Business Development Representative

From routing to execution planning with Cortex Planner. AI-assisted software delivery is moving beyond individual code suggestions. The next frontier is coordinated execution: understanding the work, organizing the right expertise, respecting dependencies, and validating outcomes before change reaches production. With the release of Cortex Planner, Cortex adds its ninth specialized model. Cortex Planner 1.8 brings a new layer of intelligence to the Cortex experience. It transforms a development request into a clear, governed execution plan - helping teams move from "what needs to happen" to "how the work should be coordinated" with greater confidence, visibility, and control. From routing work to planning outcomes. Cortex Router established a smarter way to direct work across Cortex's specialized AI capabilities. It evaluates a request and helps identify the right path and the right expertise for the task. Cortex Planner extends that vision. Where routing determines where work should go, planning defines what must happen next. Cortex Planner interprets the objective, available context, and permitted actions to create an organized plan for analysis, implementation, testing, security review, integration, and validation. This is an important step in the evolution of AI-assisted development. Complex engineering work is rarely a single action. A request to add a feature, resolve a defect, investigate a security concern, or improve an existing service may involve several distinct activities - some independent, some sequential, and some requiring careful review before they can move forward. Cortex Planner helps make that work visible, intentional, and easier to govern. A more deliberate Cortex experience. Cortex Planner advances Cortex from intelligent task direction toward intelligent orchestration. Rather than treating a broad request as one opaque operation, Cortex can represent the work as a structured plan with defined stages, specialist responsibilities, and expected outcomes. The planner can distinguish when more discovery is needed from when there is sufficient context to proceed. It can identify tasks that can move forward independently, bring their results together at the appropriate point, and include validation as part of the work from the beginning. For example, a multi-area product change may require separate implementation, testing, documentation, integration, and validation activities. Cortex Planner can organize those streams of work into a coordinated progression, helping ensure that important branches do not get overlooked and that the final result is assessed against the original objective. For security-sensitive work, the planner can help structure remediation alongside regression testing, review, integration, and validation. The goal is not simply to produce a proposed fix, but to support a more complete and accountable path to a reliable outcome. This creates a more deliberate development experience: * Clearer decomposition of complex engineering work * Better coordination across specialized AI capabilities * More intentional sequencing of changes, reviews, tests, and validation * Greater visibility into what must occur before work is considered complete * A stronger foundation for governed AI-assisted delivery Planning with boundaries built in. Powerful AI workflows need more than speed. They need boundaries. Cortex Planner is designed to operate within trusted context and defined permissions. It does not treat uncertainty as an invitation to take unchecked action. When additional information is needed, it can organize discovery before proposing execution. When changes are being planned, it keeps the work aligned with the available project context. When activities could overlap or conflict, it can organize a safer sequence. This is especially important as organizations look to apply AI across larger and more consequential software initiatives. Teams need to know not only that AI can generate output, but that it can participate in a process designed around accountability, scope, and validation. Cortex Planner helps turn those requirements into a natural part of the development workflow. Designed for specialist collaboration. Cortex is built on the belief that specialized intelligence produces better outcomes than a one-size-fits-all model. Different engineering activities call for different strengths. Analysis requires investigation and context. Implementation requires focused execution. Testing requires a separate perspective on behavior and quality. Security review requires attention to risk. Integration and validation ensure that individual changes become a coherent, dependable outcome. Cortex Planner acts as a coordination layer between intent and execution. It helps bring the appropriate specialist capabilities into the appropriate stage of the work, while preserving a clear view of dependencies, acceptance criteria, and completion. That matters because modern engineering tasks rarely end with a code change. A durable outcome may require understanding an existing implementation, updating multiple areas of a project, adding or improving tests, reviewing risk, integrating the work, and proving that it meets the original objective. Cortex Planner makes that full lifecycle more visible - and helps teams keep it connected from the first request through final validation. Making validation part of the plan. One of the most important characteristics of effective software delivery is that validation is not a final checkbox. It is part of how work is designed. Cortex Planner reflects that principle by incorporating acceptance criteria