AI-Driven Development Lifecycle
AI DLC (AI-Driven Development Lifecycle) is an AWS-originated methodology for applying AI across the whole software lifecycle, not just to writing code. You already have agents writing code. Harness extends AI across everything after. Build, test, secure, deliver, and optimize on one governed platform. Developers and AI write code. Harness AI does the rest.
Sources: United Airlines · Citi · Sensormatic · Tyler Technologies
AI writes more code than ever, but testing, securing, delivering, and operating it is still mostly manual. That's where delivery stalls, and where an AI DLC is needed.
More code, same bottleneck
Agents write code faster than teams can review, test, secure, and ship it. The work just piles up after the commit.
The lifecycle is fragmented
Coding agents stop at the pull request. Everything after lives in disconnected tools with no shared context to reason over.
Autonomy without guardrails
Letting agents act across delivery without policy, approvals, and audit is a risk most enterprises can’t take.
Keep writing code with the agents you already use. Harness AI takes it from there, building, testing, securing, delivering, and operating on one governed platform.
You bring
Harness AI does the rest
One platform. Every phase from code through production shares context, policy, and AI ensuring nothing stalls in a handoff between tools.
Agents do the work. Agents mesh with deterministic automation to drive feedback and deliver at a pace no human team could match.
Full system context. The Knowledge Graph links pipelines, policies, incidents, and services so agents decide with complete context.
Governed by default. Policy, approvals, and audit are built into every step, not bolted on.
Coding agent integrations: Bring Cursor, Claude Code, or Copilot. Harness picks up delivery intelligence over MCP so agents work inside your pipelines.
Rapid feedback: CI Test Intelligence runs only what changed. Combined with aggressive caching builds and tests return results in minutes.
Build once, trust everywhere: Every artifact is signed and provenance-tracked with Supply Chain Security, ready to promote through the rest of the lifecycle.
Intent-based Testing: AI Test Automation writes and self-heals functional tests, so coverage keeps up with the code your agents produce.
Automate Reslience: Turn real production incidents into stress and chaos tests with Reslience Testing, proving your system holds up under failure.
Test Your Agents: AI Evals score and regression-test agentic and LLM-powered features so quality is measured, not assumed.
Scan with reasoning: AI SAST uses deterministic code scanning and reasons over how your code behaves to find real vulnerabilities with fewer false positives.
Toolchain protection: Supply Chain Security tracks artifacts and helps you secure the toolchain that builds and delivers them.
Runtime protection: Detect and virtually patch attacks in real time with WAAP, shielding vulnerabilities the moment they are found.
AI deployment verification: Continuous Delivery watches every rollout and auto-rolls back the moment observability and logging metrics regress.
Experiment confidently: Decouple deploy from feature and agent release with flags, so you ship dark, test in production, and roll out to users on your terms.
Progressive delivery: Canary and blue-green strategies with built-in approvals and audit make frequent releases of apps and agents safe by default.
Understand AI impact: Measure team and delivery performance with AI DLC Insights so you can see whether more AI is actually making you faster.
Simplify self-service: Give developers and agents a single source of context: services, prompts, and golden paths in one place.
Manage cost: Cloud & AI Cost Management surfaces and cuts waste automatically, so faster delivery does not mean a bigger bill.
Try Harness free. No credit card. Use AI to quickly and safely build, test, secure, deliver, and operate.