About
Passionate about driving revenue excellence working with sales, marketing, and customer…
Articles by Jeff
Activity
25K followers
-
Jeff Ignacio posted thisAgents left to their own devices without a proper harness and context will hallucinate. Here's an example, a sales team with $2M in quota and a stretch team target of $2.8M will somehow become a target of $4.8M. That's nonsense! A few things drive this: 𝗔𝗺𝗯𝗶𝗴𝘂𝗼𝘂𝘀 𝘁𝗲𝗿𝗺𝘀 𝗴𝗲𝘁 𝗿𝗲𝘀𝗼𝗹𝘃𝗲𝗱 𝗯𝘆 𝗴𝘂𝗲𝘀𝘀𝗶𝗻𝗴. "Goal," "target," "quota," and "stretch" overlap in everyday RevOps usage. If the instructions or config don't pin each one to a specific field, the model picks a reading and commits to it confidently --> plausibility over correctness 𝗠𝗼𝗱𝗲𝗹𝘀 𝗿𝗮𝗿𝗲𝗹𝘆 𝘀𝗮𝘆 "𝗜'𝗺 𝗮𝘀𝘀𝘂𝗺𝗶𝗻𝗴." The inference comes out as a plain fact, which is why it looks like the agent invented its own goal rather than guessed 𝗖𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝗼𝗻𝘀 𝗱𝗼𝗻'𝘁 𝘀𝘁𝗶𝗰𝗸 𝘂𝗻𝗹𝗲𝘀𝘀 𝘀𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝘀𝘁𝗼𝗿𝗲𝘀 𝘁𝗵𝗲𝗺. If you fixed it in one thread and the agent can't see that thread, the next answer starts from the same inference again. Fixing it in a conversation isn't the same as fixing it in the system So how do you solve for this? 𝗖𝗼𝗻𝗳𝗶𝗴 𝗮𝗻𝗱 𝗺𝗲𝘁𝗿𝗶𝗰 𝗱𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻𝘀 𝗱𝗼 𝘁𝗵𝗲 𝗵𝗲𝗮𝘃𝘆 𝗹𝗶𝗳𝘁𝗶𝗻𝗴. They remove the ambiguity at the source. If "target" maps to one field and "stretch" to another, and the code computes coverage from those fields directly, the agent has nothing to infer. It should also be the single source of truth, so the agent pulls from the same place rather than each prompt carrying its own interpretation 𝗔𝗻𝘆𝘁𝗵𝗶𝗻𝗴 𝘁𝗵𝗮𝘁 𝗵𝗮𝘀 𝗮 𝗿𝗶𝗴𝗵𝘁 𝗮𝗻𝘀𝘄𝗲𝗿 𝗯𝗲𝗹𝗼𝗻𝗴𝘀 𝗶𝗻 𝗰𝗼𝗻𝗳𝗶𝗴, and memory should hold what's left over 𝗔 𝘄𝗮𝘆 𝘁𝗼 𝗽𝗿𝗼𝗺𝗼𝘁𝗲 𝗰𝗼𝗿𝗿𝗲𝗰𝘁𝗶𝗼𝗻𝘀. When someone corrects the agent, that should flow into a review step where it either becomes a config change or gets discarded 𝗔 𝗴𝘂𝗮𝗿𝗱𝗿𝗮𝗶𝗹 𝗳𝗼𝗿 𝘂𝗻𝗱𝗲𝗳𝗶𝗻𝗲𝗱 𝘁𝗲𝗿𝗺𝘀. If a question uses a metric the config doesn't define, the agent should say it's unsure and ask, rather than guess. That turns silent inference into a visible gap you can fix Good luck out there to all you agentic builders Go forth and operate 👋
-
Jeff Ignacio posted thisGetting AI to answer deterministic questions can be tricky. Ultimately you want AI to reason over a well vetted, correct set of data . Trying to layer on an LLM to do the searching, filtering, and math is easier said than done.👇 Here's an excerpt of an agentic build I've been deploying: 𝗧𝗵𝗲 𝘀𝘁𝗮𝗿𝘁𝗶𝗻𝗴 𝗽𝗿𝗼𝗯𝗹𝗲𝗺: You asked a real question in Slack, "if we lost our two biggest open deals, what would coverage look like, and how does that compare to last quarter" and the bot kept failing to answer it. Over several tries, it failed in a different way each time, and we chased each failure down one at a time. 𝗧𝗵𝗲 𝗳𝗮𝗶𝗹𝘂𝗿𝗲𝘀, 𝗶𝗻 𝗼𝗿𝗱𝗲𝗿: 𝗜𝘁 𝗰𝗿𝗮𝘀𝗵𝗲𝗱. A coding bug (a variable that never got set in one code path) made the whole thing error out on certain follow-up messages. Fixed. 𝗜𝘁 𝗹𝗶𝗲𝗱. After running out of steps, it said "👍 Anytime" instead of admitting it failed. Fixed so it now says plainly when it couldn't finish. 𝗜𝘁 𝗵𝗮𝗹𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗲𝗱 𝗰𝗼𝗹𝘂𝗺𝗻 𝗻𝗮𝗺𝗲𝘀. The AI was guessing at database filter formats and getting them wrong, burning retries on made-up structure. Fixed by validating and normalizing filters before they ever hit the database 𝗜𝘁 𝗱𝗶𝗱𝗻'𝘁 𝗸𝗻𝗼𝘄 𝘁����𝗱𝗮𝘆'𝘀 𝗱𝗮𝘁𝗲. When figuring out "last quarter," part of the system had no sense of the current date or your fiscal calendar, so it guessed wrong (a whole year off) before self-correcting. Fixed by giving it that context 𝗜𝘁 𝗱𝗶𝗱𝗻'𝘁 𝗸𝗻𝗼𝘄 𝗮 𝘁𝗼𝗼𝗹 𝗰𝗼𝘂𝗹𝗱 𝗱𝗼 𝘄𝗵𝗮𝘁 𝗶𝘁 𝗻𝗲𝗲𝗱𝗲𝗱. There's a function that can pull pipeline coverage for a past quarter, but the AI's instructions never told it that parameter existed, so it kept trying to force the current-quarter-only tool to do something it couldn't, wasting steps. Fixed by describing the parameter properly. 