and validation into the execution plan itself. The intended result is not merely "a change was made." It is that the requested behavior has been addressed, important constraints have been preserved, and the outcome has been evaluated through the right checks. For teams, this creates a clearer bridge between a request and a verifiable result. It also helps support more consistent collaboration between developers, security teams, engineering leaders, and the AI capabilities supporting their work. By making validation visible earlier, teams can spend less time reconstructing intent at the end of a task and more time building confidence throughout it. Human control where it matters. Automation should increase confidence, not reduce oversight. Cortex Planner recognizes that some actions require explicit human involvement. When work involves consequential external actions, the plan can preserve a confirmation point rather than assuming authority to proceed. This enables organizations to expand AI-assisted workflows while keeping people in control of decisions that matter. The result is a practical model for enterprise AI: intelligent enough to organize complex work, structured enough to respect boundaries, and transparent enough to support responsible adoption. The next chapter for the Cortex AI Ensemble. Cortex Planner is the ninth model in the Cortex AI Ensemble and a meaningful expansion of what Cortex can help engineering organizations coordinate. It builds on the progress of Cortex Router by adding a planning layer that connects intent, specialist collaboration, governed execution, and validation. It helps shift the conversation from isolated AI interactions to coordinated AI-assisted delivery - where each contribution is part of a larger, understandable path toward an outcome. The future of software engineering will not be defined only by how quickly AI can generate code. It will be defined by how effectively AI can help teams organize complex work, preserve quality, manage risk, and deliver outcomes they can trust. Cortex Planner brings Cortex closer to that future: a coordinated AI experience where every request has a clearer path forward, every specialist contribution has a purpose, and every outcome is designed to be understood, validated, and trusted.

Building a more trustworthy Cortex for enterprise software delivery. Enterprise teams do not need AI that merely writes code. They need AI that fits into real software-delivery practices: clear ownership, dependable validation, controlled access, useful continuity, and evidence that helps people decide what should happen next. This Cortex update advances that goal. It strengthens the end-to-end coding-agent experience - from request through code change, validation, review, recovery, and learning - while keeping developers and organizations in control. From code generation to accountable delivery. Cortex is evolving from a coding assistant into a more complete development partner. It can help teams understand requests, prepare code changes, run appropriate checks, summarize outcomes, and present the resulting work for review. The experience now makes the status of a coding task easier to understand at a glance. Developers can see the files involved, the scope of a change, validation status, and whether a change is still awaiting review. This is important in enterprise environments, where a natural-language statement that work is "done" is not enough. Teams need a concise, reviewable record of what the agent actually produced and what evidence supports it. Clear separation of responsibilities. Reliable AI development requires different capabilities to have clearly defined roles. Cortex now more deliberately separates the work of producing code, carrying out bounded development actions, validating results, and providing advisory review. This helps reduce confusion between an agent proposing a change and a system confirming that the change is ready for use. The benefit is a more predictable workflow. Coding assistance can remain focused on solving the task; validation can provide concrete execution evidence; and review can supply an independent perspective. Each signal is visible to the developer rather than being hidden behind an opaque automated decision. Human judgment remains the control point. Cortex now includes an advisory Verifier capability for eligible users. After a proposed change has been prepared and validation evidence is available, the verifier can provide an additional assessment: ready to proceed, needs revision, reject, or requires further review. This is designed as an advisory control, not an autonomous authority. Developers and teams retain the ability to inspect the diff, review supporting evidence, rerun validation, accept or reject a proposal, request a different approach, or escalate an important decision. Cortex does not silently merge code, authorize a patch, or substitute an automated verdict for human responsibility. That model gives organizations a practical path to use AI more broadly without weakening code-review standards or governance expectations. More honest validation and risk signals. A passing validation command is valuable evidence, but it is not a complete statement of quality. A patch can pass a local test while still needing review for coverage, maintainability, security, compatibility, or business correctness. Cortex now makes this distinction clearer. It separates validation outcomes from review recommendations and highlights when certain local checks were unavailable. Teams can see both what was verified and what remains uncertain. This creates a more useful decision-making experience