Insights
How I Learned to Stop Course-Correcting and Start Using Message Checkpoints
Why hitting the reset button will actually save you time instead of fighting an upstream context current.
Insights
Guides
How to Use Your Claude Max Subscription in Cline
Tap into your existing Claude Max or Pro subscription to use Cline without paying per-message pricing.
Insights
Why Cline Doesn't Index Your Codebase (And Why That's a Good Thing)
Here's a common question we get from prospective Cline users: "How does Cline handle large codebases? Do you use RAG to index everything?" It's a reasonable question. Retrieval Augmented Generation (RAG) has become the go-to solution for giving AI systems access to large knowledge
Insights
The Fighter Pilot's Guide to Software Strategy
AI companies are operating in arguably the most hotly contested market in human history. Earth shattering venture rounds incenting and empowering the brightest minds in the world in a winner take most (if not all!) race to the singularity. Amidst this battlefield, I find my thoughts returning to a little
Guides
Cline's Context Window Explained: Maximize Performance, Minimize Cost
Ever wondered why a simple "Hi" to Cline might seem to use more resources than expected? Or perhaps you've noticed performance subtly changing during a long coding session? The answer often lies in a crucial, yet sometimes misunderstood, concept: the context window. Understanding it is key
Insights
SICP Revisited: Writing Code for People and AI Agents
Since SICP, it's been a maxim of software engineering that "Programs must be written for people to read, and only incidentally for machines to execute." However, in the age of generative AI, code is increasingly often read by agents as well. As generative AI tools become
Insights
Inside Cline's Framework for Optimizing Context, Maintaining Narrative Integrity, and Enabling Smarter AI
Effective context management is the backbone of productive collaboration with AI coding assistants. As conversations with Cline evolve and become ever more complex, determining how to handle the persistent issue of limited room in the context window becomes increasingly more important – as well as ensuring narrative integrity is maintained during
Insights
Human Intent in the Age of AI: Insights from Our Chat with Siddharth Ahuja, Creator of the Ableton & Blender MCPs
The developer community has been buzzing about the possibilities unlocked by the Model Context Protocol (MCP), and few examples have captured the imagination quite like Siddharth Ahuja's MCP servers for Ableton Live and Blender. These notoriously complex creative powerhouses, suddenly accessible through natural language prompts via tools like
Insights
How Cline Creates Compound Productivity for Engineering Teams
Picture this: Your senior engineers spending most of their time on high-level architecture instead of debugging nested loops. Your new hires becoming productive in days instead of months. Your entire team shipping more code with fewer bugs while actually leaving work feeling energized instead of burnt out. Sound like fantasy?
Insights
What Happens When You 5x The Output of Every Engineer: Unlocking Trillions in Economic Value
Last week, we spoke with a San Francisco-based startup that estimated Cline had boosted their engineering output fivefold. While startups tend to adopt new technologies more quickly, we're still in the early days of AI-powered coding. This "5x" increase offers a glimpse into what could be
Insights
The End of Complex UIs: How MCP Servers Are Eliminating Software Learning Curves
Have you seen those viral videos of people creating stunning 3D scenes in Blender by just describing what they want? No clicking through complex menus, no hunting for the right tool in a sea of options, no watching 10-hour YouTube tutorials. Just conversation. 0:00 /0:20 1× This isn&
Use Cases
“5X Force Multiplier”: How a Sports Analytics Startup Scales Their Engineering with Cline
In the fast-paced world of sports analytics, where deadlines are dictated by game schedules and championships, engineering teams face unique challenges. For Cleat Street, a fast-growing sports analytics company launched in 2019 out of a startup lab at Columbia University, the pressure to deliver quality code with a small team