Agentic usage drove Harvey's gross margin from roughly +50% to -50% within the first half of 2026.
-
Sam Jacobs said on ToplineScaling AI companies averaged roughly 41% gross margins in 2024 and 45% in 2025, far below SaaS's mid-70s, because every prompt burns tokens; Harvey hit -50% as agents consumed usage.ListenMetrics & finance
3 sources
Scaling AI companies averaged roughly 41% gross margins in 2024 and 45% in 2025, with a projected 52% in 2026; application-layer companies ran lower at 33%, 38% and a projected 45%. Listen
Sam Jacobs cited Iconic data to contrast AI economics with SaaS, where the median company ran gross margins in the mid-70s and the best exceeded 85%. He said token consumption on every prompt and document means AI companies cannot assume the SaaS margin floor.
“So Iconic found that scaling AI companies average roughly 41 % gross margins in 2024, 45 % in 2025, and a projected 52 % in 2026”
Listen to the episode Episode Metrics & finance Link to this
Harvey's gross margin fell from about +50% at the start of 2026 to -50% by June, which Sam Jacobs attributed to rapid agentic adoption consuming tokens. Listen
Sam Jacobs said Harvey's cost to deliver $1 of revenue went from 50 cents to $1.50 as agents consumed tokens on behalf of human users. Harvey was growing extremely fast, but every dollar of revenue was destroying gross profit. He said Harvey's path out is training and hosting its own models, including open-weight models, and moving away from frontier models from labs like Anthropic and OpenAI.
“by June, Harvey's gross margin due to rapid, agentic Adoption right agents going out and consuming tokens on behalf of their human users Harvey's gross margin had fallen to negative 50 %”
Listen to the episode Episode Metrics & finance Link to this
Sam Jacobs's straw man: tolerate bad gross margins above 200% growth if there is a path to a good business, require a clearly improving trajectory at 100–200%, and require good margins below 50% growth. Listen
Sam Jacobs offered this explicitly as a straw man for his co-hosts to react to. Above 200% growth he will accept terrible margins temporarily, for example to subsidize usage or win market share, but only if the company shows the path to a good business. Between 100% and 200% growth he wants a clear improving margin trajectory, and below 50% growth he needs margins to be good. He did not specify a rule for 50–100% growth.
“Above 200% growth, I can tolerate bad margins temporarily. If you can show me, you have a path to a good business.”
Listen to the episode Episode Metrics & finance Link to this
-
Asad Zaman said on ToplineAs acquisition odds rise, annual-cliff vesting can leave employees without acceleration terms with nothing when a deal closes early in a grant, so equity should vest monthly as "credit for time served."ListenHiring & team building
3 sources
Rising M&A makes annual-cliff vesting unfair, and that equity should vest monthly as 'credit for time served'. Listen
Asad Zaman said that as acquisition odds rise, an employee may leave with nothing if a deal closes, say, ten months into a four-year grant. That happens unless they negotiated single- or double-trigger acceleration, which junior and mid-level people usually lack the leverage to get. He proposed pro-rata monthly vesting instead of vesting at the end of each year. Without it, he said, the imbalance fuels frustration when markets get choppy.
“it just vests on a monthly basis and I think that's a big shift that has to happen”
Listen to the episode Episode Hiring & team building Link to this
Tech M&A deal counts fell 58% from 2022 to 2023, then rose 41% in 2024 and 68% in 2025, with AI acquisitions up 85% in 2025. Listen
Asad Zaman presented M&A data covering tech companies broadly. AI acquisitions rose 16% from 2023 to 2024 and 85% from 2024 to 2025. Q2 2026 acquisitions were up 49% on Q2 2025. He said companies are buying other companies at a much higher rate than people realize.
“You had a 41 % increase in 24 versus 23 and a 68 % increase in 25 versus 24.”
Listen to the episode Episode Strategy & market Link to this
Asad Zaman proposes balancing pro-rata vesting with a first-year buyback right for underperformers and full vesting on acquisition. Listen
Asad Zaman said simple equity structures over-protect the company, hurt some people and make it harder to attract great talent in a tight market. His balance is pro-rata vesting plus protections. If someone is fired for poor performance within the first year, the company can buy the equity back at a multiple of the grant price or require exercise within a set period. If an acquisition happens, everything vests.
“And so instead, if you just say, hey, you're not performing, we fire you, then you don't get to hold on to that equity forever.”
Listen to the episode Episode Hiring & team building Link to this
-
Jesse Zhang said on GritDecagon felt it had product-market fit at roughly $1M in revenue from about six customers, with the two founders still doing all the selling.ListenStrategy & market
2 sources
Decagon felt it had product-market fit at roughly $1M in revenue from about six customers, with the founders still doing all the selling. Listen
Zhang says there was no clear cliff, only a gradual scale-up. Around $1M from about six customers paying real contracts felt repeatable enough to signal demand. He calls customer support and coding the two big horizontal AI use cases, with law and some healthcare more vertical. He says they did not know this going in and that mapping out the market upfront is not wise because it is noisy.
