky.

6. No Runbook = All-Hands Incidents

Without documented incident response procedures, every problem escalates to senior engineers regardless of severity. The on-call engineer who receives a 2am page has no documented procedures for diagnosing or resolving common issues, so they immediately escalate. What should be a 15-minute fix handled by a junior engineer becomes an all-hands emergency requiring multiple senior engineers.

Incident response becomes improvised rather than systematic. Each incident is handled from first principles because there's no documentation of similar past incidents or proven resolution procedures. The same problems get debugged repeatedly by different engineers, and lessons learned from previous incidents aren't captured for future reference. Mean time to resolution remains high because each incident response starts from zero context.

Impact: 5-person team needed for every incident because knowledge isn't documented and procedures don't exist.

These six failure modes aren’t isolated problems—they compound each other. No tests makes deployments riskier. No CI/CD means manual deployments happen less frequently. No monitoring means problems go undetected longer. No documentation means incident response takes longer. The absence of operational completeness creates a downward spiral where each gap makes the others worse.

The Question for Your Contracts

Look at your last contractor deliverable. How many of these eight categories were included?

If the answer is less than 8, you didn't receive a complete delivery. You received code that still requires months of internal work before it can be operated in production. You paid for a product but received a prototype that needs significant additional investment to become production-ready.

The Contractor Comparison

Understanding the gap between what contractors promise and what they deliver requires looking at the specific language used in proposals and comparing it to actual deliverables. Here’s what the common promises actually mean in practice:

What They Say	What They Deliver	What’s Missing
”Production-ready”	Code that runs locally and passes demo scenarios	Deployment infrastructure, monitoring systems, operational runbooks, incident response procedures
”Complete solution”	Features work as specified in acceptance criteria	Automated tests, CI/CD pipeline, environment reproducibility, documentation for maintainability
”Enterprise quality”	Complex architecture with many services and layers	Operational readiness, team handoff materials, troubleshooting guides, long-term maintainability considerations
”Full documentation”	README file with local setup steps	Architecture documentation, API specifications, runbook for operations, onboarding guide for new team members

The language gap isn’t necessarily deceptive—it’s a difference in what “production-ready” and “complete” mean to contractors versus what they need to mean for operational teams. Contractors often define completeness in terms of feature delivery: “Does it do what the spec says?” Operations teams define completeness in terms of operability: “Can we run this without the original developers?”

Questions to Ask Before Signing

The best defense against incomplete deliveries is asking specific questions before signing the contract. These five questions force clarity about operational completeness and surface gaps early when they can still be addressed in the scope and pricing:

The 5 Questions That Separate Complete Deliveries from Code Dumps

1.

"What does your delivery checklist include?"

If they don't have a documented checklist, they haven't systematized completeness. Every project will be different based on who's leading it. Ask to see the checklist—it should include operational categories, not just feature lists.
2.

"Can I see an example handoff package?"

Completed handoff materials from a previous project show what you'll actually receive. Look for runbooks, architecture docs, CI/CD configurations, and monitoring setup—not just code and a README.
3.

"Who maintains this after you deliver?"

This question forces clarity about operational ownership. If they assume ongoing maintenance contracts, the delivery won't include operational completeness. If they assume your team takes over, there should be materials enabling that transition.
4.

"What's your test coverage standard?"

Specific numbers matter. "We write tests" is different from "80%+ coverage with both unit and integration tests." Ask how coverage is measured and what happens if coverage drops below the threshold.
5.

"Will we receive a runbook?"

A runbook means documented procedures for common operations and incident response. If they don't include runbooks in deliveries, they're assuming either ongoing support from them or learning-by-doing for your team.

If They Can't Answer

If a contractor can't provide clear, specific answers to these questions, they're planning to hand you code, not a production system. They may deliver working features, but you'll spend months making it operationally complete.

Walk away and find a contractor who defines "done" the same way you do.

The Standard Is Public

Transparency about delivery standards serves everyone in the industry—buyers know what to expect, contractors have a reference for operational completeness, and the overall quality bar rises. We published our standard for four specific reasons:

1. Accountability

Publishing our standard creates public accountability. You can judge our deliveries against our own documented criteria. If we fail to meet our standard, it's public and verifiable. We can't quietly lower the bar or claim something was "out of scope" when it's listed in our published checklist.

2. Industry Improvement

The more organizations that adopt comprehensive delivery standards, the more pressure exists for all contractors to meet that bar. If enough CTOs include our checklist (or similar standards) in their RFPs, incomplete deliveries become commercially unviable. Market forces can raise the industry baseline.

