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Day AI provides the context graph and agent control plane to quickly and securely upgrade…
Articles by Christopher
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Christopher's Love Letter to HubSpot Customers
Christopher's Love Letter to HubSpot Customers
I’ve had the immense privilege to become friends with many of our customers through HubSpot, and have had many of my…
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Why We’re Building HubSpot’s Next Big Product in Dublin
Why We’re Building HubSpot’s Next Big Product in Dublin
Christopher O’Donnell, VP Product at HubSpot When we opened a HubSpot office in Dublin five years ago, there were no…
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Christopher O'Donnell shared thisLFG Austin Gentile - welcome!!Christopher O'Donnell shared thisI first worked with Austin Gentile back in 2019, when I was building HubSpot’s Sales Partner program. From the first moment I met him, I wanted to hire him. He has infectious positive energy, he's sharp, and he’s one of the most motivated people I've ever worked with. So, it means a lot to welcome him into another partner program. This time at Day AI. Austin’s firm, OrbitalWise Consulting (you might know them as Orbital HubSpot Partners), builds AI agents that do real jobs inside a business. Each agent gets one clear job, a shared memory of every call, email and meeting, and a person who approves its work. And they stay until the team can run it without them. The line from their “pitch” that stuck with me: “leads don’t get lost. They get forgotten. Because nobody owns the next step.” Every sales leader I know has a graveyard of those leads, accounts, and deals. Here’s how Austin and the team work. A contractor operating in four states had more demand than their team could keep up with. Before building a single agent, the Orbitalwise team sat in a recruiter’s seat themselves. They mapped every step from first lead to first shift, built daily call lists and call capture with the client’s developer, cut onboarding down to what the state actually requires, and launched a campaign to keep the pipeline full. The goal: one recruiter doing the work of five. Sitting in the seat first is the step most AI projects skip. The team has the HubSpot DNA you’d expect. Austin spent five years there, including time supporting agencies. Gyasi Slaughter spent eight and a half and owns their builds and integrations. And Jacob Jefferson leads sales and strategy after running a social media agency that drove 100M organic views in 90 days. Every agent they build works from Day AI’s customer memory, so nothing depends on someone remembering to update the CRM. And with AI tools changing every week (or so it feels!), that foundation lets their clients plug in whatever comes next with real business context behind it. So, if you run an owner-led, growing company and you know AI belongs in your business but you haven’t been able to make it stick, Austin is your call. Welcome back, Austin. Good to be building together again.
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Christopher O'Donnell reposted thisChristopher O'Donnell reposted thisMy agent drafts every follow-up on my deals. I’m still the one who sends them. On day one, the skill reads your sent emails and learns how you write: sentence length, tone, what you skip, how you close. Every draft after that already sounds like you. I review it, fix what’s off, and send. The agent does the busywork, and I own what goes out. Team rules are locked. Short subject lines. Never name a customer. Never invent a fact. Same for every rep. Voice is personal. Mine writes the way I talk to RevOps people: short sentences, no filler. A teammate’s writes like him. Christopher, our CEO, set one up for David in marketing. It read about fifty of David’s sent emails, rewrote its own email skill to match, and has sent him a Voice of Customer report that gets better every week since July. Lock what needs consistency. Learn each rep’s voice from day one. Keep a human on every send. Check out the video about David's agent in the comments.
