Cloud costs
June 21, 2023
min read

Introducing Harness AIDA™ - AI Development Assistant for AI Infused Software Delivery


Watch our LinkedIn Live Event or Replay of Announcing Harness AIDATM

Harness is proud to announce AIDA, AI Development Assistant. AI infused software delivery that doesn't merely embrace AI but weaves it into the fabric of every stage of the software delivery lifecycle. Harness aims to automate routine tasks, improve accuracy, and accelerate software delivery timelines, marking a significant leap forward in its mission to provide the industry's most innovative and comprehensive modern software delivery platform.

Envision supercharging your coding with autocomplete, gaining deep insight with code explanations, automatically creating test cases, and having an AI sidekick for swift debugging and code issue remediation. That's the kind of productivity boost Harness is bringing to developers.

Imagine the software delivery process being simplified as if it's on auto-pilot: AI-driven generation of CI/CD pipelines, automated static code analysis, succinct PR summaries, enriched code reviews, and feature flags instrumented automatically. Plus, an AI-assisted onboarding and a troubleshooting guide for build and deployment issues. This is how Harness is making software delivery seamless and intuitive.

But it's not just about speed and simplicity. Harness also strengthens governance and security. Picture an AI tool that automatically explains and fixes vulnerabilities, auto-generates Open Policy Agent (OPA) policies and templates, and automatically crafts cloud asset policies, ensuring you're always in control and your environments remain secure.

Harness is infusing AI into the entire software delivery lifecycle, empowering engineers and engineering leaders with tools that boost productivity, streamline software delivery, and enhance governance, leading to an exciting and game-changing future for DevOps.

Transforming Software Delivery

Harness is announcing the following three capabilities to start with as part of its AI infused software delivery platform, AIDA.

Build and Deployment Troubleshooting

Harness AIDA has a lot of potential in Continuous Integration (CI) builds and Continuous Delivery (CD) deployments, particularly in the analysis and resolution of build errors. Upon a build failure, the AI can analyze log files, correlate the error messages with known issues, and suggest possible fixes. This allows developers to rectify the problem quickly, increasing productivity and reducing downtime.

Harness AIDA for Build and Deployment Troubleshooting

Auto-Generate Cloud Asset Policies Using Natural Language

Harness Cloud Asset Governance (CAG) is innovating Cloud Cost Management (CCM) through a Governance-as-Code approach, featuring real-time enforcement and auto-remediation backed by YAML-based policies. Generative AI facilitates policy creation using natural language queries and helps users understand pre-existing policies. This advanced approach not only accelerates time to value, resulting in hard dollar savings but also democratizes policy expertise, enabling anyone to become a policy expert and enhancing the effectiveness of cloud governance.

Harness AIDA for Auto-Generate Cloud Asset Policies Using Natural Language

Explain and Fix for Security Vulnerabilities

Harness AIDA has integrated the AI capabilities of Generative AI into Security Test Orchestration (STO) to address detected vulnerabilities such as Common Vulnerabilities and Exposures (CVEs) and Common Weakness Enumerations (CWEs). Harness AIDA generates remediation suggestions to guide users through resolving these issues. This new feature allows users to easily adjust or reset the remediation process, transforming how security issues are managed within the system. This innovation not only streamlines the vulnerability remediation process but also empowers users to take control, thereby enhancing the security and efficiency of the software delivery process.

Harness AIDA for Explain and Fix Security Vulnerabilities

Harness is infusing AI into DevOps, empowering users with tools that boost productivity, streamline software delivery, and enhance governance, ushering in the era of DevTools 2.0.

A Comprehensive AI Development Assistant

Most AI developer tools primarily focus on code generation and developer productivity. While this is important, it is necessary to understand the role AI will play in the overall software delivery lifecycle. 

Since 2018, Harness has leveraged AI to improve software delivery. Test Intelligence, Deployment Verification, and Change Impact Analysis have been used by our customers for years to reduce developer toil and improve software delivery that led to the vision of Harness AIDA. A full range of capabilities will be rolled out this year across each SDLC phase.

AI infused software delivery lifecycle


  • Onboard Assist: Help guide new and existing users through workflows to achieve the outcome desired.
  • Autocomplete: Intelligently anticipates developers' coding needs, offering real-time suggestions to speed up coding tasks.
  • Code Explainer: By automatically explaining complex code segments, Harness AIDA fosters shared understanding and knowledge transfer within development teams by automatically explaining complex code segments by automatically explaining complex code segments.
  • Debug/Remediate Code Issues: Automates the debugging process, proposing solutions for identified problems and even rectifying code issues automatically.
  • Code Reviews: Automate aspects of the code review process, ensuring consistency and saving developers valuable time.
  • Summarize PRs: Leveraging AI, generate concise summaries of pull requests, speeding up code review and team collaboration.

