{"id":155297,"date":"2026-06-23T14:14:01","date_gmt":"2026-06-23T22:14:01","guid":{"rendered":"https:\/\/xira.com\/p\/2026\/06\/23\/why-you-should-choose-legal-ops-tools-you-can-build-on-part-2\/"},"modified":"2026-06-23T14:14:01","modified_gmt":"2026-06-23T22:14:01","slug":"why-you-should-choose-legal-ops-tools-you-can-build-on-part-2","status":"publish","type":"post","link":"https:\/\/xira.com\/p\/2026\/06\/23\/why-you-should-choose-legal-ops-tools-you-can-build-on-part-2\/","title":{"rendered":"Why You Should Choose Legal Ops Tools You Can Build On (Part 2)"},"content":{"rendered":"<p><em><span>Ed. note:<\/span> Second in a series. <a href=\"https:\/\/abovethelaw.com\/2026\/06\/why-you-should-choose-legal-ops-tools-you-can-build-on-part-1\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Read the first installment here<\/a>.<\/em><\/p>\n<p>The previous article in this series proposed that Legal Operations leaders should evaluate legal technology not on the polish of its embedded AI features but on whether the underlying platform allows the department to build custom agents on top of it. That argument addressed the procurement question, but it does not address the operational one. Once the right tools are in place, what automated process tools are built on them, in what order, and where does that process reside?<\/p>\n<p>Industry data quantifies the gap. <a href=\"https:\/\/venturebeat.com\/orchestration\/enterprise-agentic-ai-requires-a-process-layer-most-companies-havent-built\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">The Celonis 2026 Process Optimization Report<\/a>, as covered in VentureBeat, finds that 85 percent of enterprises plan to deploy agentic capabilities within three years, while 76 percent acknowledge their current operations cannot yet support that ambition. Legal departments are not exceptions to that pattern. The distance between an agent-ready technology stack and a portfolio of agents that actually process work through the legal function is meaningful, and bridging that distance is the purpose of what enterprise AI commentary has begun calling the \u201cimplementation process layer.\u201d<\/p>\n<p><a href=\"https:\/\/www.bain.com\/insights\/the-three-layers-of-an-agentic-ai-platform\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Bain &amp; Company<\/a> has documented the same architectural pattern at the broader enterprise level, describing three converging layers that organize workflow orchestration, agent observability, and controlled data access. For Legal Operations, the implementation process layer is more specific. It comprises five components: workflow definition, system access and authority, encoded business rules, audit traceability, and design ownership. Together, these determine whether agents produce defensible Legal Operations work or merely competent demonstrations. None of the five can be delivered by a vendor in finished form, because each is the encoded expression of how a particular department defines a good process or outcome.<\/p>\n<p>Workflow definition is the first component because it governs everything that follows. The work is to define which decisions the agent owns, where the human approval gates sit, what triggers a handoff from agent to human, and what constitutes a completed task. This corresponds directly to existing operational decisions in any legal department: matter intake routing and matter database setup, invoice approval workflows, and escalation thresholds. <a href=\"https:\/\/architect.salesforce.com\/docs\/architect\/fundamentals\/guide\/agentic-enterprise-it-architecture\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Salesforce<\/a>\u2019s \u201cagent-first with human oversight\u201d design principle reinforces the discipline required. Agents must be capable of being monitored, paused, overridden, or escalated to a human at any step, and must proactively escalate when their confidence falls below a defined threshold. The objective is not to constrain the agent for its own sake, but to ensure that an agent operating outside its intended envelope stops and requests guidance rather than producing an incorrect or harmful output.<\/p>\n<p>The second component is system access and authority. The relevant questions are familiar to any operations leader who has designed signing-authority matrices or invoice-approval limits. Which systems and what records does the agent read from? Which records or fields are they permitted to modify? What dollar thresholds and commitment limits apply to its write actions? How are its actions compared against the governance structure that already constrains human team members? A read-only agent that surveys invoice patterns presents a fundamentally different risk profile than an agent empowered to adjust line items or approve invoices. The implementation process layer is where that distinction is encoded, and where the audit consequences of misconfiguration are managed in advance rather than after the fact.<\/p>\n<p>Encoded business rules are the third component of the implementation process. Most legal departments maintain their billing guidelines, rate schedules, fee structures, scope definitions, and engagement terms as documents that humans interpret and apply. The implementation work for this component involves converting those documents into machine-readable rules that the agent can quickly and easily execute, along with the measurement criteria for evaluating the agent\u2019s output. This is where prior investment in value-based pricing delivers a second dividend. A department with structured fee arrangements, clearly defined scopes, and articulated criteria for material deviations has the raw material an agent needs to apply those rules consistently. A department whose rate cards reside in static PDFs and whose fee arrangements vary firm to firm without a standardized template will need to complete foundational work before any agent can produce reliable output.