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Christopher O'Donnell shared thisLife after CRM.Christopher O'Donnell shared thisSome highlights on week 1 of fully incorporating day.ai into our business: 1) We stopped calling and texting as a team and now try to have all conversations through zoom so every business decision gets recorded in day. 2) All of that context from those calls and emails are going into our business brain. That is teaching day about our ICP and creating a library of lessons we'll leverage for blogs. 3) Follow ups, next steps and team coordination are all becoming tasks we don't spend personal time working on, which is allowing for more sales efforts. 4) Loving their fixed cost payment model. Leveraging 3 agents across the team at a very reasonable cost. Actually, less money per month than my failed prospecting agent I made in Claude. 😂 5) By EOW, we'll have migrated all of sales over, all cold calls are recorded, emails are written. Everything recorded. We have a 7 step outreach program per lead, none of those steps are missed with each lead, every day. My prospecting agent reaches out to me in the morning with a list of who was already emailed and who I need to call each day. I know we're still probably reaching 1% of what we can do within day, so if any #dayai partners or customers have anything you love about the platform, comment below 🙏
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Christopher O'Donnell posted thisWhen you hand someone an agent, you have to decide which parts they're allowed to change. Some of it should be locked. The handoff to CS should cover the same ground no matter who sold the deal. And nobody should be quietly "personalizing" the discount guardrails. Some of it should be theirs. How David in marketing likes his emails written is NOT how I like mine. Recently I built a voice of the customer agent for David, pushed her into his account, and got out of the way. Joanna delivers him work on her own every Monday. She picked up his voice from his sent emails, and when he pushed back on her first report, she changed how she works. Nobody else's agent needed those changes. His did. That's a living agent: a fixed core the team can count on, and a personal layer that learns from the person who manages it. We filmed the whole thing ... the build, the handover, and what it looked like from David's side. Video link in the comments.
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Christopher O'Donnell shared thisHUGEChristopher O'Donnell shared thisFor seven years, 🧙 Christopher Booth refused to join a single partner program… because: “I didn’t want a client to wonder whether we recommended a tool because it paid us.” I’ve spent a good chunk of my career building partner programs. That sentence should make any client a little nervous. So… why break his seven-year streak? Because before recommending Day AI to ANY clients, Chris moved his own company onto it. Before Day AI, any time a lead or client question came up, someone at Charm had to go around the office asking what the last touchpoint was. A sales call? A support ticket? An email someone else sent? Now the full history across sales, support and ops sits in one place. Charm runs its whole operation on our Context Graph, and they’re now rolling it out to clients. So who’s Charm? The team runs sales and customer support for companies that make physical products. Think: pool and spa equipment, at-home health tracking devices, patio heaters for restaurants. On the sales side, they find every retailer, dealer, distributor and installer who could carry a product and go after them by email, LinkedIn and phone. Last year, that added up to over $40M in pipeline for their clients. On the support side, they staff teams that learn each product inside and out and handle thousands of customer conversations a month. Which means Charm sees how new age GTM is forming, and why building and leveraging a context graph is so important for any company to win (even survive) today. Here’s a real client example: one distributor they work with sells stone and tile to designers, and it sells on samples. A designer gets a piece in hand, then orders. When Charm followed 200 sample orders forward, almost none showed a purchase in the CRM. The purchases were happening. They were just recorded in a different system from the one sales works in. So the sales team had no way to tell whether its main tactic was working. It gets better (worse?)... that same company’s order desk answers roughly 40,000 customer emails a year about POs, deposits, back orders and freight. None of it reaches the sales team. And when Charm checked reorder timing for the regular dealers, every single one showed as overdue. Yet, none of them were. The orders were just in another system. “What a customer said on a support call should inform the next sales conversation,” Chris says. “The agent handling a warranty claim should know what the rep promised.” Day AI keeps the full history of a customer, from the first sales call through every support ticket after. For a physical product company, that means sales and support are finally looking at the same real-time information about all its customers. So, if you make a physical product and need help selling it, supporting it, or both, talk to Charm. Welcome to the Day AI partner program, 🧙 Christopher and team.