𝗜𝘁 𝗱𝗶𝗱 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 𝘄𝗼𝗿𝗸 𝘁𝗵𝗿𝗲𝗲 𝘁𝗶𝗺𝗲𝘀 𝗼𝘃𝗲𝗿. This was the last one, and it's what we just finished. One of your bot's building blocks (query_quarter_downside) secretly runs a big historical calculation twice internally as part of its own logic, and then the AI, not knowing that, would sometimes ask for that same calculation a third time on its own. Each of those was a full sweep through thousands of database rows. Three sweeps for one question ate the whole step budget before the bot could actually answer. Fixed by adding a cache: the same calculation, asked for twice in one conversation, now gets computed once and reused. Where things stand now: All six of those are fixed and merged. The last live test (before this caching fix) showed real progress, no more crashing, no more lying, no more date confusion, but it still ran out of steps because of that triple-calculation problem. That's exactly what the caching fix addresses And they said that working with AI would be easy! Cheers to the AI operators and builders out there Go forth and operate
-
Jeff Ignacio posted thisWhen renewal forecasts are off. Don’t blame the CSM team when churn occurs. For startups, there might not even be Customer Success Operations function If you can make a case for one, go get one: build out CS Operations Other 𝗳𝗮𝗶𝗹𝘂𝗿𝗲 𝗽𝗮𝘁𝘁𝗲𝗿𝗻𝘀 you might see in your org without it: ➡️ Health scores without evidence ➡️ Renewal dates stored in spreadsheets ➡️ Overloaded CSMs ➡️ Expansion that depends on luck ➡️ No structured handoffs ➡️ Churn codes that provide no insight Under a bit of guidance #revenueoperations can help to build out: ➡️ Renewal management infrastructure ➡️ Expansion operations ➡️ Health scoring ➡️ Customer lifecycle process ➡️ Onboarding capacity and analytics ➡️ CSM coverage and segmentation ➡️ Systems and data ➡️ Operating cadence ➡️ Churn and contraction analytics ➡️ Cross functional governance Give me a shout at Go forth and operate 👋
-
Jeff Ignacio posted thisI find Claude to be quite patronizing. "This is a good place to stop", "... to put down for the night"... I don't think Claude knows what it's like to work with someone in #revenueoperations --> we have quite the motor STOP TELLING ME TO TAKE A REST. I will tell you when I want to rest
-
Jeff Ignacio posted thisI'm genuinely confused by some of the marketing by AI companies "AI is going to destroy jobs!" Keeps building and aiming for IPO "AI is going to destroy civilization!" Keeps building and aiming for IPO I don't get it. Why not just change your message to something far more positive? 🤷
-
Jeff Ignacio shared thisWe're either closing out or in the middle of Q3. Clearly the focus is closing the year out, but us revenue operators we clearly have Annual Planning on our mind. Ugh, not again! I've been jamming with Lusha in my stack and here are a few capabilities I've been unlocking through their API (with the help of my automation workflows and coding agent of course) TAM sizing: leveraging lookalikes in Lusha Seeding accounts with hypothesized buying committees -> for this one I used their decision_maker, potential_champion and end_user contact labels (super helpful) Anonymous website visitors identified (less so for TAM and more so for very top of funnel, intent tracking) But more importantly it looks like they’ve built out their US data offering: ✅ 3.5x more US contacts ✅ 85% more US companies ✅ Now sitting at 87.8M contacts and 6.5M companies ✅ Email accuracy at 98%, phone at 86% As