What is Shift Left Testing? Everything Engineering Leaders Need to Know

Shift left testing is still the gold standard for catching bugs early on engineering teams, and for good reason.

But as code gets written faster and faster, and codebases expand quickly, shifting testing left often just backlogs devs with more review, more testing, and more bottlenecks. In fact, at Atlassian, a team with over 6,000 engineers, coding is now roughly 15% of how they spend their time. The rest goes to new bottlenecks, including problem framing, validation, and alignment.

Shift-left testing still works to catch bugs, but the traditional shift left testing approach is creating bottlenecks for many engineering teams today. PR cycle times are still as long as ever. You're catching bugs, but some bugs are still slipping through the cracks. "Shift-left testing" is still the best recommendation, but it's not keeping pace with the way your team, and your codebase, is growing.

In this article, we'll break down the types of shift-left testing, how and why they work, and how to implement shift-left testing for an agentic era to improve code quality, while automating more testing, sooner.

What is shift-left testing?

Shift-left testing is a software development approach where engineering leaders "shift" the testing to earlier in the software development lifecycle. Engineering leaders typically adopt shift left testing as a way to catch bugs sooner (when they're easier to fix), collaborate more effectively, and streamline the development timeline.

If traditional project planning is a straight line from ideation and coding, progressing along a timeline toward testing, QA, and production, shift-left testing simply shifts left the phase of testing to earlier in the timeline.

Shift-left testing vs. traditional testing

In a traditional SDLC, testing happens "on the right" of the timeline. Coding and development happen first, and then, when they're done, testing and validation. Validation acts as a single checkpoint before production that catches what slipped through all the previous steps. The problem is, by the time a bug reaches that gate, it's expensive and time-consuming to fix, and it often derails project plans and timelines at that point.

That cost curve is well documented. Our research on AI code review for modern engineering teams found that the longer agents work on a codebase without validation, the more expensive every subsequent change becomes, because the codebase itself gets progressively harder to work with.

Many engineering leaders are now shifting testing left, which moves that validation earlier in the SDLC. Instead of waiting until the development is done to check your work, validation, testing, and QA happen concurrently, making bugs and errors much less effort (and cost) to fix.

Types of shift-left testing

"Shift left testing" has become a bit of a catch-all term for any type of SDLC that moves testing "left," or emphasizes it earlier in the development lifecycle. However, when it comes to implementation, there are far more technical ways to consider and think about shift-left testing:

• Traditional shift left testing
• Incremental shift left testing
• Shift left testing in agile
• Model-based shift left testing
• Agentic shift left testing

Traditional shift left testing

Traditional shift left testing has generally corrected an overemphasis on acceptance and UI-based testing, as described by Donald Firesmith at Carnegie Mellon's Software Engineering Institute. Rather than focusing on system-level testing late in the process, it "shifts left" to emphasize testing earlier in the process, with API testing and integration testing.

Incremental shift left testing

Incremental shift left testing, as the name suggests, shifts testing left by making testing incremental throughout a waterfall development cycle. Rather than using a strict, single waterfall, as teams break down development into smaller incremental waterfalls, testing also shifts to become increments of corresponding parts of development.

In short: as development, testing, and delivery happens incrementally within the SDLC, testing is also shifted to occur both (a) earlier in the development process, and (b) incrementally throughout the process, so that unit testing is occurring for the phases of the project in development, alongside operational testing for the phases of the project being launched, and so on.

Shift left testing in agile

In agile frameworks, engineering teams work in short "sprints" rather than a large "V" or "waterfall" process of software development. As such, shift left testing in agile shifts testing left by making it a part of each sprint, rather than doing all the development, then all the testing, as with a traditional V or waterfall method.

However, shift-left testing in agile can also mean introducing testing earlier in the sprint. Rather than leaving testing to the end of a sprint, engineering teams test throughout the sprint, preventing and fixing bugs as they code rather than after.

Model-based shift left testing

Model-based shift left testing shifts even further left, de-coupling testing from coding. Instead, it focuses on testing and validating requirements, architecture, and design to prevent bugs and errors and create stronger foundations with which to build from.

In this case, you start testing almost at the beginning of the project instead of waiting for there to be code ready to test. You might write unit tests and other tests prior to development, then test against them. But in general, the goal is to uncover systemic and structural issues that will cause more problems down the line, and eliminate them early. In this way, model-based shift left testing can actually be used alongside other models.

Agentic shift left testing

Agentic shift left testing shifts testing left (earlier in the software development lifecycle) by using AI agents to perform testing, review code, do security checks, and run agentic looping cycles on AI- or human-written code.

This is the natural evolution of shift-left testing in an agentic era. Agentic code review tools like Greptile can check PRs against your entire codebase, run security testing, and spin up sandboxes to find runtime errors that can't be spotted by just reading a diff. If you're using agents or agentic workflows like Claude Code or Codex to write code, you can set up agentic loops to test it, create fixes, and ensure the code is working properly before a human ever reviews it.

One caveat worth designing around: models are worse at reviewing their own code than they are at reviewing another model's. The blind spots that produced a bug are the same blind spots at play when the same model reviews it, so the reviewing agent should not be the one that wrote the code.