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Christopher O'Donnell shared thisHonored. To say this is a deep eval of the market landscape of AI-Native GTM vendors would be ... an understatement.Christopher O'Donnell shared thisAfter many discussions with the frontier labs and other players in the GTM x AI space - here's what we think the interface of the future will look like. Context: a LOT of vendors are aggressively building their flavor of the workspace that teams should operate out of. There are some really interesting points of view out there, some of which we think will inevitably converge as "best practice" design/architecture. 1) Chief of Staff + Agent bench: everyone will have a personal AI assistant/CoS that manages a suite of agents to do work on your behalf. Agents will operate asynchronously, connected to your warehouse (or wherever your data sits), and leverage a decision engine/next-best-action framework to advise on what work you should prioritize. The CoS consolidates the "next best action" list down to the things you need to action today. I’d be remiss not to shout out Day AI as having the best in-production version of this idea. 2) Shared workspace/multiplayer: in the harness/UI, people and agents will collaborate together in dedicated spaces. Imagine a workspace for Coca-Cola where the account team and their sub-agents work together on account planning, demo prep, the village map, etc. Think Slack channels, but in the harness, with everyone's agents, and better governance/provisioning. Dust does this best today. 3) Next best action: touched on this above - harnesses will leverage your business ontology and codified GTM strategy to reason about what actions should be prioritized to move deals forward, secure a renewal, or support a customer who isn't realizing value. Agents will use the warehouse to gather deep deal and account-specific context, then apply your GTM strategy to advise reps (maybe via a context graph rather than RAG... TBD). 4) Logs and loops: all actions, agent and human, will be logged. For agents, this includes inputs > reasoning > outputs. You'll be able to use that transactional data to build recursive loops that refine and improve what next-best-action gets recommended. I think of this as autonomous win/loss analysis, where the dependent variable is securing the meeting, deal, or renewal - and the independent variables are all your classical GTM data plus the newly added logs. Context graph may matter here too, vs. RAG... TBD again. 5) Data syncs: in most harnesses today, if an AM builds out a robust account plan for Coca-Cola and then leaves the business, all of that tribal knowledge is lost - it's locked away in a project folder. An agent might write updates back to the CRM, but it's not guaranteed. We envision a future where that tribal knowledge syncs back to the CRM (or directly to the warehouse) without relying on a user to trigger it. Hot take: if this future means writing straight to the warehouse and skipping the CRM, that has implications for the CRM category - it could slowly drift away from being the source of truth for customer and deal data.
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Christopher O'Donnell reposted thisChristopher O'Donnell reposted thisOn a demo last week, a customer success lead told me his best signals come from the product layer: who's actually using it, and whether it's one power user or the whole team. His book keeps getting bigger, so learning that that one call at a time isn’t an option. It runs the other way too. A product team's best signals come from what customers tell sales and CS: the request someone made twice, the workaround a client is using that a CSM heard about on a renewal call. Same customers, read by two teams for two different reasons. At most companies those live in separate places, so each team gets the other's half secondhand. That's the idea behind Christopher O'Donnell's new course: making the product org revenue-oriented turns out to mean making it customer-oriented. In his words, "If you are customer-oriented, the revenue tends to take care of itself." It's free, twelve short chapters, built for product people. Link in the comments.
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Christopher O'Donnell shared thisWill has done something incredibly interesting here …Christopher O'Donnell shared thisAfter grad school, I was looking for a job and cold emailed a cool sounding startup that a friend had just seen a demo of. The response I got was along the lines of "you probably don't want to work here, and we're probably not hiring, but if you really want to, you can swing by my house." I knew I wanted to join Day AI after spending a morning with Christopher in his living room, watching the Day AI team work. The thing that stood out to me most was a moment when a customer reported an issue over Slack. While I was there over his shoulder, Christopher dropped what he was doing, started chatting with the customer, and fixed the issue together with them in real time. From that moment, I've learned a lot from Christopher, much of it about the attitudes we bring to work and how to be of service to our teams and customers. Last month, we blocked our afternoons and I sat down with Christopher to record an interview about what he has learned about building products for customers. A lot of this stuff takes practice, so it evolved into a course with exercises that connect the topics to your day job. Please check out The Revenue-Oriented Product Team and let us know if it helps you or your team. Link in the first comment.
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Christopher O'Donnell posted thisEvery product team wants to be "revenue-oriented." For half of my ten years at HubSpot, the revenue number belonged entirely to marketing and sales. By the time I left, product carried close to two-thirds of the demand SLA. A well-known investor told us he'd basically never seen a sales-driven company become product-driven... HubSpot was the one exception. We didn't get there by staring at a revenue number. We got there by getting product closer to customers, to what they did in the product and what they said on calls. If you're customer-oriented, the revenue tends to take care of itself. We run Day AI the same way. When a customer asks for something on a call, it lands on the Linear issue it belongs to, with the customer attached. Six requests on an issue means six customers you can name, and you can go read what each one said. I put the whole playbook into a free course for product people, APM to CPO. Twelve short chapters, each with an exercise and a prompt you run on your own company's material. Link in the comments.