you go through planning here's what I would work towards: ➡️ Define your universe for next fiscal year ➡️ Define regions, segment cutoffs ➡️ Build out your project timelines for territory sizing and account distribution (buffer much more time than you think you'll need) ➡️ Org design (roles, teams, responsibilities/coverage areas) ➡️ Account sizing (wallet share, helpful for expansion motions if you're underpenetrated) ➡️ Sales capacity modeling (likely all you have at the moment is a projected top down booking target but that's enough to work with) Also needless, to say, agents need solid data to work with Good luck out there with planning Go forth and operate 👋 #LushaPartner
-
Jeff Ignacio posted thisIf you're in #revenueoperations supporting your #sales org here are some core tenets to think through as you (re)design your org for next year 👇 𝗦𝗮𝗹𝗲𝘀 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝗗𝗲𝘀𝗶𝗴𝗻 & 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 Define, document, and improve sales processes to increase efficiency and effectiveness 𝗖𝗥𝗠 𝗔𝗱𝗺𝗶𝗻𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 & 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Manage CRM systems (e.g., Salesforce, HubSpot) to ensure data integrity, accuracy, and adoption. 𝗧𝗲𝗿𝗿𝗶𝘁𝗼𝗿𝘆 𝗗𝗲𝘀𝗶𝗴𝗻 & 𝗤𝘂𝗼𝘁𝗮 𝗦𝗲𝘁𝘁𝗶𝗻𝗴 Develop fair and balanced sales territories and establish quotas aligned with company goals (primarily for midmarket and up + outbound; but certainly lead scoring and routing for inbound) 𝗙𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 & 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Build forecasting models, track pipeline health, and provide insights to leadership. 𝗦𝗮𝗹𝗲𝘀 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴 & 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 Create dashboards and reports that track KPIs, revenue, win rates, and rep productivity. 𝗜𝗻𝗰𝗲𝗻𝘁𝗶𝘃𝗲 𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝘀𝗶𝗴𝗻 & 𝗔𝗱𝗺𝗶𝗻𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 Design, implement, and manage commission and bonus plans to align rep behavior with company objectives. 𝗦𝗮𝗹𝗲𝘀 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝗦𝘁𝗮𝗰𝗸 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 Evaluate, implement, and maintain sales tools (e.g., enablement platforms, dialers, enrichment tools). 𝗖𝗿𝗼𝘀𝘀-𝗳𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻 Partner with Marketing, Finance, and Customer Success to align GTM strategy and execution 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 & 𝗘𝗻𝗮𝗯𝗹𝗲𝗺𝗲𝗻𝘁 𝗦𝘂𝗽𝗽𝗼𝗿𝘁 Support onboarding, training, and skill development by providing data-driven insights and process guidance. 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴 & 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 𝗦𝘂𝗽𝗽𝗼𝗿𝘁 Support annual planning, account segmentation, and resource allocation for sales leadership 𝗕𝘆 𝗰𝗼𝗺𝗽𝗮𝗻𝘆 𝘀𝘁𝗮𝗴𝗲 (craw, walk, run) ➡️ In early stage companies, RevOps is the 𝗯𝘂𝗶𝗹𝗱𝗲𝗿: setting up the CRM, basic processes, and reporting. ➡️ As organizations grow, RevOps becomes the 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗼𝗿 helping to align Sales, Marketing, and CS around territories, forecasts, and shared metrics ➡️ At scale, RevOps is the 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗼𝗿 running the GTM operating system with advanced forecasting, complex comp models, and full-stack technology Go forth and operate 👋 (more musings on the Substack, link in profile)
-
