November 2, 2026
StartupQodo builds context into AI code review with Codex
Qodo brings organizational context and codebase standards into Codex, helping developers catch P0 issues across repositories.
Qodoβ (opens in a new window) builds AI tools for code review and software quality, giving coding agents the organizational knowledge they need to understand the code they change. Co-founder and CEO Itamar Friedman calls it βthe coding agentβs best friend.β
Qodo uses OpenAI models including GPTβ6 Astra to gather engineering knowledge, review code, and monitor software quality. Its Codex plugin brings that context and review into developersβ coding sessions.
βWe love OpenAI models. We want the frontier, the best reasoning models, but also those that are really fast.β
Finding P0 bugs across repositories with Codex
Itamar describes customer environments that can span 10,000 or more repositories, where a local code change can break a downstream service, even if it looks correct on its own. Qodo built a plugin in the Codex marketplace to address this.
βCodex is really good at taking a local task and completing it in an efficient way,β Itamar says. Qodoβs plugin gives Codex access to codebase knowledge, organizational rules, and independent review through Qodoβs Agentic Toolbox.
With context, Codex can account for dependencies across repositories, including those hosted by different Git providers or services connected through Kafka. βQodo will make that connection and will help Codex look at the software as a whole and not miss those P0 bugs,β Itamar says.
Automating review while keeping human judgment
Before Codex starts writing code, it can use Qodoβs plugin to retrieve the relevant codebase rules and pull request history and patterns. After Codex makes the changes, Qodo reviews them and returns its findings directly to Codex in the same session, before the developer opens a pull request.
Nnenna Ndukwe, Qodoβs AI Developer Relations Lead, sees developers using this workflow to build features and tackle technical debt with GPTβ6 models in Codex. They are automating the handoff between Codexβs coding work and Qodoβs independent review. βThatβs what Iβve been seeing developers do, which is really exciting because GPTβ6 is extremely capable,β Nnenna says.
Itamar describes coding and review agents as βyin and yangβ: one creates code, the other challenges it. Each role needs its own setup and context and may involve multiple agents. His vision is for agents to discuss findings and βsurface only what they donβt acceptβ for human review. Developers would become planners and reviewers, able to inspect unresolved issues alongside the agentsβ discussion, context, and prior developer decisions.
βThatβs how you create trust,β Itamar says. βI think it makes the whole process overall more efficient,β Nnenna adds. βWe get to leverage the best parts of our expertise.β
Putting Codex to work every day
Internally at Qodo, Nnenna has been using GPTβ6 Astraβs Extra High and Ultra effort settings in her own automated development workflows as well as knowledge work.
βWhat does Codex not do? I love everything that Codex does. I love the idea of combining AI and automation.β
Nnenna schedules Codex to report on what she accomplished during the week and where she could focus or improve next. She also uses it to research conversations about agentic engineering on social platforms and suggest ideas for developer content. When it comes to her own code changes, she schedules Codex to analyze her work and suggest agent skills to create or refine.
Choosing which coding rules apply with the Decisions API
Itamar sees an opportunity to use OpenAIβs recently launched Decisions API to choose which rules and agent skills apply at each stage of development, rather than rely on language models for every decision.
He cites an example where the Decisions API could select which of 200 rules need checking before a language model reasons through the relevant ones, helping to make selection faster and cheaper while improving the quality of the review. βThe Decisions API is an immense opportunity for us to bring more trust to the process,β Itamar says.
Building software factories customers can own
Qodoβs approach combines βthe best aspects of artificial intelligence and the best aspects of traditional software engineering and scripting,β Nnenna says. Company knowledge guides coding agents, independent review checks their work, and human expertise resolves the questions that remain.
This creates the foundation of what Itamar describes as a software factory: a system customers could assemble and own, bringing coding and review agents together with an understanding of how software changes in production.
With OpenAI, Qodo is building a future where coding agents put more of a companyβs experience to work and developers can focus their judgment where it matters most.


