Podcast Summary: AI & I with Dan Shipper
Episode: If SaaS Is Dead, Linear Didn’t Get the Memo
Date: April 1, 2026
Guest: Kari (Co-founder and CEO of Linear)
Overview
This episode explores the evolution of SaaS in the AI era through the lens of Linear, a productivity and product management tool. Host Dan Shipper interviews Kari, Linear’s co-founder, about how the company navigated the transition to being “agent native”, rethought product workflows, and balanced speed, quality, and decision-making in software development. The discussion offers insights for founders, builders, and anyone interested in how AI is transforming organizational strategy and execution.
Key Discussion Points & Insights
1. Linear’s Philosophy: Patience, Craft, and AI Integration
- Kari explains Linear’s founding principle: focusing on craft, patience, and building the "best product in its category" rather than chasing trends or rushing features. This philosophy informed how they engaged with AI.
Key Quote:
“We just want Linear to be the best product in this category and helping companies move work forward... This new AI stuff doesn’t really change that mission; it maybe even improves it.” — Kari (02:55)
- Rather than jumping on early AI chatbots, Linear spent years understanding real workflows and user needs before releasing their own agent platform.
2. Linear as a System for Guiding Agents
- Linear’s platform is now agent-native: companies can integrate their own AI agents (e.g., internal coding bots from Coinbase and Ramp) to drive workflow automation.
Notable Quote:
“Everyone will have many agents and companies will build their own agents. Linear becomes kind of like a system for guiding the agents and building this context.” — Kari (00:00, revisited in 05:45)
- Their approach: remain open, not attempting to "own everything," but rather provide high-quality integration and context management.
3. Deliberate Adoption of AI Features
- Initial internal trials with chatbots were found to be unhelpful—not enough real workflow value.
- Linear created an agent platform with excellent documentation, enabling external integration and rapid adoption once the market demanded it (e.g., OpenAI’s Symphony platform).
4. The SaaS is Dead Meme and Market Realities (07:39)
- Dan raises the “SaaS is dead” narrative and the pressure public companies face. Kari agrees large companies may struggle due to inertia, but sees new opportunities for focused, flexible startups.
Kari:
“Even for us, we consider now it’s like we need to live in this day one world again where we can’t rely on our previous decisions anymore.” (11:29)
5. Adapting Team Workflow to AI (12:54)
- Linear has 120 people (60 on product).
- The company encouraged broader adoption of agent coding tools but cautions against “vanity metrics” like % of AI-generated code.
- Emphasizes meaningful output and product quality over raw throughput.
Memorable Quote:
“The biggest vanity metric is how much of your code is agent written... But what does that output do? Does it actually generate value?” — Kari (13:40)
6. Meaningful Metrics in the AI Era (15:03)
- Kari advises using classical metrics (revenue, customer love, bugs) over AI-specific metrics.
- Linear employs a “zero bugs policy” fixed within one week—AI agents now help execute first-pass fixes, with engineers reviewing in Linear’s interface.
“With the agents and AI it’s almost like, why do you even have bugs in your product? There’s no excuse for it anymore.” — Kari (16:46)
7. How AI Changes the Product Workflow (17:42)
- AI skills in Linear can synthesize customer requests, helping quickly understand and prioritize features.
- Kari still values manual design work for conceptual phases, underscoring the role of human judgment and exploration.
Figma Example:
“For me, my work is often more exploring things. So I actually don’t think the speed [of AI] helps there. I like the slowness of the manual thing.” — Kari (19:05)
- For engineering, agents can turn conversations or Slack discussions directly into actionable issues and fixes.
8. Balancing Speed and Deliberation (21:52)
- Linear leverages tools and agents for rapid execution—but maintains a “go slow to go fast” strategy for decision-making.
“I don’t want the problem finding to be fast. You should take the time to find the right problem... then you can go faster on it.” — Kari (22:17)
- Prototyping is often for internal understanding, not always direct shipping.