Jeff Ignacio posted thisBuilding a #revenueoperations function? Start with a clear charter 👇 It defines the mission, sets boundaries, and positions RevOps as a strategic growth lever rather than a reactive support team. 𝗞𝗲𝘆 𝗲𝗹𝗲𝗺𝗲𝗻𝘁𝘀 𝘁𝗼 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: 1️⃣ 𝗠𝗶𝘀𝘀𝗶𝗼𝗻 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁 State why RevOps exists in one sentence. Keep it focused on business outcomes. 2️⃣ 𝗦𝗰𝗼𝗽𝗲 𝗼𝗳 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 List what RevOps owns across processes, systems, data, analytics, and enablement. 3️⃣ 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗠𝗼𝗱𝗲𝗹 Spell out how RevOps works with Sales, Marketing, CS, and Finance. Include how requests are made and prioritized. 4️⃣ 𝗚𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗮𝗻𝗱 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻 𝗥𝗶𝗴𝗵𝘁𝘀 Clarify where RevOps has authority versus where it collaborates or advises. 5️⃣ 𝗞𝗣𝗜𝘀 𝗳𝗼𝗿 𝗥𝗲𝘃𝗢𝗽𝘀 Measure impact through forecast accuracy, CRM adoption, data hygiene, and SLA adherence. 6️⃣ 𝗢𝗿𝗴𝗮𝗻𝗶𝘇𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲 Outline current roles and future hires across systems, analytics, and strategy. 7️⃣ 𝗦𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗣𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝗲𝘀 Highlight the most critical initiatives for the next 12 to 24 months. 8️⃣ 𝗦𝗰𝗼𝗽𝗲 𝗘𝘅𝗰𝗹𝘂𝘀𝗶𝗼𝗻𝘀 Be explicit about what RevOps does not own to avoid role confusion and political friction. A strong charter gives RevOps the foundation to drive clarity, scale, and predictable growth. Good luck out there Go forth and operate 👋
Jeff Ignacio replied to a comment
11h
Justin Tung ☁ we still have to find a project to work together on!
-
Jeff Ignacio reacted on thisJeff Ignacio reacted on thisI’m thrilled to share that I started a new chapter as Operating Partner, People at Emergence. I’ll focus on building scalable people architecture across our operating companies and partnering with leaders to build organizations where great talent, strong operating systems, and business performance reinforce one another. In a shifting corporate landscape, I’m especially excited to join a permanent-capital platform backed by The Pritzker Organization, with a long-term approach centered on compounding, operational clarity, and sustainable growth rather than short-term cycles. There is a lot to build, and I’m excited to get started. Thank you, Henry T. Zhang, and the entire Emergence team for such a warm welcome. I’m looking forward to building alongside you. #CompassionateCapitalism
-
Jeff Ignacio liked thisJeff Ignacio liked thisWe’re growing the team at Granola… I’m looking for a GTM Analytics Lead to join us! This role will be equal parts technical and partnership-focused, helping lay our GTM data foundation while working directly with GTM leaders to make better, data-informed decisions. I'm looking for someone who’s technically strong, highly collaborative, and excited to build from the ground up. Please reach out if someone great comes to mind! https://lnkd.in/d7m7E4iK
-
Jeff Ignacio liked thisJeff Ignacio liked thisOpen to what’s next. After five years at Syncari, I’m opening the door to my next chapter. Over the last decade, I’ve built and led at the intersection of data, automation, platforms, partnerships, GTM, and operations. At Syncari , I built and led both the global partnerships and marketing organizations, growing partnerships into a meaningful contributor to ARR while leading our category evolution from data automation into Master Data Management. Through marketing, I helped position Syncari in the Gartner Magic Quadrant for Master Data Management Solutions. My scope later expanded into strategy and serving as Chief of Staff to the CEO. Before Syncari, I built Workato’s global partner organization from 0 to 1 and led global partner programs at Alfresco Software Limited (now