than a simple pass/fail label. It helps developers move quickly when evidence is strong while preserving appropriate caution when the evidence is incomplete. Faster, more resilient AI workflows. AI-assisted development must be efficient as well as capable. Cortex has strengthened routing and recovery behavior so coding tasks are handled by the most appropriate capability and do not consume excessive time or resources through unnecessary retries or unsuitable fallback paths. The result is a more dependable experience for common coding requests and clearer behavior when a supporting service is unavailable. Instead of leaving a developer waiting indefinitely or presenting confusing results, Cortex keeps recovery bounded and communicates the practical outcome. When an optional advisory review service is unavailable, the code change remains available for user review. Internal provider details are not exposed in the developer experience, and no automated approval is implied. Reliable continuity across the development experience. Development work often spans restarts, refreshes, reconnects, devices, and long-running sessions. Cortex has improved session continuity so active work is less likely to be lost, duplicated, or displayed inconsistently when a client reconnects. Conversation restoration is now more reliable across desktop, browser, and mobile experiences. The improvements focus on preserving meaningful user and agent activity, maintaining clearer timing and review context, and preventing incomplete or operational-only records from appearing as customer-facing conversation. Cortex has also expanded support for longer active conversations. This better reflects real enterprise development, where an investigation, implementation, testing cycle, and review may extend well beyond a short chat exchange. Consistent review across Cortex surfaces. Whether a developer is working from an editor, browser, or mobile device, the underlying expectation is the same: proposed changes should be understandable and reviewable. Cortex is aligning the change-review experience across supported surfaces so users receive clearer status signals, compact validation indicators, accessible review actions, and consistent handling of pending changes. This reduces friction when work moves between environments and helps teams maintain a common review standard. Enterprise access that follows the user. Enterprise AI must respect the organization's existing boundaries. Cortex is strengthening the connection between identity, access, and AI capability so that developers receive the assistance appropriate to their role, plan, and approved work environment. This gives organizations greater confidence that advanced coding assistance, connected enterprise systems, and higher-impact workflows are available deliberately, not simply because a client requests them. It also creates a cleaner path for security, IT, and engineering leaders to expand adoption in line with internal policy. Controlled access for advanced capabilities. Advanced AI review capabilities need to be introduced with clear access controls. Cortex now supports subscription-based availability for advisory patch review, allowing organizations to make these capabilities available according to their commercial plan and governance requirements. This enables a measured adoption path. Organizations can begin with standard coding assistance, enable enhanced review for the right teams, and expand usage as internal practices and confidence mature. A connected development experience. Modern development does not happen in one place. Engineers move between their IDE, browser, and mobile device as they investigate issues, review work, coordinate with colleagues, and return to active tasks. Cortex is making that experience more continuous. Developers can carry meaningful work context across supported surfaces, return to previous discussions more easily, and maintain a more consistent experience regardless of where they choose to work. The goal is to reduce the friction of switching environments without weakening governance or creating disconnected AI experiences. A foundation for continuous quality improvement. Cortex is also establishing a stronger evaluation foundation for coding-agent quality. This enables the platform to assess workflow reliability over time: how coding tasks recover, how often validation is performed, how review signals align with outcomes, and where user experience can improve. These capabilities support future improvements to coding agents, validation workflows, and verifier models while keeping data governance central. Organizations can control whether eligible feedback contributes to learning and evaluation, preserving transparency and choice. What this means for enterprises. Cortex is becoming a more accountable AI development environment. It helps teams accelerate coding work while retaining the safeguards that matter in production software delivery: * Clear evidence of what changed and what was checked * Better separation between generation, execution, validation, and review * Advisory AI review with human-controlled decisions * More honest visibility into validation status and remaining risk * Faster, bounded recovery when supporting services fail * Reliable continuity across editor, browser, and mobile workflows * Subscription-aware access to advanced capabilities * A scalable foundation for measuring and improving AI quality The objective is not automation for its own sake. It is to help engineering organizations deliver software faster with stronger visibility, clearer accountability, and greater confidence in every AI-assisted change.