Despite being the top community feature request for years, implementing a 'stacked diffs' workflow has been repeatedly shelved at GitHub. Previous efforts were deemed 'too risky' and 'too big of a change' for the platform. This illustrates how even highly desired features can be blocked by the inertia and complexity of a large, established system.
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Saying 'no' to product ideas is often contentious. At GitHub, the process is simplified by first 'seeking the truth'—rigorously assessing if an initiative aligns with the team's definition of success. If it doesn't, the 'no' becomes an objective, logical conclusion rather than a subjective or political decision.
Instead of choosing between diverse user segments, GitHub defines success with extreme clarity. This allows them to treat prioritization like an investment portfolio, allocating dedicated squads to different user needs (e.g., open-source maintainers vs. enterprise admins) to achieve a balanced outcome.
The creative process with AI involves exploring many options, most of which are imperfect. This makes the collaboration a version control problem. Users need tools to easily branch, suggest, review, and merge ideas, much like developers use Git, to manage the AI's prolific but often flawed output.
Tools like Git were designed for human-paced development. AI agents, which can make thousands of changes in parallel, require a new infrastructure layer—real-time repositories, coordination mechanisms, and shared memory—that traditional systems cannot support.
Early user research showed designers did not want a collaborative, multiplayer tool. However, Figma's web-based architecture made a single-player experience technically terrible (e.g., tabs constantly reloading). They were forced by the technology to build multiplayer functionality, which ultimately became their key differentiator, proving the platform's needs can override initial user requests.
To serve both solo developers and large enterprises, GitHub focuses on creating horizontal "primitives" and APIs first. This foundational layer allows different user types to build their own specific workflows on top, avoiding the trap of creating a one-size-fits-none user experience.
Figma learned that removing issues preventing users from adopting the product was as important as adding new features. They systematically tackled these blockers—often table stakes features—and saw a direct, measurable improvement in retention and activation after fixing each one.
Despite user requests, Supercut is holding back on building a traditional video editor. They believe it would become an "excuse" for their AI-powered "auto edit" to be mediocre. This strategic constraint forces them to perfect their core differentiator before adding table-stakes features.
Saying yes to numerous individual client features creates a 'complexity tax'. This hidden cost manifests as a bloated codebase, increased bugs, and high maintenance overhead, consuming engineering capacity and crippling the ability to innovate on the core product.
When teams constantly struggle with prioritization, the root cause isn't poor backlog management. It's a failure of upstream strategic filters like market segmentation, pricing, and product discovery. Without these filters, the feature list becomes an unmanageable mess of competing demands.