<\/p>\n<p>The fourth component is audit traceability. The relevant standard is not whether the agent maintained a log file, but whether a billing auditor, a Legal Ops professional, or a finance partner can subsequently reconstruct what the agent did, why it did it, and what changed in the system as a result. Salesforce\u2019s \u201ctrust-throughout\u201d design principle frames the correct approach: validation against departmental policies and reconstructible audit trails for every agent decision and action must be embedded up front across the architecture, not added after deployment. What it does require is the discipline to design the audit trail before the agent operates, rather than construct it after the first incident.<\/p>\n<p>The fifth component is design ownership and maintenance. Someone within the Legal Operations function must own the workflow logic, maintain the encoded business rules as guidelines and rate cards evolve, and manage recoveries and recoding when the agent produces an incorrect outcome. This is the operational extension of the design ownership argument discussed in the prior article. Agent design is not a one-time configuration exercise. It is an ongoing function that the department either owns directly or, by default, relinquishes to the vendor.<\/p>\n<p>These components matter only if the department has a coherent sequence for building them out. The governing principle discussed in developer circles is to start where the right answer is verifiable and the wrong answer is recoverable. Verifiable workflows take precedence and judgment-intensive work follows later. In Legal Operations, the verifiable tier is fairly well-defined. For example, consider invoice review against billing guidelines, including line-item flagging, block billing detection, timekeeper rate compliance, and expense policy checks. This can be an appropriate starting point because the underlying rules are explicit, the data is structured, and the agent\u2019s output can be reviewed against a known standard before it reaches the firm. Rate compliance against approved schedules is another example if the schedules are encoded for agent readability. Fee structure adherence for VBP matters, including phase completion triggers, per-occurrence counts, and scope compliance, sits a level above, benefiting directly from existing scope and fee documentation. Deadline calculation, matter tracking, basic matter intake routing, and structured data extraction from MSOWs, engagement letters, and invoices are additional opportunities in sequence.<\/p>\n<p>The reason to sequence the work this way is not technical caution. These workflows produce two outcomes simultaneously: the operational result the agent was built to deliver, and the performance record that justifies extending the agent\u2019s authority responsibly over time. Judgment-intensive work, including litigation strategy, settlement valuation, panel selection scoring, and outside firm performance evaluation, has a legitimate place in the long-term roadmap, but later in the sequencing process.<\/p>\n<p>The organizing rule is straightforward: anything that encodes how the department defines a good outcome belongs in-house. The billing guidelines logic, the rate card structure, the fee structure templates, the VBP scope definitions, the matter intake decision tree, and the criteria by which the agent\u2019s output is evaluated constitute the department\u2019s intellectual property and should remain so. What can reasonably be partnered out is the work that surrounds that intellectual property: data pipeline plumbing, integration build, evaluation framework construction, security infrastructure, and repeatable component patterns drawn from other Legal Operations engagements. A productive partner delivers capacity and proven patterns under the department\u2019s direction, rather than a proprietary framework that absorbs workflow logic into a locked, vendor-owned offering.<\/p>\n<p>Vendors will come to understand that they need to sell the system-of-record platform itself. They can sell the underlying data model and process patterns that fit common Legal Operations workflows. What they cannot credibly sell is a working agent calibrated to a specific department\u2019s processes, workflows, and organizational structure. Does the vendor provide a platform that the legal department can direct, or does the vendor attempt to own the workflow logic itself?<\/p>\n<p>Legal technology platforms cycle on multi-year intervals. Vendor roadmaps shift when ownership changes, when category leaders lose ground, or when a model provider releases capabilities that displace an existing feature set. The client\u2019s implementation process layer provides another set of variables to these cycles. The workflow logic, the encoded business rules, and the decision rights governing what constitutes a good outcome are the Legal Operations function\u2019s lasting assets. They survive the next platform migration, the next vendor consolidation, and the next round of pricing changes. Legal operations has the opportunity to organize its own implementation process layer on its own terms and timeline. The alternative is to allow vendor roadmaps to determine the shape of the layer by default. Vendors supply the system of record. The Legal Operations function holds the design.