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Christopher O'Donnell liked thisChristopher O'Donnell liked thisLife after CRM. You have a call tomorrow, so you ask your AI tool for an email to the prospect. You give it a name, a title and a company. It writes a perfectly correct email that sounds like every other email. Someone on r/sales explained why AI outreach feels robotic: it's "working off basically nothing, name and title and that's it." Day AI's CEO, Christopher O'Donnell, calls that a crayon sketch (I'm a Day AI partner, so weigh that). You asked it to build a house. So you do what everyone does and paste in everything. Notes, the website, last quarter's thread, a long list of things it should check, and a polite "make it great :)." It gets worse. I've watched an overloaded prompt invent its own criteria halfway through, like an intern who decided the brief was a suggestion, and hand back answers that are correct and still not what you wanted. I learned this building a list for a client who wanted one specific segment of companies. I asked for property managers and got property managers. Just not the ones who work w/ community associations the client meant. Correct, and wrong. So we stopped asking for everything at once. One column checks one thing: is it a property manager? The next checks what segment they work in, and whether the first answer holds. The third checks the specific area, and the second answer. One question at a time, each one checking the last. You can borrow that tomorrow in any AI chat: ask for one thing, then ask it to verify its last answer before you add the next. Now picture a version of this where you never build those layers. The agent runs the checks before it shows you anything. You open the account and it tells you who on your team has already spoken to them and what each of you pitched, how your current offering fits, and what's moving in their industry. Then it builds you a case. Someone in operations may set up the layers, and you tune your own agent until it hands you what you need to move the deal. It costs you one thing: you have to know what a right answer looks like, because the agent will gladly hand you a correct one. Life after CRM looks like this: you open the account and the homework is already done, and already checked. You ask for that email again. This time it sounds like someone who's been paying attention, and you spend the afternoon thinking about the account instead of feeding the machine. If this is the kind of thing you want fixed at your company, not just read about, DM me.
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Christopher O'Donnell liked thisChristopher O'Donnell liked thisBuilding a DIY CRM is a good place to start. @Christopher O'Donnell argues in Fast Company that it's a risky place to stop. When an internal tool slips, nobody outside the building notices. When the system that's supposed to remember your customers slips, you find out from a lost renewal nobody saw coming. The column is for anyone vibe coding their own company brain who is starting to wonder what happens when the team doubles. https://lnkd.in/e_sHfczS
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Christopher O'Donnell liked thisChristopher O'Donnell liked thisWorking fully remote, nobody sees me: - Start work at 7am - Skip lunch to finish a project on time - Stay late to finish tasks - Sacrifice my own time to help colleagues. Because I don’t do any of these things. #remote #remotework #workfromhome
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Christopher O'Donnell liked thisChristopher O'Donnell liked thisProbably time for a quick update: as some of my network knows, at the end of July I wrapped up 15.5 years at HubSpot. Starting out as a 22-year-old BDR making cold calls, I never expected it would lead to running a sales team of nearly 300 people responsible for $200M+ of ARR. Thank you to the leaders, colleagues, teammates, and reps who made those years worth it, and to every customer who trusted me to help grow their business. I’m grateful for the chance to play a role in HubSpot’s growth over the last 15.5 years. A special thanks to Ryan Beale for hiring me as a sales manager all those years ago, and to Brian Halligan and Dharmesh Shah for building something “our grandkids” will be excited about. As for what’s next: I’m looking forward to building a world-class GTM organization. The last three months have given me the chance to reconnect with old colleagues, new connections, and some remarkable founders leading some of the most successful AI-native startups in the world. I’m excited to share where I’m heading soon, and we’ll be hiring fast. If you’re looking to make a move and want to be part of something, let me know. Here’s to one chapter closing, and a new one beginning 🙌
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Christopher O'Donnell liked thisChristopher O'Donnell liked thisA RevOps leader I shadowed on a scoping call earlier this month described the exact moment her team's agent work stalls: someone builds one that works for them, and it stays theirs. She walked us through a Salesforce hygiene agent her team runs every day, an account research agent a mid-market director built to standardize outbound research, and then the gap: every one of them was built by one person, for one team, and none of them travel. The one she wants most is an account handover agent, so a deal's context follows it from SDR to AE to implementation to CSM, each handover building on the last, instead of living in everyone's personal docs. What she kept circling back to was which parts should run the same way for the whole team, and which should bend to whoever ends up managing the thing. That is the whole question. The hygiene checks have to be identical for everyone or they're not checks. How an AE writes to a customer should never be standardized. I work at Day AI, where our CEO built an agent for our CMO and handed it over; it now reports to him weekly, in his voice. There's a video about it, link in the comments.
