TTV is the time before customers experience the value promised after 'purchasing' the product (e.g., a free trial or a freemium).
Let's take @canva as an example. You can use it immediately. You get sucked in and don't even notice that you've just become their customer! :)
You can easily minimize #TTV by using the Bowling Alley Framework. It's like using "bumpers" to guide users to the outcome your product promises.
There are two types of bumpers:
1. Product Bumpers
Their goal is to help adopt the product within the application.
a. Welcome Messages — displayed after logging in. It's an opportunity to greet users, make them feel invited, and restate the value proposition. They can also set expectations.
b. Product Tours — Eliminate distractions and allow users to focus only on the most critical options. It commonly starts with the question about what users would like to accomplish with the product. Let your users choose their adventure.
c. Progress Bars — Help users understand what's their progress. It's a good practice to start with a substantial percentage of the bar filled in so that users can feel that they are already underway instead of starting from scratch.
e. Onboarding Tooltips — Helpful messages are displayed when interacting with application elements (e.g., mouse hover). It shouldn't be too intrusive; e.g., forcing users to click every detail on a page may not be a good idea.
f. Empty states — After the first login, many applications are tedious. There is no data specific to you; without it, it's virtually impossible to understand what value you will get once you start using the product.
There are two ways:
a) Present users required steps and prompt them to take action.
b) Prevent it from happening. Dynamics 365 Sales populates every trial with sample data. I presented it at the beginning of this article.
Conversational bumpers work to educate the users, set their expectations, bring them back to the application, and eventually upgrade their accounts. I selected the two most popular forms:
a. User Onboarding Emails — can include welcome messages, usage tips, sales touch (to upgrade accounts), case studies, communicating the benefits, information about trial expiration, or post-trial surveys. You can easily automate most of them.
b. Explainer Videos — The name is self-explanatory. Videos can generate even 1200% more engagement than text and images. I highly recommend it, especially for complex products.
After an interview with @karpathy, everyone is talking about what AI agents can/can't do.
But an opinion without data is just a hypothesis.
So, I tested 3x185 workflow executions for a market researcher agent.
The results have shocked me🧵
I tested three variants:
I. LLM Workflow: No agency, the entire logic carefully orchestrated.
What was expected:
- An LLM workflow was 2x faster (the same model) compared to an AI Agent.
- An LLM workflow consumed 12x less tokens to an AI Agent.
3/185 "errors" are minor formatting results.
II. Agentic Workflow: Deterministic logic moved to the orchestration layer.
More time, more tokens.
100% task success.
GPT-5 (a reasoning model) consumed less tokens than GPT-4o due to better compression.
In SaaS, PLG meant free trials, referral bonuses, or “invite your team.”
But AI changes the game.
PLG isn’t just about virality, it’s about compounding adoption.
Over the last few years Miqdad Jaffer (OpenAI) found 7 distinct loops that consistently drive compounding growth:🧵
1. Viral Output Loops → “Every Output Is Distribution”
In SaaS, virality was about users sending invites. In AI, virality lives in the outputs. Images, summaries, videos, answers - they naturally travel across ecosystems.
E.g., Midjourney: Early on, every image generated in Discord carried prompts, channels, credits. Users didn’t just share art; they shared the Midjourney experience. Every screenshot was free marketing.