<\/p>\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n<p><em>.<\/em><strong>Cited Sources<\/strong><\/p>\n<ul class=\"wp-block-list\">\n<li>Sheng, E., Zhu, R., O\u2019Rourke, B., Pedzinski, D., and Zhang, K. \u201cThe Three Layers of an Agentic AI Platform.\u201d Bain &amp; Company, April 2026. <a href=\"https:\/\/www.bain.com\/insights\/the-three-layers-of-an-agentic-ai-platform\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.bain.com\/insights\/the-three-layers-of-an-agentic-ai-platform\/<\/a><\/li>\n<li>Salesforce Architects. \u201cThe Agentic Enterprise: The IT Architecture for the AI-Powered Future.\u201d <a href=\"https:\/\/architect.salesforce.com\/docs\/architect\/fundamentals\/guide\/agentic-enterprise-it-architecture\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/architect.salesforce.com\/docs\/architect\/fundamentals\/guide\/agentic-enterprise-it-architecture<\/a><\/li>\n<li>\u201cEnterprise agentic AI requires a process layer most companies haven\u2019t built,\u201d VentureBeat, reporting on the Celonis 2026 Process Optimization Report. <a href=\"https:\/\/venturebeat.com\/orchestration\/enterprise-agentic-ai-requires-a-process-layer-most-companies-havent-built\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/venturebeat.com\/orchestration\/enterprise-agentic-ai-requires-a-process-layer-most-companies-havent-built\/<\/a><\/li>\n<\/ul>\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n<p><strong><em>Ken Callander is Managing Principal of Value Strategies LLC, a consulting practice that advises corporate legal departments on outside counsel pricing strategy. He previously served as Head of Legal Operations at Uber Technologies. He is a Certified Pricing Professional and holds a degree in Physics from Stanford University.<\/em><\/strong><\/p>\n<p>The post <a href=\"https:\/\/abovethelaw.com\/2026\/06\/why-you-should-choose-legal-ops-tools-you-can-build-on-part-1-2\/\" rel=\"nofollow noopener\" target=\"_blank\">Why You Should Choose Legal Ops Tools You Can Build On (Part 2)<\/a> appeared first on <a href=\"https:\/\/abovethelaw.com\/\" rel=\"nofollow noopener\" target=\"_blank\">Above the Law<\/a>.<\/p>\n<p><em><span>Ed. note:<\/span> Second in a series. <a href=\"https:\/\/abovethelaw.com\/2026\/06\/why-you-should-choose-legal-ops-tools-you-can-build-on-part-1\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Read the first installment here<\/a>.<\/em><\/p>\n<p>The previous article in this series proposed that Legal Operations leaders should evaluate legal technology not on the polish of its embedded AI features but on whether the underlying platform allows the department to build custom agents on top of it. That argument addressed the procurement question, but it does not address the operational one. Once the right tools are in place, what automated process tools are built on them, in what order, and where does that process reside?<\/p>\n<p>Industry data quantifies the gap. <a href=\"https:\/\/venturebeat.com\/orchestration\/enterprise-agentic-ai-requires-a-process-layer-most-companies-havent-built\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">The Celonis 2026 Process Optimization Report<\/a>, as covered in VentureBeat, finds that 85 percent of enterprises plan to deploy agentic capabilities within three years, while 76 percent acknowledge their current operations cannot yet support that ambition. Legal departments are not exceptions to that pattern. The distance between an agent-ready technology stack and a portfolio of agents that actually process work through the legal function is meaningful, and bridging that distance is the purpose of what enterprise AI commentary has begun calling the \u201cimplementation process layer.\u201d<\/p>\n<p><a href=\"https:\/\/www.bain.com\/insights\/the-three-layers-of-an-agentic-ai-platform\/\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Bain &amp; Company<\/a> has documented the same architectural pattern at the broader enterprise level, describing three converging layers that organize workflow orchestration, agent observability, and controlled data access. For Legal Operations, the implementation process layer is more specific. It comprises five components: workflow definition, system access and authority, encoded business rules, audit traceability, and design ownership. Together, these determine whether agents produce defensible Legal Operations work or merely competent demonstrations. None of the five can be delivered by a vendor in finished form, because each is the encoded expression of how a particular department defines a good process or outcome.