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Christopher O'Donnell liked thisChristopher O'Donnell liked thisI first worked with Austin Gentile back in 2019, when I was building HubSpot’s Sales Partner program. From the first moment I met him, I wanted to hire him. He has infectious positive energy, he's sharp, and he’s one of the most motivated people I've ever worked with. So, it means a lot to welcome him into another partner program. This time at Day AI. Austin’s firm, OrbitalWise Consulting (you might know them as Orbital HubSpot Partners), builds AI agents that do real jobs inside a business. Each agent gets one clear job, a shared memory of every call, email and meeting, and a person who approves its work. And they stay until the team can run it without them. The line from their “pitch” that stuck with me: “leads don’t get lost. They get forgotten. Because nobody owns the next step.” Every sales leader I know has a graveyard of those leads, accounts, and deals. Here’s how Austin and the team work. A contractor operating in four states had more demand than their team could keep up with. Before building a single agent, the Orbitalwise team sat in a recruiter’s seat themselves. They mapped every step from first lead to first shift, built daily call lists and call capture with the client’s developer, cut onboarding down to what the state actually requires, and launched a campaign to keep the pipeline full. The goal: one recruiter doing the work of five. Sitting in the seat first is the step most AI projects skip. The team has the HubSpot DNA you’d expect. Austin spent five years there, including time supporting agencies. Gyasi Slaughter spent eight and a half and owns their builds and integrations. And Jacob Jefferson leads sales and strategy after running a social media agency that drove 100M organic views in 90 days. Every agent they build works from Day AI’s customer memory, so nothing depends on someone remembering to update the CRM. And with AI tools changing every week (or so it feels!), that foundation lets their clients plug in whatever comes next with real business context behind it. So, if you run an owner-led, growing company and you know AI belongs in your business but you haven’t been able to make it stick, Austin is your call. Welcome back, Austin. Good to be building together again.
Experience & Education
Patents
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Method of enhancing customer relationship management content and workflow
Issued US20160078455A1
Forward-looking sales activities are poorly served by existing Customer Relationship Managements systems, as the customer information those systems maintain by definition does not include the speculatively interested “leads” pursued in initial sales contacts. An Enrichment database, asynchronously loaded with corporate and optionally individual contact information in anticipation of use, provides real-time access to information in support of such first customer contacts. The Enrichment…
Forward-looking sales activities are poorly served by existing Customer Relationship Managements systems, as the customer information those systems maintain by definition does not include the speculatively interested “leads” pursued in initial sales contacts. An Enrichment database, asynchronously loaded with corporate and optionally individual contact information in anticipation of use, provides real-time access to information in support of such first customer contacts. The Enrichment information may also be used to expedite creation and revision of CRM records.
Other inventorsSee patent
Languages
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English
Native or bilingual proficiency
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Portuguese
Professional working proficiency
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Spanish
Limited working proficiency
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Italian
Elementary proficiency
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Adam Singolda
Adam Singolda
Adam leads Taboola’s business strategy, execution and development while maintaining the company’s unique culture of quantification and innovation.<br><br>Prior to founding Taboola, Adam developed his analytical skills while serving as an officer in an elite mathematical unit of the Israeli National Security Agency for near 7 years (don’t ask, he can’t tell you).<br><br>Adam is an honored alum of the Israeli Defense Forces’ elite Mamram computer science training program, graduated first in his class at the Officers Academy of the IDF, and was recently named one of Israel’s top “30 under 30” business managers by TheMarker.<br><br>Adam authors a column for Mediapost on the video industry and is a regular speaker for Steaming Media, NAB, NewTeeVee, ELEVATE, Meetup, The Israel Conference, MIT (Sloan) , Bloomberg West, and others<br><br>Specialties: I build things
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