Feel like your roadmap keeps shrinking while delivery dates stay the same?
A lot of teams are not “slow at coding.” They are slow at everything around coding. Lokalise’s Developer Delay Report found developers lose an average of 3 hours per week to tool failures, outages, and workflow problems, which adds up to nearly 20 workdays a year. The same report notes 44% missed a deadline because of a tech or tool issue, and 25% say they spend more time debugging than writing new code.
That is why “speeding up by 50%” is not a fantasy goal. It is often the natural result of removing friction, shrinking rework, and automating the pipeline.
In this guide, you will see what MAD services are, where the time actually goes, and how a custom software development service built around Modern Application Development can move delivery forward without trading quality for chaos.
The Fastest Teams Are Not Coding More, They Are Losing Less Time
Atlassian’s 2025 State of Developer Experience survey highlights a blunt reality: developers do not spend most of their week writing code. Atlassian notes developers spend about 16% of their time coding, and big time-wasters include finding information, adapting to new tech, and context switching.
This matters because most “speed programs” focus on the visible part of work, like coding output. But the bigger lever is reducing wait time and repeated work across the software delivery lifecycle.
Atlassian also reports that 68% of developers save more than 10 hours a week with AI tools, but 50% still lose 10+ hours per week and 90% lose 6+ hours due to organizational inefficiencies. That gap is where a real 50% improvement often lives.
What Are MAD Services?
MAD services, short for Modern Application Development services, are a managed delivery model designed to make software delivery predictable, fast, and repeatable.
Instead of treating each project like a fresh start, MAD focuses on building a system that makes delivery easier every sprint: shared components, automated testing, CI/CD, infrastructure as code, and clear product discovery so the team is not guessing.
A strong MAD-led custom software development service combines three layers.
Product discovery that prevents rework
Speed dies in the second and third rewrite. MAD starts by locking the minimum usable scope, defining success metrics, and turning fuzzy ideas into buildable user stories.
This step is not “documentation for the sake of documentation.” It is about removing churn. If requirements keep changing because nobody agreed on what “done” looks like, no amount of engineering talent will save your timeline.
Cross-functional pods that ship outcomes, not tickets
MAD delivery usually runs in pods (small squads) that include engineering, QA automation, and a product owner-style role, so decisions do not bounce around for days.
The point is simple: fewer handoffs, fewer approval loops, more momentum.
A platform layer that makes shipping routine
This is the layer many teams skip, then regret later.
A mature MAD setup standardizes how software is built, tested, secured, deployed, and observed. It makes routine work self-serve and reduces the “we can’t release today because…” surprises.
If you want a clean way to think about it, MAD is not “work faster.” It is “make the system faster.”
Where The 50% Speed-Up Actually Comes From
If you want to accelerate delivery, you need to stop measuring effort and start measuring flow.
DORA’s research has consistently used delivery performance metrics like deployment frequency and lead time for changes to understand what separates top performing teams. JetBrains, citing the 2024 DORA research report, highlights huge real-world gaps: elite performers deploy 182x more frequently, recover from failures 2,293x faster, and achieve 127x faster lead times than low performers.
Most teams are not trying to become “elite” overnight, but those numbers show something important: large performance differences are possible when process and tooling stop blocking the team.
In practical terms, MAD services create speed in four places.
Less rework from clearer decisions early
A short discovery sprint can remove weeks of rework later. When the team agrees on scope boundaries, acceptance criteria, and edge cases early, you avoid building the wrong thing fast.
MAD teams also design for change. They define what can evolve later (nice-to-have features) vs what must be stable (core data model, authentication flows, billing logic).
Shorter feedback loops through automation
If QA is mostly manual, every sprint ends with a bottleneck. MAD shifts testing left and automates high-value scenarios early: regression, API tests, and critical user flows.
This is where “50% faster” becomes realistic. You are no longer waiting for a human-heavy testing phase to find out you broke something two sprints ago.
Faster releases through CI/CD that is actually trusted
CI/CD is not just “we have a pipeline.” It is “we can release without fear.”
MAD emphasizes:
- Smaller, safer changes
- Feature flags to separate deploy from release
- Automated checks that block risky builds
- Rollback strategies that are practiced, not theoretical
When release is routine, you stop batching huge risky changes, and delivery speed climbs naturally.
Fewer late-stage security surprises
Security delays are one of the most common “hidden taxes” on delivery.
The Black Duck 2025 OSSRA report found that 90% of audited codebases had open source components more than four years out of date. Old dependencies create urgent patch work, compatibility issues, and fire drills that wreck sprint plans.
MAD services integrate software supply chain checks, dependency monitoring, and security testing into the workflow, so security work does not show up as a last-minute stop sign.
The Speed Traps MAD Services Are Designed To Remove
You cannot fix what you do not name. Here are the problems that drag software teams down, and how MAD targets each one.