Build & Test:

  • Build/Deployment Troubleshooting: Harness employs AI to identify and address issues during the build and deployment process, enhancing productivity and reducing downtime.
  • Code Analysis: Identifies problematic code snippets before they cause issues, promoting a proactive approach to code quality.
  • Generate Test Cases: AI creates test scenarios to validate code functionality, improving test coverage.
  • Generate CI Pipelines: By auto-generating CI pipelines, Harness AIDA allows teams to ship faster, with fewer errors.


  • Explain & Fix Vulnerabilities: Harness AI identifies security vulnerabilities, explains them, and suggests remediation.
  • Automated Remediations: Harness AIDA can be configured to automate the remediation of vulnerabilities based on specific user defined workflows reducing the time spent on fixes. 


  • Generate CD Pipelines: By auto-generating CD pipelines, Harness AIDA allows teams to ship faster, with fewer errors.
  • Auto Instrument Feature Flags:  AI managed feature flags, reducing the risk of human error and increasing operational efficiency.

Ensure Reliability:

  • Recommend Chaos Experiments: Harness AIDA suggests chaos engineering experiments based on system constraints to test and improve resilience.
  • Auto RCA: Performs root cause analysis during system failures, improving incident response.


  • Auto-Generate Cloud Asset Policies: Harness uses AI to develop cloud asset policies, ensuring proper management and secure utilization of cloud resources
  • Generate OPA Policies, Dashboards, and Templates: By creating coding templates, OPA policies, and reports, Harness AI promotes coding standardization and streamlines the development process.
  • Generate SDLC Insights: Extracts valuable insights from the software delivery lifecycle, leading to improved process management.
  • Detects Cost Changes: AI monitors cloud expenditure changes, providing real-time cost oversight.

Barriers to AI Adoption in Software Delivery

As the generative AI landscape evolves, organizations are eager yet cautious about leveraging large language models (LLMs). The reluctance stems from notable concerns surrounding data privacy and security, issues with weaving AI tools into existing software delivery toolchains, and the classic 'build vs.. buy' considerations. 

  • Data Privacy and Security: AI tools need access to codebases, raising privacy and security concerns. The need for more transparency in AI training, the potential for external data sharing, and insufficient understanding of AI operations pose significant barriers to adoption. Overcoming these requires robust data governance and clear communication about AI functionalities.
  • Systems aren't integrated into Software Delivery Toolchain: AI tools must seamlessly integrate with CI/CD pipelines, build/test automation systems, artifact repos, and issue tracking software. This requires a cohesive experience trained on data sets that span language formats, security events, monitoring metrics, etc while providing API support, standardized data formats, and plugin frameworks. 
  • Build vs. Buy:  Vendor lock-in, unpredictable costs, performance latency, and regulatory compliance may cause enterprises to build some of the capabilities. While this may provide more control, it necessitates higher upfront costs, infrastructure management, and a deeper understanding of model training and fine-tuning to enable integration of workflows across a software delivery lifecycle. 

Harness’ Proven History of Leveraging AI/ML to Address the Barriers in Software Delivery

Harness has successfully infused AI into the software delivery lifecycle while ensuring users have the required privacy, security controls, and governance guardrails. 

Company CEO and founder Jyoti Bansal says AIDA is an extension of a lot of the work the startup has been doing over the years. “When we look at generative AI we look at how Harness has such a proven history of bringing AI to DevOps, CI/CD and deployment, verification and all the different things we have been doing,” Bansal told TechCrunch.

Jyoti Bansal reported to SiliconAngle that Harness added that it has also taken steps to ease concerns around data privacy, security and copyright infringement. The company explained that the AI Development Assistant’s stack, including its custom large language model, training data and vector database, are designed in such a way that all of the source code used in training has permissive licenses. It said this means its AI can be used without worrying that proprietary or copyleft code is used for training the Harness AI stack.

As reported in, “Harness has invested in machine learning algorithms to automate a range of DevOps tasks. Generative AI, in combination with machine learning, will transform DevOps workflows in ways that will ultimately improve both the rate at which applications can be built and their overall quality.”

Harness AIDA builds upon these capabilities by seamlessly integrating AI into build and deployment pipelines, enhancing software security, code integrity, cost efficiency, and reliability monitoring. Harness AIDA is a privacy first and enterprise ready solution for your enterprise.

Embracing the Future of Software Delivery with Harness AIDA

Harness AIDA is set to revolutionize software delivery by infusing AI into the SDLC, ushering in the era of DevTools 2.0. Harness AIDA empowers users with tools that boost productivity, streamline software delivery, and enhance governance, transforming the way we view and execute software delivery.

Harness AIDA is more than just a tool; it is the future of software delivery. Join us on this journey and experience the power of AI infused software delivery.

Learn more about Harness AIDA, or request a demo to get started.

Check out our Harness youtube channel to see the product in action!
AIDA for Software Delivery Lifecycle:
AIDA for Build/Deployment Troubleshooting:
AIDA to Explain and Fix Vulnerabilities:
AIDA to Auto-Generate Cloud Asset Policies:

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