Benefits of shift left testing

For most engineering teams, the benefits of shift-left testing are evident:

• Finds bugs sooner, reducing development costs and timelines. The earlier in the process you can find and fix bugs, the easier, faster, and cheaper they are to fix. Not only have you not invested significant resources in development, but you have less finalized code that can easily be adjusted.
• Better allocation of resources. Testing too late often means that too few resources (time and human) get allocated to testing. Testing is often rushed to meet deadlines. Testing earlier in the process allows for more time, more thorough testing, and better allocation of resources between development and testing.
• Less last-minute, all-hands-on-deck panic. Testing late in the SDLC creates lots of panic at the end of a project, as a major bug is found and thousands of lines of code need to be patched and re-written with just days or weeks to go before the deadline. Testing early allows you to have an accurate view of your code and how much work remains to be done.
• Agentic shift left testing allows testing to happen faster and more continuously. This compounds the results of good testing by making it more consistent, ongoing, and easier. As code volume increases while your engineering teams incorporate more AI and agentic coding into the process, agentic testing keeps up with the volume of code, without losing quality or security.
• Improved code quality and software architecture. As AI coding becomes more and more common, the way we need to test and review code changes. Our job as engineering leaders is not to just shift testing left and then leave it as a backlog on our developers. Nor is it to avoid testing at all, or until all the code is ready, and then saddle our QA team with it. Agentic shift left testing can catch bugs humans would otherwise miss, create cleaner, higher quality code, and help automate code validation.

Limitations of shift left testing

Of course, shift left testing has limitations too, and engineering leaders need to be aware of them so you can account for them.

• Increases developer workloads. Shift-left testing can increase the scope and workload of the developer role by making them more responsible for testing and code quality. One way we account for this at Greptile is by introducing Greptile review agents. By having agents review pull requests early, they can find and fix both obvious and complex bugs, removing tedious review from dev workloads and speeding up your overall PR cycle times.
• Some bugs can't be found by just reading a diff. Earlier testing often equates to static testing. But without early runtime or sandbox testing, you'll miss bugs that only show up in live environments. At Greptile, we fix this by implementing TREX: our runtime validation system that spins up a sandbox, tests your code, and provides screenshots, logs, and step-by-step validation of what broke.
• Noisy feedback clogs up PR cycle times and workflows. Lots of early feedback (common in shift-left testing) can be noisy and unactionable, especially if you're using shift-left testing tools. At Greptile, we focus on reducing noise while catching more bugs by indexing and learning your entire codebase for context-aware feedback. Greptile also learns from your team: the comments you leave, what fixes you implemented, and how you take action. This way, it provides better feedback sooner in the future.

How to implement shift left testing: Best practices

These core shift left testing principles are key for implementing shift left testing (and making sure it works for you):

• Involve QA early. Not just earlier, early. Best case scenario is to bring them in during requirements gathering and user story phases, where they can start to spot ambiguities in scope, understand what testing will be needed, and sketch out a testing plan before you start writing code.
• Encourage devs to write tests for their own code. TDD and BDD can help developers own more of the testing and quality around their own code, ensuring that code gets tested early: while, or right after, developers are writing it.
• Adopt testing and code review tools that help you shift left. A number of code quality and review tools now can be implemented early in the SDLC. For example, linters like ESLint or Pylint review code as it's being written for bugs and errors. Code review tools like Greptile run at the PR phase to find and fix errors before a merge, without needing human reviewers to do all the review manually. These tools can help shift-left testing while also removing tedious review work from your team's plate.
• Automate quality gates and testing. Automating quality enforcement checks in the CI/CD pipeline is another key way to help test and enforce code quality sooner, without relying heavily on manual checking.

The future of shift left testing: agentic coding loops

Like all parts of the SDLC, shift-left testing is going to keep evolving. The future of shift-left testing lies in automated, or agentic, loops that allow agents to run, test, and iterate on code on their own, as they're writing it.

For engineering teams to take advantage of the speed and scale of agentic coding and testing, you need code review to not become a bottleneck. To do so, first: prioritize shift-left testing, then set up workflows where agents can do shift-left testing on their own.

That's, in part, what we're building at Greptile.

What engineering teams need now is agentic loops that can automate shift-left testing to scale trust and validation along with your code.

Agentic loops essentially run shift-left testing automatically. Instead of your human devs having to write, run, review, and fix every test manually, you have agents on the case who can do all of those steps independently.

For example: Greptile's "greplooping" skill is one way to solve this. Agents review the PR, find potential errors and bugs, and attempt to fix. The agent then iterates with Greptile, going back and forth until the PR hits a 5/5 score with no major errors. Agents work autonomously to find and fix bugs early in the development process, and shift-left testing happens agentically on AI-written code.

But it's not the only way:

• Podium uses Greptile to implement automated code review and quality assurance early in the process, now reviewing 8,400+ code changes a week, faster and more effectively.
• Coinbase scores every code change against a security risk framework that sets the reviewer requirements for it, running from a single AI reviewer at the low-risk end to multiple mandatory human reviewers at the high end. Not all code needs the same scrutiny, but every line needs some.
• AI-assisted validation, shifted left, can pull requirements and context in even before code is written. Chris Kasten, Intuit's chief architect and SVP engineering, told our researchers: "We're shifting left so much that the agents have all of our architecture rules, all of our security requirements fed into the context." In this case, every PR serves as its own validation checkpoint, catching bugs earlier and validating code sooner, ensuring that codebases stay simple enough to trust.

When you're implementing shift-left testing on your team, you can't just think about what worked in the past. You have to think also about how shift-left testing will work in the future.

Agentic looping and agentic shift-left testing move validation and code review earlier in the SDLC, while also using agents to manage and perform more of the process: eliminating tedious work from engineering and QA teams, performing more robust testing, and implementing more testing, sooner.

To see how agentic shift left testing can improve your code quality and PR cycle times, try Greptile today →