Introducing Qodo 3.0: the quality and governance layer for the software factory.
Engineering teams are building agentic software factories. Output is up, but code review hasn't kept up.
And a factory with no quality control is just a faster way to ship defects.
Qodo 3.0 governs your software factory from the first line an agent writes through review and into production.
Instead of individual PRs, group your code into work packages as connected changes across repos. Reviewed, ranked, and measured together, with a clear map of impact.
Headed to AWS re:Invent? Join Qodo, the AI code quality and governance platform, at House of Kube on Nov 30.
VIP entry, our VIP section, a signature cocktail, and a swag bag.
Request VIP access: qodo.ai/reinvent/#form
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Listen to The Agentic Review podcast: qodo.ai/podcasts/why-ai-shou…
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A shared-library change can pass local tests and still break a service in another repo.
Qodo's Software Map shows dependencies across repos, helping reviewers identify affected services and involve their owners before merging.
Explore ten ways to use the Software Map: qodo.ai/blog/10-ways-qodos-s…
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Adding AI leaves existing development problems for teams to solve.
Scott Hanselman (@shanselman) questions blind optimization for more PRs when the workflow needs repair. Listen to The Agentic Review podcast with @nnennahacks and @itamar_mar.
Watch Scott Hanselman on The Agentic Review podcast:
qodo.ai/podcasts/why-develop…
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At Packsize, AI coding tools made pull requests larger and more frequent.
The team now uses Qodo for the first rounds of review on every PR, checking shared-package compatibility and repository rules before human reviewers take over.
Read the Packsize case study: qodo.ai/blog/no-code-goes-to…
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Where does the bottleneck move when code generation speeds up?
Paul Duvall (@PaulDuvall) discusses growing PR queues and how AI amplifies a team's existing practices. Listen to The Agentic Review podcast with @nnennahacks and @itamar_mar.
Watch Paul Duvall on The Agentic Review podcast:
qodo.ai/podcasts/beyond-the-…
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Fast AI adoption creates security decisions teams still have to own.
Gil Elbaz (@gil_elbaz_) of @Onyx_Security discusses the risk of less structured adoption with @nnennahacks and @itamar_mar on The Agentic Review podcast.
Watch Gil Elbaz on The Agentic Review podcast:
qodo.ai/podcasts/why-ai-cont…
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Generated code still needs decisions about architecture, latency, and scale.
Nirmal Jingar explains why engineering fundamentals matter when using AI tools. Listen to The Agentic Review podcast with @nnennahacks and @itamar_mar.
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Watch Nirmal Jingar on The Agentic Review podcast:
qodo.ai/podcasts/determinist…
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Files like AGENTS md are great for guiding agents, but your workflow needs to verify output quality.
@nnennahacks explains how to connect instructions, executable checks, review, human approval gates, and keep evidence tied to the code being shipped.
Read the guide below.

ALT Diagram titled One expectation, five responsibility layers. The expectation to cover behavior changes with regression tests connects to agent guidance, executable checks, independent review, lifecycle systems, and human authority. Each layer answers a different question; evidence moves from test execution through review and revision checks to a human decision.
Read the guide to steering AI coding agents:
qodo.ai/blog/how-do-you-effi…
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Shipping software takes planning, tests, usable recovery paths, and accurate documentation.
@nnennahacks shares seven agent skills that bring that work into the development workflow, with a real ThreadLoop example.
Choose the skill for the step your agent keeps skipping. Full guide below:
When teams use several coding agents, review needs consistent standards and enough context to spot affected callers.
Our Codex and Claude Code guide compares review workflows, rule files, and the limits of reviewing one repository at a time.
Read the blog here: qodo.ai/blog/codex-vs-claude…
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Manual bug bashes limit how many user journeys a team can explore.
@MomenticAI CEO @wuweiweiwu explains how parallel agents can test different paths and edge cases on The Agentic Review podcast.
Fantastic read:
🏭 AI didn't invent the software factory. We've had them since the 1960s.
LLMs change what we automate, not what makes a factory valuable.
Automating broken engineering just produces broken software faster.
Build the factory that makes YOUR business different.
davidparry.com/blog/2026/10/…
Your software factory needs an independent verifier because the agent that wrote the code brings its assumptions into the tests.
@wuweiweiwu, CEO of @MomenticAI, joins The Agentic Review to discuss what it takes to trust what your factory ships.
Full episode below.
Watch “Can You Trust What Your Software Factory Ships?” with Wei-Wei Wu, @nnennahacks and @itamar_mar:
youtu.be/niH78HK0dUk
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In the example, a bulk update misses the account-level authorization check required in a linked Confluence spec. Qodo flags the gap in the PR.
Spec sources: Asana, Confluence, Notion, ServiceNow, JSM Assets.
Read the walkthrough: qodo.ai/blog/how-qodo-uses-l…
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AI adoption looks different across an engineering team.
@anacondainc's Emilie Schario joins @nnennahacks and @itamar_mar on The Agentic Review podcast to discuss how workflows, tooling, and support need to match that range.
Every review comment asks for a developer’s attention.
Our AI Code Review Benchmark is joining @FireworksAI_HQ’s Specialized Intelligence Index to help teams compare what models catch, what they miss, and how often they raise false alarms.
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