<\/p>\n<p>Workflow definition is the first component because it governs everything that follows. The work is to define which decisions the agent owns, where the human approval gates sit, what triggers a handoff from agent to human, and what constitutes a completed task. This corresponds directly to existing operational decisions in any legal department: matter intake routing and matter database setup, invoice approval workflows, and escalation thresholds. <a href=\"https:\/\/architect.salesforce.com\/docs\/architect\/fundamentals\/guide\/agentic-enterprise-it-architecture\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Salesforce<\/a>\u2019s \u201cagent-first with human oversight\u201d design principle reinforces the discipline required. Agents must be capable of being monitored, paused, overridden, or escalated to a human at any step, and must proactively escalate when their confidence falls below a defined threshold. The objective is not to constrain the agent for its own sake, but to ensure that an agent operating outside its intended envelope stops and requests guidance rather than producing an incorrect or harmful output.<\/p>\n<p>The second component is system access and authority. The relevant questions are familiar to any operations leader who has designed signing-authority matrices or invoice-approval limits. Which systems and what records does the agent read from? Which records or fields are they permitted to modify? What dollar thresholds and commitment limits apply to its write actions? How are its actions compared against the governance structure that already constrains human team members? A read-only agent that surveys invoice patterns presents a fundamentally different risk profile than an agent empowered to adjust line items or approve invoices. The implementation process layer is where that distinction is encoded, and where the audit consequences of misconfiguration are managed in advance rather than after the fact.<\/p>\n<p>Encoded business rules are the third component of the implementation process. Most legal departments maintain their billing guidelines, rate schedules, fee structures, scope definitions, and engagement terms as documents that humans interpret and apply. The implementation work for this component involves converting those documents into machine-readable rules that the agent can quickly and easily execute, along with the measurement criteria for evaluating the agent\u2019s output. This is where prior investment in value-based pricing delivers a second dividend. A department with structured fee arrangements, clearly defined scopes, and articulated criteria for material deviations has the raw material an agent needs to apply those rules consistently. A department whose rate cards reside in static PDFs and whose fee arrangements vary firm to firm without a standardized template will need to complete foundational work before any agent can produce reliable output.<\/p>\n<p>The fourth component is audit traceability. The relevant standard is not whether the agent maintained a log file, but whether a billing auditor, a Legal Ops professional, or a finance partner can subsequently reconstruct what the agent did, why it did it, and what changed in the system as a result. Salesforce\u2019s \u201ctrust-throughout\u201d design principle frames the correct approach: validation against departmental policies and reconstructible audit trails for every agent decision and action must be embedded up front across the architecture, not added after deployment. What it does require is the discipline to design the audit trail before the agent operates, rather than construct it after the first incident.<\/p>\n<p>The fifth component is design ownership and maintenance. Someone within the Legal Operations function must own the workflow logic, maintain the encoded business rules as guidelines and rate cards evolve, and manage recoveries and recoding when the agent produces an incorrect outcome. This is the operational extension of the design ownership argument discussed in the prior article. Agent design is not a one-time configuration exercise. It is an ongoing function that the department either owns directly or, by default, relinquishes to the vendor.<\/p>\n<p>These components matter only if the department has a coherent sequence for building them out. The governing principle discussed in developer circles is to start where the right answer is verifiable and the wrong answer is recoverable. Verifiable workflows take precedence and judgment-intensive work follows later. In Legal Operations, the verifiable tier is fairly well-defined. For example, consider invoice review against billing guidelines, including line-item flagging, block billing detection, timekeeper rate compliance, and expense policy checks. This can be an appropriate starting point because the underlying rules are explicit, the data is structured, and the agent\u2019s output can be reviewed against a known standard before it reaches the firm. Rate compliance against approved schedules is another example if the schedules are encoded for agent readability. Fee structure adherence for VBP matters, including phase completion triggers, per-occurrence counts, and scope compliance, sits a level above, benefiting directly from existing scope and fee documentation. Deadline calculation, matter tracking, basic matter intake routing, and structured data extraction from MSOWs, engagement letters, and invoices are additional opportunities in sequence.<\/p>\n<p>The reason to sequence the work this way is not technical caution. These workflows produce two outcomes simultaneously: the operational result the agent was built to deliver, and the performance record that justifies extending the agent\u2019s authority responsibly over time. Judgment-intensive work, including litigation strategy, settlement valuation, panel selection scoring, and outside firm performance evaluation, has a legitimate place in the long-term roadmap, but later in the sequencing process.