3. Transparency

No hidden surprises in scope or pricing. When you evaluate our proposals, you know exactly what "done" means before signing anything. The checklist makes deliverables explicit and creates shared understanding between us and clients about what operational completeness actually requires.

4. Proof

Our standard is verifiable, not claimed. You can check our GitHub repositories, examine our handoff materials from past projects, and see whether we actually deliver what we document. Claims are cheap; publicly auditable standards backed by real deliveries are meaningful proof.

How to Use It

The delivery standard works for multiple audiences and use cases. Whether you’re evaluating contractors, building internal standards, or conducting code reviews, the checklist provides a systematic framework for operational completeness.

For Evaluating Contractors

Include the complete eight-category checklist in your RFP and make completion of all categories a contractual requirement. Use it as acceptance criteria—delivery isn't complete until all eight categories are satisfied. This prevents scope ambiguity and ensures contractors price the work correctly upfront.

For Internal Teams

Adopt this as your internal delivery standard for all projects. Use it during sprint planning to ensure operational categories are included in estimates, not just feature work. Make it part of your definition of done—stories aren't complete until tests, documentation, and operational materials are delivered alongside code.

For Code Reviews

Validate deliverables against the checklist during code review. Don't approve pull requests that add features without corresponding tests, documentation updates, or monitoring instrumentation. Make operational completeness a blocking requirement at the PR level, not something to address "later."

For Scoping

Include all eight categories explicitly in statements of work with specific deliverables for each. Make completion criteria measurable—test coverage percentages, specific documents to be delivered, monitoring dashboards to be configured. Remove ambiguity about what "done" means before work begins.

Download the Standard

Free. Open source. No registration required. Fork it, adapt it, use it in your RFPs, or adopt it for your internal teams.

View ioanyt-delivery-standard on GitHub

What Complete Delivery Enables

The value of operational completeness isn’t just about avoiding problems—it’s about enabling a fundamentally different operational mode. Teams that receive complete deliveries operate at a different velocity and stress level than teams spending months remediating code-only handoffs.

Before (Code Only)

Months to production — Your team spends weeks building missing infrastructure, tests, and documentation before deployment is possible.
Incidents = emergencies — Every problem requires all-hands response because there are no procedures or documentation.
Onboarding = tribal knowledge — New engineers spend months learning from code archaeology and tribal knowledge.
Changes = risky — Without tests, every modification risks breaking something in production.
Ops = firefighting — Reactive operations with manual processes and constant crises.

After (Complete Delivery)

Days to production — Complete operational materials mean immediate deployment capability.
Incidents = procedures — Documented runbooks enable systematic response by on-call engineers.
Onboarding = documentation — New engineers ramp up in days using architecture docs and handoff guides.
Changes = confident — Comprehensive test coverage enables confident refactoring and feature development.
Ops = systematic — CI/CD pipelines, monitoring, and IaC create predictable, automated operations.

The ROI Calculation

The financial case for complete delivery is straightforward when you calculate the true cost of remediation work versus paying for operational completeness upfront.

Time Value of Complete Delivery

Without Complete Delivery

3-6 months of internal engineering work required to reach production-ready state. At $150-200/hour for senior engineers working half-time on remediation, this represents $50K-$150K in additional costs beyond the original contract value.

With Complete Delivery

Production-ready on delivery day. Your team can deploy immediately and focus on feature development rather than operational remediation. The upfront cost is higher but the total cost is significantly lower.

Net Savings

$50K-$150K in saved engineering time, plus faster time-to-market, reduced operational risk, improved team morale, and elimination of the "code handoff crisis" that typically accompanies contractor departures.

The Strategic Advantage

Teams that receive complete deliveries can focus on building features.

Teams that receive code-only deliveries spend months on operations.

The difference isn't just cost or timeline—it's strategic positioning. While your competitors are still making contractor code production-ready, your team is shipping features, responding to market feedback, and building competitive advantages. Operational completeness creates a velocity gap that compounds over time.

Which team do you want to be?

Take Action

For CTOs

Download our delivery checklist and include it in your next RFP. Make operational completeness a contractual requirement.

View on GitHub

For Teams

Fork our standard, adapt it to your context, and raise your internal delivery bar. Make it part of your definition of done.

Fork on GitHub

Work With Us

We deliver to this standard on every project. No exceptions. Receive complete, production-ready systems.