Hyland). The common thread throughout my career has been leading GTM for emerging technologies, setting strategic direction, and defining the playbook when one doesn’t exist yet. That’s what excites me about AI and agentic platforms. Agents need trusted enterprise data, context, integration, governance, orchestration, and access to the systems where work actually happens. I’ve spent my career working across those layers, from content and integration to automation, MDM, and now the emerging agentic ecosystem. I have builder DNA with a strategic leadership orientation. I’m at my best identifying where a market is going, shaping the commercial strategy around it, and leading the organization that turns that strategy into durable growth. I view partnerships as more than a pipeline source. The strongest ecosystems shape product, distribution, market position, customer value, and ultimately revenue. For my next chapter, I’m exploring leadership opportunities across Partnerships & Alliances, GTM Strategy, and executive operations in AI and agentic platforms, data infrastructure, orchestration, and enterprise software. If you’re building what comes next and looking for someone who can see the opportunity, shape the strategy, and lead, I’d love to reconnect.
-
Jeff Ignacio liked thisJeff Ignacio liked thisAnnouncing our $350M funding round at a $4 billion valuation. Led by a16z and Bessemer, with participation from OTPP, Sapphire, and Navitas. Thrilled I get to build as part of the EliseAI team daily. Bringing down the cost of housing and healthcare is a mission worth working on! Our scale: $200M+ ARR, 30M unique renters reached, 1 in 5 multifamily apts in the US. Back to work! ⚙️
-
Jeff Ignacio liked thisJeff Ignacio liked thisI’m hiring a Senior Director of RevOps to help build the next chapter of Replicant’s revenue engine! This person will work directly with me and partner closely with our CFO to help drive our next stage of growth. We’ve got an incredible team and big ambitions. You’ll help us think bigger, move faster, and build the machine that gets us there. I’m looking for someone who’s built this at a growth-stage company before, can see around corners, and brings both the vision and the drive to make it happen. AI agents are changing how contact centers operate, and the market opportunity ahead of us is massive. If that sounds like you (or someone great in your network) — let’s talk! JD in the comments 👇
Experience & Education
Licenses & Certifications
Volunteer Experience
Courses
-
Advanced Competitive Analysis
Strategy 669
-
Application Development Spreadsheet
BIT 513
-
Applying Business Stategy
OMS 502
-
Applying Business Strategy
OMS 502
-
Business Leadership in Changing Times
MO 611
-
Business in Asia
Strategy 584
-
Corporate Financial Reporting
ACC 564
-
Corporate Financial Strategy
FIN 647
-
Corporate Strategy
Strat 502
-
Corporate Strategy
Strategy 502
-
Data Mining
OMS 567
-
Decision Analysis
-
-
Decision Support Spreadsheet
BIT 512
-
Financial Analysis
FIN 513
-
Human Behavior & Organizations
MO 503
-
Intellect Prop Law
LHC 509
-
Management Accounting
ACC 552
-
Marketing Management
MKT 503
-
Mergers, Acquisitions & Corp Development
Strategy 682
-
Negotiations & Dispute Resolution
LHC 510
-
Operations Management
OMS 552
-
Options &Futures - Corporate Decision Making
FIN 580
-
The World Economy
STRATEGY 503
-
Valuation
FIN 615
-
World Economy
Strat 503
Test Scores
-
GMAT
Score: 730
Languages
-
Spanish
Professional working proficiency
Recommendations received
15 people have recommended Jeff
Join now to viewOther similar profiles
Explore more posts
Explore top content on LinkedIn
Find curated posts and insights for relevant topics all in one place.
View top content