<\/p>\n<p>The organizing rule is straightforward: anything that encodes how the department defines a good outcome belongs in-house. The billing guidelines logic, the rate card structure, the fee structure templates, the VBP scope definitions, the matter intake decision tree, and the criteria by which the agent\u2019s output is evaluated constitute the department\u2019s intellectual property and should remain so. What can reasonably be partnered out is the work that surrounds that intellectual property: data pipeline plumbing, integration build, evaluation framework construction, security infrastructure, and repeatable component patterns drawn from other Legal Operations engagements. A productive partner delivers capacity and proven patterns under the department\u2019s direction, rather than a proprietary framework that absorbs workflow logic into a locked, vendor-owned offering.<\/p>\n<p>Vendors will come to understand that they need to sell the system-of-record platform itself. They can sell the underlying data model and process patterns that fit common Legal Operations workflows. What they cannot credibly sell is a working agent calibrated to a specific department\u2019s processes, workflows, and organizational structure. Does the vendor provide a platform that the legal department can direct, or does the vendor attempt to own the workflow logic itself?<\/p>\n<p>Legal technology platforms cycle on multi-year intervals. Vendor roadmaps shift when ownership changes, when category leaders lose ground, or when a model provider releases capabilities that displace an existing feature set. The client\u2019s implementation process layer provides another set of variables to these cycles. The workflow logic, the encoded business rules, and the decision rights governing what constitutes a good outcome are the Legal Operations function\u2019s lasting assets. They survive the next platform migration, the next vendor consolidation, and the next round of pricing changes. Legal operations has the opportunity to organize its own implementation process layer on its own terms and timeline. The alternative is to allow vendor roadmaps to determine the shape of the layer by default. Vendors supply the system of record. The Legal Operations function holds the design.<\/p>\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n<p><em>.<\/em><strong>Cited Sources<\/strong><\/p>\n<ul class=\"wp-block-list\">\n<li>Sheng, E., Zhu, R., O\u2019Rourke, B., Pedzinski, D., and Zhang, K. \u201cThe Three Layers of an Agentic AI Platform.\u201d Bain &amp; Company, April 2026. <a href=\"https:\/\/www.bain.com\/insights\/the-three-layers-of-an-agentic-ai-platform\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/www.bain.com\/insights\/the-three-layers-of-an-agentic-ai-platform\/<\/a><\/li>\n<li>Salesforce Architects. \u201cThe Agentic Enterprise: The IT Architecture for the AI-Powered Future.\u201d <a href=\"https:\/\/architect.salesforce.com\/docs\/architect\/fundamentals\/guide\/agentic-enterprise-it-architecture\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/architect.salesforce.com\/docs\/architect\/fundamentals\/guide\/agentic-enterprise-it-architecture<\/a><\/li>\n<li>\u201cEnterprise agentic AI requires a process layer most companies haven\u2019t built,\u201d VentureBeat, reporting on the Celonis 2026 Process Optimization Report. <a href=\"https:\/\/venturebeat.com\/orchestration\/enterprise-agentic-ai-requires-a-process-layer-most-companies-havent-built\/\" rel=\"nofollow noopener\" target=\"_blank\">https:\/\/venturebeat.com\/orchestration\/enterprise-agentic-ai-requires-a-process-layer-most-companies-havent-built\/<\/a><\/li>\n<\/ul>\n<hr class=\"wp-block-separator has-alpha-channel-opacity\">\n<p><strong><em>Ken Callander is Managing Principal of Value Strategies LLC, a consulting practice that advises corporate legal departments on outside counsel pricing strategy. He previously served as Head of Legal Operations at Uber Technologies. He is a Certified Pricing Professional and holds a degree in Physics from Stanford University.<\/em><\/strong><\/p>\n<p>The post <a href=\"https:\/\/abovethelaw.com\/2026\/06\/why-you-should-choose-legal-ops-tools-you-can-build-on-part-1-2\/\" rel=\"nofollow noopener\" target=\"_blank\">Why You Should Choose Legal Ops Tools You Can Build On (Part 2)<\/a> appeared first on <a href=\"https:\/\/abovethelaw.com\/\" rel=\"nofollow noopener\" target=\"_blank\">Above the Law<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Ed. note: Second in a series. Read the first installment here. The previous article in this series proposed that Legal Operations leaders should evaluate legal technology not on the polish of its embedded AI features but on whether the underlying platform allows the department to build custom agents on top of it. That argument addressed [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[16],"tags":[],"class_list":["post-155297","post","type-post","status-publish","format-standard","hentry","category-above_the_law"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/155297","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/comments?post=155297"}],"version-history":[{"count":0,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/155297\/revisions"}],"wp:attachment":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media?parent=155297"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/categories?post=155297"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/tags?post=155297"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}