Scope blur that keeps restarting the same conversations
You see this pattern when teams keep “reconfirming” requirements in sprint 4 that should have been settled in sprint 1.
MAD fixes it with clear story mapping, decision logs, and defined product outcomes. Not heavy paperwork. Just enough structure that the team is not building on moving sand.
Tool failures, downtime, and workflow friction
The Lokalise report is a painful reminder that engineering time is often burned by instability, not complexity. Developers lose about 3 hours per week to tool failures and workflow problems, and 61% regularly handle troubleshooting beyond their job description.
MAD addresses this by standardizing environments (containers, IaC), creating stable pipelines, and reducing the number of tools people must juggle to ship code.
Documentation and knowledge being trapped in people’s heads
Atlassian highlights “finding information” as a top time-waster for developers. If the team has to hunt for API details, services, or past decisions, delivery slows even when people are motivated.
MAD services usually add lightweight knowledge practices:
- A single source of truth for architecture decisions
- Self-serve runbooks
- Living API docs generated from code
- Clear ownership per service
It is not glamorous, but it removes daily friction.
AI used for speed, then paid back in debugging
AI can help, but only when used intentionally.
Stack Overflow’s 2025 Developer Survey press release reports 84% of developers use or plan to use AI tools, but 46% do not trust the accuracy of AI outputs. It also notes 45% say debugging AI-generated code is time-consuming.
MAD services treat AI as an assistant, not an autopilot. They add guardrails: code review standards, security scanning, and tests that catch issues before they turn into production bugs.
What MAD Looks Like Across 30, 60, And 90 Days
Every organization is different, but MAD delivery has a common rhythm. If you want a practical view of how speed builds over time, here is a realistic path.
First 30 days: remove guesswork and stabilize the foundation
Most of the “speed” in month one comes from clarity and removing friction.
Typical outcomes:
- A clean roadmap that separates must-haves from nice-to-haves
- A delivery plan with milestones the business can trust
- A working CI pipeline and baseline automated tests
- A deployment workflow the team can run repeatedly
The goal is not perfection. It is control.
Days 31 to 60: shift quality left and make releases routine
This is where teams feel the difference in momentum.
You start expanding test automation, improving build times, tightening code review practices, and moving toward smaller changes shipped more often.
Delivery improves because the team is not constantly stopping to fix preventable issues.
Days 61 to 90: scale delivery without scaling chaos
Now you focus on throughput and predictability:
- Performance and observability baked in
- Stronger security automation
- Reusable components and templates
- Internal tooling that reduces repetitive setup work
This is often the stage where “we’re moving about 50% faster” becomes believable, because the system is no longer fighting the team.
When You Should Use A Custom Software Development Service For MAD
MAD services are most valuable when speed and reliability matter at the same time.
You are a strong fit if:
- You have a product roadmap but delivery keeps slipping
- Your team spends too much time firefighting
- QA and releases feel like a weekly crisis
- Dependencies and security issues keep derailing sprints
- You need to ship faster without adding a large full-time team
This is also where a custom software development service adds leverage. You are not only buying developers. You are buying a delivery system, ready to run.
What To Ask Before You Hire MAD Services
Not every vendor that says “modern delivery” actually has modern delivery.
Ask these questions and listen closely to how they answer.
How do you prevent rework early
A good partner can explain their discovery process in plain language: how they define scope, handle unknowns, and make trade-offs.
If the answer is vague, you will pay for it later.
What does your CI/CD and testing baseline look like
If they cannot describe how they keep releases safe, they are probably relying on heroics, not systems.
How do you handle security and dependency risk
Look for supply chain awareness. Black Duck’s OSSRA findings about out-of-date components show why this cannot be an afterthought.
How do you measure speed
If speed is only “story points,” be careful. Better signals include lead time, deployment frequency, and failure recovery, aligned to DORA thinking.
Choosing the right custom software development service is less about a flashy tech stack and more about whether they can build a process your team can live with.
A Realistic Note About “50% Faster”
You can absolutely speed up delivery by 50%, but it usually comes from a bundle of improvements, not a single trick.
MAD services work best when you combine:
- Clear scope and outcomes
- Stable toolchain and environments
- Automated testing and trusted CI/CD
- Security integrated into delivery
- Better knowledge flow inside the team
If you only do one of these, you will improve, but you will not feel a major shift.
Conclusion
When developers lose weeks each year to workflow friction, missed deadlines, and preventable debugging, speed is not about hiring more people. It is about building a delivery system that protects focus.
That is what MAD services are designed to do. And when done right, they are one of the most practical ways to get a 50% jump in delivery speed without turning your release cycle into a risk machine.
If you want Trifleck to map this to your product, we can review your current delivery flow, identify the top three bottlenecks, and propose a MAD rollout plan that fits your team size and deadlines. A custom software development service should make shipping feel calmer, not louder.
