ItInsightsWorld SoftwareDevelopment Field Guide: Entire, Git, Trails, and Continuous Memory for Human-Agent Code Review
For SoftwareDevelopment teams reading ItInsightsWorld, the question is not whether a new forge announces itself loudly, but whether it improves three daily concerns: reviewing agent-generated code, keeping CI authoritative, and preserving context across sessions. Entire, presented by Thomas Dohmke, groups those concerns under three primitives: Trails, distributed Git hosting, and Continuous Memory.
From PR fatigue to Trail-based judgment
Standard pull requests place comments, CI output, and the merge action on a single linear page. As agents add longer explanations, the thread becomes more like an audit log than a human decision surface. Entire’s Trail model reverses that arrangement: eval scores sit at the top and update on every push. That score view is intended to indicate whether coding and review loops have stabilized, or whether the branch still needs another pass.
A 3-step engineering path
The review flow below compresses the concept into 3 practical steps.
- Open a Trail. The unit may begin as a bug report or feature request, or from an agent around the time code is written. It can connect multiple repositories when one change touches several codebases.
- Attach eval scores to pushes. Entire runs review agents in isolated cloud sandboxes and returns scores plus rationale. Launch examples name Security, Slop, and Human Review Required. The page keeps the current run and the last 5 runs visible. Internally, the described stack uses Claude Code and Codex on Daytona and E2B sandboxes.
- Resolve findings before the merge. Findings can appear with suggested fixes and severity levels. Unresolved items remain open; resolved items can be recalled from a menu. Gates add preconditions for approval, and may require human sign-off or CI status.
CI remains the safety line
The CI concept dates to 1991, when Grady Booch proposed it, and it later enabled teams to ship hundreds of times per day. With agents contributing more code, CI becomes a control point for unintended changes. Entire connects first-class CI to Trails through Buildkite and Depot.
Buildkite path
On Entire, CI settings can live at project level because repositories in one project may share infrastructure. After Buildkite is connected, each push builds either on Buildkite-managed or self-managed infrastructure. The check appears on the Trail and can block merges when the build fails. Agents can drive that loop through Buildkite’s API, CLI, or MCP. Existing GitHub Actions workflows can be converted with bk pipeline convert.
Depot path
Depot focuses on fast delivery infrastructure for developers and coding agents while preserving compatibility with GitHub Actions. Its Depot CI mode can execute existing workflows without using GitHub as the execution middleman. Teams can connect Depot from Entire, create the account during the flow, then use depot ci migrate to locate workflows, promote them, and flag review needs. The companion commands import secrets and variables; the billing model charges by the second.
Repository hosting, regions, and benchmarks
Before distributed version control spread widely, project history often sat on systems such as Subversion. Git shifted local work—commits, branches, and reconciliation—toward the developer. Entire argues that centralizing the server side still creates friction for scale, resilience, and storage location.
New repositories can be created natively on Entire, or mirrored from GitHub. The platform’s source-control layer pairs a distributed object store with a transactional ref database while staying Git-compatible. The launch benchmarks describe pushes up to 89x faster than GitHub and 6x faster than Cursor Origin. Another phrasing in the same benchmark shows up to 89 × faster than GitHub.
The table below records the pushes-per-second values shown in the launch benchmark.
| Forge | Pushes per second |
|---|---|
| Entire | 418 |
| Cursor | 65 |
| Pierre | 15 |
| GitLab | 10 |
| GitHub | 4.7 |
Regions currently named are US, EU, Australia, and India. Organizations may keep a repository in one region or replicate projects across several, especially when data residency matters.
Repository transition patterns
- Create natively. Use the web UI or the Entire CLI. Repositories sit inside projects belonging to an organization or personal account. At project creation, a primary region is selected, then replication can add other regions.
- Mirror while GitHub stays authoritative. Authorize the GitHub App for Entire, then choose a repository and target regions. Trails still operate above pull requests. While mirroring, push traffic goes through GitHub. During a GitHub outage, Entire can continue serving clones and fetches from its regional mirror, and agents can write to Entire-native branches using the
entire/unmirrored/prefix. - Migrate away. Migration follows two patterns. For a United States mirror, detach from GitHub in repository settings and choose the destination project. A separate direct route uses the
entire-migrateplug-in. Teams can also pull from GitHub locally or in CI/CD, then push to Entire.
Continuous Memory for agent context
Sessions produce decisions, constraints, attempted fixes, and lessons learned. When context resets, agents must relearn that information, which is slow and costly. Continuous Memory is positioned as a third kind of pipeline: CI integrates code, CD ships it, and this layer carries context forward. The repository becomes the memory an agent needs.
There are two named commands: entire-graph and entire-brain. entire-graph maps code and reportedly saved up to 71% on tokens in tests. entire-brain attaches session records to the graph so memories can be retrieved without grep.
entire-graph provides ranked code search plus definitions, callers, types, routes, and change impact with file:line references. Its parser uses tree-sitter locally, with no network request, model call, or API-key lookup.
entire-brain adds a persistent layer, so agents can access the why behind the what changed. It indexes the graph and links it to sessions recorded through Git history. In a billing rounding issue, entire-graph can trace invoice logic through callers and tests, while entire-brain can reveal prior intent, shipped fixes, and broken tests from earlier modifications. If the repository connects to the Entire backend, agent memories can live in a shared team space, and each Trail can display memories created during the work.
Common misconceptions
- A Trail is only a renamed pull request. It changes the decision surface: eval scores and findings are placed for merge confidence, not comment accumulation.
- One scoring loop is enough. The current run and the last 5 runs are exposed because repeated loops help stabilize agentic coding results.
- Regional hosting forces teams to leave GitHub. Mirroring lets GitHub remain the source of truth while Trails operate on top.
- Memory is the same as CI. CI brings code together and CD ships it; Continuous Memory preserves the context needed by agents.
Mapping the three primitives to team work
| Primitive | Engineering problem | SoftwareDevelopment action |
|---|---|---|
| Trails | Review timelines become noisy for humans and agents | Track eval scores, findings, and Gates before merge |
| Distributed Git hosting | Centralized server infrastructure limits scalability and residency control | Host in US, EU, Australia, or India, or mirror from GitHub |
| Continuous Memory | Agent sessions lose context and relearn information | Install entire-graph and entire-brain in the repository |
FAQ
Can teams keep GitHub while testing Trails?
Yes. Teams can mirror a repository by authorizing the GitHub App, then choose the repository and regions on Entire. GitHub remains the source of truth, and push traffic routes through it during mirroring.
Which CI tools are named first?
The first CI integrations named are Buildkite and Depot. Buildkite can convert GitHub Actions workflows, while Depot CI can promote existing workflows and import secrets and variables.
How is an early merge prevented?
Open findings stay visible until handled, and Gates can define conditions that must be satisfied before approval, including human approvals and passing CI checks.
Where can feedback go?
Users can report what they like or want improved through Discord, helping shape the forge with community input.
Action checklist for implementation teams
- Start one Trail from a bug or feature request and observe how Security, Slop, and Human Review Required scores change across pushes.
- Check the current run and last 5 runs before judging whether a coding-review loop is stable.
- Enable Gates when unresolved findings, human approval, or CI status should block merge.
- Connect Buildkite or Depot and test the path from push to check, including MCP-driven automation if relevant.
- Select a primary region from US, EU, Australia, or India, then decide whether to mirror, replicate, or migrate from GitHub.
- Add
entire-graphandentire-brainso future agents can use local tree-sitter maps and shared session memory.