Agentic Index
Agentic AI Platform Change Log
Agentic Index tracks material changes across agentic AI platforms, including new agent capabilities, workflow orchestration updates, integrations, MCP/tool-calling changes, memory features, human approval controls, observability, deployment options, pricing, funding, and verification-status updates. This change log is the index that tracks changes to agentic AI platforms, updated weekly. If you are trying to keep up with changes to AI agent platforms without reading every vendor's release notes separately, this is the feed to read.
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Public-source research. All entries are sourced from official vendor blogs, changelogs, documentation, or press materials. Support levels marked Needs Review or Publicly Claimed should be independently verified before relying on them for procurement decisions.
9 entries matching filters
Human approval / guardrails
Agentic Batch Changes now honors administrator defined context filters that make matched repositories and file paths invisible to its agents. The coordination agent cannot search or read excluded content, workspaces in excluded repositories are not run, and publishing from an excluded repository is refused, with the same rules applying to Deep Search.
Security and platform teams can keep secrets, production config or restricted repositories out of reach of an autonomous code change agent that works across many repositories.
Agent capability
Agentic Batch Changes now runs its coding steps on a Sourcegraph managed coding agent instead of Codex and Claude Code. The new agent brings MCP and its own Finder, Oracle and Worker subagents, and existing batch specs keep working.
Teams running large code migrations no longer depend on separately configured third party agents inside batch steps, with no rewrite cost for existing specs.
MCP / tool calling / API
Sourcegraph Cloud updated Code Finder to accept the repository as a separate parameter and expanded read_live_changesets so Agentic Batch Changes can inspect live CI checks and branch state before requesting help. The same release adds structured publish credential problems to prepare_batch_spec metadata and enables repository fetch history logs. Deep Search gains safe date functions for analyzing commit activity and time windows.
Teams integrating code agents should review tool argument handling and can give agents more evidence before escalating failed changes to an engineer. Repository fetch history also helps administrators diagnose whether stale source data affected an investigation.
Pricing / packaging
Sourcegraph introduced outcome based pricing for Agentic Batch Changes: customers pay per changeset successfully merged, not for compute or seats.
Paying only for merged changes puts the risk of wasted agent work on the vendor. It is one of the first outcome priced coding agents, and it gives buyers a clean way to measure value.
Workflow orchestration
Sourcegraph made Agentic Batch Changes generally available. The agent plans, generates and executes large code changes across many repositories at once.
Changes across hundreds of repositories are where coding agents save the most time and can do the most damage. Review workflow and rollback are the questions to ask.
Security / enterprise
Sourcegraph is reinforcing technical safeguards to strictly enforce geographic access restrictions across its products. This update aligns access controls with applicable laws and the requirements of underlying AI model providers.
Enterprise buyers must ensure their distributed engineering teams operate within supported regions to avoid access disruptions. This change helps organizations maintain compliance with international data and AI usage regulations.
MCP / tool calling / API
Sourcegraph released Code Finder in Beta through its Model Context Protocol (MCP) server, an agentic tool that helps AI coding agents rapidly locate relevant files and documentation within single repositories. Additionally, Sourcegraph made its redesigned Compare page generally available, introducing a file tree view and full code navigation for analyzing complex diffs.
Code Finder makes automated agent workflows faster and cheaper by minimizing the context window consumed during codebase discovery. Meanwhile, the upgraded Compare page provides essential oversight tooling for engineering teams to effectively review the massive, multi-file code changes generated by these agents.
Agent capability
Sourcegraph launched Agentic Batch Changes in public beta: an agent harness for applying code changes across thousands of repositories or the largest monorepos. Built on Batch Changes and Deep Search, the agent plans a change, chooses between writing deterministic scripts or delegating per-repo work to Claude Code or Codex, executes across all targets, and reacts to downstream events like CI failures and merge conflicts until changes are ready to merge. Beta access is by request.
Large-scale migrations, security patching, and breaking-change upgrades are among the most expensive maintenance work in big codebases. Orchestrating a single coding agent's capability across every repository at once, with human review checkpoints and CI feedback loops, is a distinct capability tier from single-repo coding agents.
Security / enterprise
Sourcegraph added granular admin permissions via RBAC, allowing teams to delegate specific admin capabilities without granting full administrator access.
Granular RBAC is a foundational enterprise governance requirement — directly relevant for large teams and regulated industries where least-privilege access is a procurement criterion.
Current rankings
These changes feed the index. See where each category stands: the best vendors of 2026, ranked by verified capability coverage.
Capability coverage
Every change above is graded against the same 14 capability axes. Each axis has its own page showing how much of the index documents it, which categories concentrate it, and the leading platform in each.
The AI agent directory for business · The full feature taxonomy · Pricing research
Common questions
How do I keep up with changes to AI agent platforms?
Read one maintained change log instead of tracking each vendor's release notes separately. The Agentic Index change log records 1648 verified updates across agentic AI platforms, updated weekly, covering new agent capabilities, MCP and tool calling changes, memory, human approval controls, observability, deployment options, pricing and funding. Every entry names the vendor, the date, the change type and an impact level, and links to that vendor's profile.
How often is the agentic AI change log updated?
Weekly. The most recent update was Oct 21, 2026, covering Equal AI, Kognitos, Findem.
How do I track changes for one specific AI agent vendor?
Filter the change log by vendor, or open that vendor's profile page, where the same verified entries appear alongside its capability coverage across the 14 point Agentic Index taxonomy.
Where can I find a single feed of agentic AI platform updates?
This page is that feed. Agentic Index reviews vendor blogs, changelogs, documentation and press materials every week and files what materially changed, so keeping up with changes to AI agent platforms is one page rather than several hundred. Entries are filterable by vendor, change type, impact level and verification status, and each one carries the evidence basis it was graded from. The same entries are published as a free RSS feed at agenticindex.io/feeds/changes.xml, with one feed per ranking category listed at agenticindex.io/use-this-data.
Last updated: Oct 21, 2026 · 1648 tracked changes across 550 vendors