Stacked Diffs / Stacked Pull Requests
Breaking a large change into a sequence of small, dependent pull requests/commits that build on each other and can be reviewed and merged in order — pioneered internally at Meta, productized by Graphite and Sapling, and (as of August 2026) natively supported by GitHub.
Also known as: stacked pull requests, stacked PRs, stacked diffs, stack (PR), Graphite, Sapling, GitHub Stacked Pull Requests
Part of: Pull Requests & Async Code Review
How authors use it
Oldest first (extraction date when no publication date is known).
| Author | Their term | Their meaning |
|---|---|---|
| GitHub Brings Stacked Pull Requests to Public Preview Craig Risi · 2026-08-18 | Stacked Pull Requests | GitHub's new native platform feature: a sequence of small, dependent pull requests, each building on the previous one, that can be reviewed and merged in order while preserving existing branch protection rules, review workflows and merge policies. |
Documents (4)
- GitHub Brings Stacked Pull Requests to Public Preview Craig Risi · 2026-08-18 source ↗ Reader 🖥️
GitHub's native stacked pull requests matter because they attack code review — not code generation — as the increasingly binding bottleneck of AI-accelerated software development, by structurally shrinking what each PR asks a reviewer to understand rather than by making review itself faster. - Does GitHub still merit "top git platform for AI-native development" status? The Pragmatic Engineer · 2026-04-03 source ↗ Reader 🖥️
GitHub's reliability has collapsed to roughly one-nine availability under AI-coding-agent load, a startup (Pierre Computer) is already demonstrating the AI-native git infrastructure GitHub lacks, and the root cause isn't primarily a scaling problem but an organizational one — GitHub has had no CEO or North Star strategy since Microsoft folded it into its AI group, leaving it chasing Copilot revenue instead of building the agent-native platform its own infrastructure crisis shows it badly needs. - Steve Yegge's Vibe Coding Manifesto: Why Claude Code Isn't It & What Comes After the IDE Latent Space · 2025-12-26 source ↗ Reader 🖥️
Chat-style coding tools like Claude Code are a transitional phase, not the destination; the real endpoint is an agent-orchestration dashboard for fleets of simultaneously-running coding agents, and the discipline this demands — reading diffs instead of code, tolerating unpredictability, and solving multi-agent merge collision — will determine which engineers and teams survive the shift to 'factory farming' of code. - Technology Radar: An opinionated guide to today's technology landscape (Volume 30) Thoughtworks (Technology Advisory Board) · 2024-04-03 source ↗ Reader 🖥️
As AI assistance shifts from an individual developer's tool to something that must be engineered at the team level, organizations need deliberate, disciplined practices (team-shared prompts and RAG-grounded knowledge over ad hoc fine-tuning, and reformed PR/CI practices to absorb AI-increased throughput) rather than either overenthusiastic LLM adoption or business-as-usual team process.
Propositions touching this concept (3)
By publication month, oldest first (extraction month when no publication date is known).
2026-04
- explicitcontestedGitHub's work on stacked diffs (started October 2025) may be largely obsolete by the time it ships, because AI agents change the review workflow the feature was designed for.
2026-08
- explicit⚡ disputed & corroboratedStacked pull requests reduce the code-review bottleneck by shrinking the scope of what each PR asks a reviewer to understand, not by making review itself faster.
- explicitNative GitHub support for stacked PRs removes the operational overhead of third-party tooling or manual branch management that previously discouraged adoption, while preserving existing branch protection rules, review workflows and merge policies.
Open gaps (4)
- incompleteYegge asserts the multi-agent merge problem is unsolved and offers only ad hoc workarounds (one-engineer-per-repo, stacked diffs, a home-grown file-reservation/messaging system) without comparing their trade-offs, or considering whether architectural decomposition (small, loosely-coupled services/modules per agent) could sidestep the problem rather than requiring a better merge tool.Steve Yegge's Vibe Coding Manifesto: Why Claude Code Isn't It & What Comes After the IDE — read next: Compare against the corpus's stacked-diffs material (extract-github-stacked-pull-requests) and team-topologies' cognitive-load/fracture-plane framework (extract-team-topologies#p12) for whether the 'wall' is a tooling gap or a team/architecture-boundary design problem in disguise.
- incompleteThe article asserts GitHub's stacked-diffs feature 'might be mostly obsolete' under AI agents without explaining the mechanism — whether agents reviewing/merging each other's work removes the human-review-scope problem stacked diffs exist to solve, or whether some other agent-specific dynamic is meant — leaving a specific, checkable claim unexamined just as it's introduced.Does GitHub still merit "top git platform for AI-native development" status? — read next: Compare against extract-github-stacked-pull-requests, which frames stacked diffs entirely around reducing human reviewer cognitive load — if AI agents increasingly do first-pass review, that premise (and the obsolescence claim) can be tested directly; see also extract-latent-space-yegge-vibe-coding-manifesto's framing of merge collision as the still-unsolved 'wall' that stacked diffs/Graphite have NOT fully solved even for human-paced review, which is in tension with calling the whole workflow obsolete.
- incompleteThe theme on dragging PRs closer to proper CI names AI-increased throughput and larger PRs as a growing strain on async review, and surveys several mitigations (gitStream, merge queues, stacked diffs, PR metrics) in the same breath — but does not analyze which of these actually addresses the AI-specific mechanism (more code per unit time) versus merely repackaging the same total review burden into more numerous smaller transactions.Technology Radar: An opinionated guide to today's technology landscape (Volume 30) — read next: Later corpus material on stacked pull requests and on DORA's AI/changelist-size findings examines this mechanism more directly.
- incompleteThe 'AI team assistants' blip offers no account of adoption barriers, measured outcomes, or how a team-shared-prompt-and-RAG approach differs in practice from a team that already had strong individual tool adoption plus good informal knowledge-sharing habits — it is reported as a promising direction from a single internal case, not evaluated.Technology Radar: An opinionated guide to today's technology landscape (Volume 30) — read next: Later Radar volumes or practitioner reports that follow up on team-level AI tooling outcomes specifically (as opposed to individual-developer AI productivity studies).