Welcome back to Good Better Best.
Each week, we break down real pricing, packaging, and product moves from SaaS and AI leaders and share the ideas worth stealing.
This week, we hosted an Office Hours session focused on pricing iteration. Most teams assume they have a pricing strategy problem, but this week Ulrik Lehrskov-Schmidt and Arnon Shimoni make the case that it's really two other things holding you back: your billing system and your org. Below, we’ll go deep on both.
Let’s get to it.
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This Week in Pricing, Packaging, and Product
This week we observed 100+ changes. The highlights:
DeepSeek dropped its peak/off-peak plan and warned of a broader increase [Link]
env0 discontinued the Cloud Compass plan, and added a Free tier [Link]
Landbot moved the Business plan's AI Chats quota to Custom [Link]
Microsoft Teams added a "Try for free" trial to Standard with Copilot [Link]
Privy swapped its 14-day trial for a Buy-1-Year-Get-6-Months-Free promo [Link]
QuickBooks added a Free plan and hiked Essentials ($75→$85/mo) [Link]
RD Station cut the Pro plan $269→$159/mo and dropped its contact limit 5K→3K [Link]
Runway launched a 7-day unlimited Seedance 2.5 promo for new Max signups [Link]
Shopify added MB WAY and Bizum payment methods [Link]
Softr repriced plans across the board [Link]
Substrate added the MiniMax H3 video model to its media catalog [Link]
Sumo Logic added a new MCP Server AI integration to Dojo AI [Link]
Superblocks added Admin MCP, Smart Model Routing and 3 security features to Enterprise [Link]
Surfe cut the Free plan search limit 1,000→100 results/week [Link]
Strikegraph added the CMMC framework and a self-serve trial to the Certify plan [Link]
Teamwork shortened its free trial from 30 days to 14 [Link]
UserGems raised prices across all tiers [Link]
Unify upgraded the Business plan's AI model to GPT 5.6 [Link]
Viktor added spend-cap controls to Team & Enterprise [Link]
Wispr Flow launched Notetaker AI meeting notes and dropped its 14-day Pro trial [Link]
Check out more updates on PricingSaaS →
The Two Forces that Slow Pricing Velocity
Most teams that feel stuck on pricing assume they need a better strategy. That may be the case, but often, there are two other forces holding them back.
Last week I hosted an Office Hours session on pricing velocity with two people who’ve seen this from opposite ends:
Ulrik Lehrskov-Schmidt, CEO of Willingness to Pay, who has implemented hundreds of complex pricing strategies for B2B SaaS companies.
Arnon Shimoni, VP of Growth at Solvimon, who has seen under the hood of some of the most complex billing implementations on the planet.
Together, they highlighted the two forces that most frequently stand in the way of pricing velocity: the System and the Organization.
Force One: The System
This is Arnon's territory, and he shared a common progression that results in pricing stagnation: (1) a company’s billing system creates constraints, (2) the person who manages the system is the only one who deeply understands the constraints, and (3) that person becomes a gatekeeper for pricing changes, stifling pricing velocity.
1. Infrastructure limits what pricing models are technically possible.
The NIH Cycle
Arnon draws this as a loop he calls the NIH (Not-Invented-Here) cycle.
You build the system, you get good at it, and then the system starts defining your pricing. The team works within its constraints, the constraints start to feel like common sense, and eventually nobody questions them at all. By the end you're optimizing around what you know your stack can do instead of what the market wants.
As Arnon put it in Office Hours, "Your billing system isn't just a system for charging customers, it's a system for remembering every promise you've ever made." When it can't represent a new idea, you stop proposing it.
2. Human dependency limits how quickly the org can change.
Underneath the cycle is a person. Most monetization systems depend on one person who holds the integration logic in their head. Arnon traces the psychology to the IKEA effect:
You trust what you understand, and
You understand what you built, so
When someone proposes swapping your homegrown billing for something external, the first instinct is skepticism.
The ceiling on your pricing becomes what that one person can imagine, and what they can imagine is likely bounded by what they already built.
3. Pricing speed compounds, and laggards get left behind.
This bottleneck is especially dangerous in times of rapid experimentation, which is exactly what’s happening with AI pricing today. AI-native companies experiment more rapidly than legacy SaaS players. Vercel has shipped 5-6 pricing changes in a single month, Lovable made multiple material updates last year, and Cursor reset its core plan twice in 2025 — adjusting credit-to-output ratios within days of OpenAI and Anthropic moving token prices.
Each experiment allows these teams to learn something about their customers that slow-movers don’t, and those learnings compound. As Arnon said in Office Hours, "When pricing changes are easy, you make more of them. When you make more of them, you learn faster."
Force Two: The Org
This is Ulrik's territory, and he points to a common progression that reaches the same stagnation: (1) “win the deal” mindset pushes sales to cut bespoke deals, (2) each bespoke deal adds commercial debt that cascades across the org, and (3) the deeper the commercial debt, the harder it becomes to make any uniform pricing change.
1. “Win the deal” mindset pushes sales to cut bespoke deals.
Bespoke deals start with a rep trying to close their quarter. To win, they promise something outside the standard model: a custom rate, a special entitlement, a carve-out. Some of it lands in the contract; some of it lives in a verbal side-agreement that never gets documented at all. The nature of bespoke deals is that the rep gets the upside, while moving the operational cost across the company.
As Arnon put it, sales makes these commitments "officially and unofficially in sales meetings," and "not everything is documented, and then it ends up wreaking havoc." One deal at a time, your contracts stop looking like each other, which is exactly where commercial debt begins.
2. Commercial debt cascades across the organization.
This variance across contracts, where no two customers are quite alike, compounds across the entire org:
Product delays monetization to accommodate the exceptions
RevOps builds shadow spreadsheets to track who got what, and
CS inherits the complexity at every renewal
It never shows up on a balance sheet, which is exactly why it never gets paid down.
3. The more you customize, the harder it is to change pricing for everyone.
Commercial debt has a compounding cost: it slowly takes away your ability to make uniform moves to your model. The deeper into customization you go, the fewer customers share the same terms.
Ulrik's antidote is to make flexibility standard before it turns bespoke: predefined "catalog amendments," a set of approved concessions a rep can apply without pulling legal and engineering into every deal. Give sales room to bend within guardrails, and you keep the ability to move everyone together.
The Takeaway
Both of these forces feed each other. A rigid billing stack limits what you’re able to offer, while a messy contract book forces more custom logic back into the system. Fix one, and you’ll still be constrained by the other.
A solid test worth stealing from the session: could you run one pricing experiment this month that would have taken a quarter a year ago?
If not, try to figure out if one of these forces is the reason why. The good news is that both are fixable. The companies pulling ahead didn't get necessarily get smarter about pricing. Many of them just made pricing easier to change.
Thanks for reading! If you’re working on AI monetization and want to learn more about how we help, book time here.
Until next time,
Rob