“Six customers, a million in revenue. It's like, okay, well yeah, there's a lot of people that want this. People willing to pay us real contracts.”
Listen to the episode Episode Strategy & market Link to this
Decagon hired only when it felt the pain for its first 18 months, including sales, and Zhang thinks in hindsight this may have been a mistake. Listen
For roughly the first 18 months and first 50–60 people, Decagon did not hire ahead. Zhang and co-founder Ashwin did all the sales, and the first salespeople were hired when there were already deals waiting for them. Zhang says that in hindsight, given how strong the market turned out to be, 'maybe' they should have hired ahead, but in the moment the stories of companies that over-hired and then had layoffs made them cautious.
“We only hired someone when we actually felt the pain of, okay, we need someone doing this. That went for sales as well. I mean, in the beginning, Ashwin and I were doing all the sales, and eventually when we hired our first salespeople, it was like we already had deals for them.”
Listen to the episode Episode Hiring & team building Link to this
-
John McMahon said on Revenue BuildersReps lose about five hours a week re-entering deal data across disconnected tools, and managers who distrust the CRM end up chasing the forecast instead of coaching.ListenSales process & deals
2 sources
Disconnected sales tools force reps to re-enter deal data, which McMahon estimated at about five hours a week of lost selling time. Listen
McMahon described reps juggling Gong, Outreach, Clari, the CRM, Word and Excel, where a Friday update is outdated by Monday. He added that managers and others ask for deal updates after each call, so he estimated three to four weeks of a quarter lost to updating the stack and updating people. Kaplan added that the typical stack is 12 to 15 products that do not talk to each other.
“So where the big productivity losses are is when I gotta update the entire tech stack all the time so I'm wasting probably five hours a week updating the tech stack”
Listen to the episode Episode Sales process & deals Link to this
Managers who do not trust CRM data end up chasing reps for updates, which replaces coaching with forecast chasing. Listen
McMahon said managers hound and pound reps for updates because they need an accurate forecast and do not trust the data in the tech stack. He said managers should instead go on sales calls with reps and coach them to be more productive.
“They are basically doing what I call chasing the forecast Instead of effectively coaching Going on sales calls with reps and making them more productive”
Listen to the episode Episode Sales team, hiring & comp Link to this
-
Kellie Woodin said on [Un]ChurnedHer email-drafting agent saves roughly 10 hours a week on under 500 Notion credits a day, and usage pricing lets CS offset seat contraction with agent-driven credit usage.ListenAI
3 sources
Kellie Woodin's email-drafting agent saves her roughly 10 hours a week and runs on under 500 Notion credits a day. Listen
Her agent, 'reply wood', drafts responses to customer product questions and best-practice requests overnight. She starts the day with about 20 drafts to edit instead of 20 unread emails. She estimated it saves an hour or more a day, 'maybe 10 a week', and said it runs on under 500 credits a day. A separate AITP agent drafts tailored AI transformation plans; these are less in-depth for commercial accounts than for higher-ARR mid-market ones.
“instead of having 20 unread emails, I have 20 drafts waiting for me to tweak or to add my flavor.”
Consumption pricing puts 'good pressure' on CS to prove value, and Notion answers it with a calculator setting credit cost against hours saved. Listen
Kellie Woodin said product usage data doesn't tell the full story, so CS has to understand the actual time saved. Notion's internal 'custom agent hall of fame' includes a small calculator for what credits are worth. Her example takes hours an agent saves (about 10 a week for her email agent) times an hourly salary rate and compares that with credits that cost under $5 a day. Customers come to Notion for guidance on these calculations across their LLM and Notion credit usage, which she said positions CS as strategic.
“we've been able to include a small calculator of how to understand what the credits are worth.”
Listen to the episode Episode Pricing & packaging Link to this
Usage-based pricing gives CS new levers at renewal, such as offsetting seat contraction with agent-driven credit usage. Listen
Kellie Woodin said that under seat-based pricing, the best CS could do after a seat contraction was try to win seats back. Under Notion's new usage-based pricing there is 'no ceiling'. A contraction can be offset by building workflows with custom agents that raise credit usage. Her lesson from her first renewals was that they are no longer black and white: she brings in power users and other stakeholders to show what Notion can be beyond a license count.
“previously, if they had some kind of contraction in seats, the best we could do is try to get them back up.”
Listen to the episode Episode Pricing & packaging Link to this
From 5 episodes that week, checked against their transcripts.
Most discussed this week: AIHiring & team buildingLeadership & culture