Concept Process:
“Even with all this tooling, the output shouldn’t always be like we ship something. Sometimes the output can be something internal that, hey, now we have a better understanding of this problem.” — Kari (25:51)
9. Product Strategy in the Age of Agents (30:01)
- Linear combines both bringing agent integration to third parties and building their own “Linear Agent” and “coding agent” with deep product context.
- The vision: context-rich, shared workspaces enable smarter automation—e.g., automating bug fixes where the agent knows what context to bring.
Practical Benefit:
Linear acts as a "cloud conductor"—the context is shared and visible, agents do the grunt work, and the human team reviews collaboratively.
10. Demo Highlights (37:16)
- Kari demos Linear’s new interface featuring agents and skills:
- Users can create custom “skills” (prompt-based tools) to synthesize and reason about requests.
- Tasks (like “create a new, pure black dark theme”) can be delegated to a coding agent, with real-time progress and team transparency.
- Shared context: multiple team members can see and interact with an agent session or proposed code changes.
- Pull request previews, in-context code review, and contextual collaboration are baked in.
11. Building vs. Integrating: Scope Creep and Focus (44:23)
- Linear aims not to be a “kitchen sink” product or an agent platform for everything, but to improve the real workflow of building and maintaining product software.
“We always thought about it like—we try to feel what is a natural next step in this workflow... We are always focused on the workflow.” — Kari (46:19)
12. Looking Ahead: The Future of Product Development (47:47)
- Kari projects five years ahead:
- More “self-driving” aspects—features and products will run themselves based on inputs and rules.
- AI/agents will handle pattern recognition, routine decisions, and even customer feedback cycles.
- Human thinking, context-setting, and strategy remain central; agents can codify strategy, but not replace creativity, judgment, or intuition.
Quote:
“Product building is still kind of like a craft or an art...You still need the human touch of what is interesting, or what would make this good.” — Kari (50:45)
Notable Quotes & Moments
| Timestamp | Speaker | Quote | |-----------|---------|-------| | 00:00 | Kari | “Everyone will have many agents and companies will build their own agents. Linear becomes kind of like a system for guiding the agents and building this context.” | | 02:55 | Kari | “We just want Linear to be the best product in this category…this new AI stuff doesn’t really change that mission…” | | 13:40 | Kari | “The biggest vanity metric is how much of your code is agent written... But what does that output do? Does it actually generate value?” | | 16:46 | Kari | “With agents and AI it’s almost like, why do you even have bugs in your product? There’s no excuse for it anymore.” | | 22:17 | Kari | “We shouldn’t go fast in deciding things or...speed running the decisions…You should take the time to find the right problem and the right approach.” | | 25:51 | Kari | “Even with all this tooling, the output shouldn’t always be like we ship something. Sometimes the output can be something internal that, hey, now we have a better understanding of this problem.” | | 46:19 | Kari | “We are always focused on the workflow and how do we improve it.” | | 50:45 | Kari | “Product building is still kind of like a craft or an art. A lot of times we talk about intuition…You still need the human kind of touch.” |
Timestamps for Key Segments
- Linear’s AI Integration Philosophy — 02:55–07:39
- Market Pressures & SaaS Future — 07:39–12:16
- Team Workflow & Agent Coding — 12:54–17:56
- Balancing Speed and Deliberation — 21:52–23:36
- Conceptual Design vs. Shipping — 25:08–29:28
- Product Strategy & Building Agents — 30:01–34:14
- Demo of Agent Features & Collaboration — 37:14–44:23
- Scope, Focus, and AI Platform Decisions — 44:23–47:47
- Kari’s 5-Year Prediction on Product Development — 47:47–51:51
Conclusion
This episode offers a masterclass on reimagining SaaS for the AI era—balancing patient, thoughtful product development with rapid agent-accelerated execution. Kari’s insights highlight the enduring importance of human judgment, strategic focus, and craftsmanship, while also embracing the power of AI to automate, synthesize, and streamline the software creation process. For anyone navigating digital transformation or fascinated by the future of work, this conversation is essential listening.