> ## Documentation Index > Fetch the complete documentation index at: https://docs.corbits.dev/llms.txt > Use this file to discover all available pages before exploring further. # GTM Workbench > An AI-assisted, human-in-the-loop go-to-market workspace built on the Corbits agentic platform — turn sales calls, docs, and links into publishable collateral you review at every step. ## What GTM Workbench is GTM Workbench is an AI-assisted workspace where agents and workflows turn your source material — sales-call transcripts, documents, URLs — into publishable **artifacts**: case studies, one-pagers, emails, LinkedIn posts, and briefs. It is deliberately **human-in-the-loop (HITL)**. The agents handle analysis and first drafts; you curate, approve, and refine at every stage. This is intentionally not a black-box, fully automated pipeline — you stay in control of what ships. Workbench is a flagship example of what teams build on the Corbits agentic platform. We run it internally to move our own go-to-market work — so the platform primitives it depends on (identity, agent lifecycle, credentials and grants, native workflows, and skills-as-assets) are proven in production, not just documented. It's built for sales and marketing teams who want to turn call insights into usable content quickly, without waiting on a content team. ## Meet Myra, your chief of staff Every user gets a personal AI agent named **Myra**, framed as a chief of staff and executive assistant. Workbench opens into your **Inbox**, not a chat window. The Inbox is your mailbox in Workbench. Chat with Myra is its own surface, reachable from the Threads entry in Workbench's sidebar. Run multiple Myra **threads** at once. Each thread is a full agent with its own tools and history — not just a saved transcript — so you can keep separate lines of work going in parallel. Myra's durable memory is shared across all of your threads. What she learns in one chat — standing facts, context, contacts — is available in the others. Attach an image or a PDF to a message. Myra reads images directly and understands PDFs through a dedicated file parser, so documents work regardless of her underlying chat model. Myra can read a document you or a workflow saved earlier as an artifact, so prior work becomes input for the next task. ## The agent roster Myra is the agent you talk to, but she isn't working alone. A roster of specialists handles focused parts of the job (processing calls, research, writing, humanizing), and Myra brings them in as a job needs them. | Agent | What it does | | -------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- | | **Myra** | Your chief of staff: the one that coordinates the other agents. | | **Oat** | Turns call recordings into clean call-document artifacts your workflows build on. | | **Walter** | Content writer. Turns briefs and research into polished go-to-market collateral. | | **Lincoln** | LinkedIn writer. Drafts substantive, paste-ready posts grounded in call insights and field observations. | | **Hammy** | Humanizer. Rewrites AI-sounding drafts to read as human-authored, or scores how human a draft already reads. | | **Freddie & Fannie** | Deep-research agents that gather source material across the web and write it up as artifacts, tuned for depth (Freddie) and speed (Fannie). | | **Freddy** | Web-research crawler. Pulls and extracts structured content from any URL. | ## The source-to-artifact model Workbench follows one product rule: **you choose outcomes, not pipeline topology.** You bring source material, pick the outcome you want, review the decisions that matter, and approve usable artifacts. The internal steps stay hidden. That model is built from a small, consistent vocabulary: | Term | What it means | | --------------- | -------------------------------------------------------------------------------------------------------------------------------- | | **Source** | Input material you select — a transcript, a document, a URL, or a prior Artifact reused as input. | | **Offering** | The product-facing outcome you pick from a catalog or command menu, such as "Create sales collateral" or "Draft LinkedIn posts." | | **Job** | One run of a workflow against your selected sources and options. | | **Review Gate** | A human decision point — confirm sources, select findings, approve artifacts, confirm delivery. | | **Artifact** | An output produced by a Job. An Artifact can later become a Source for the next Job. | | **Package** | A curated group of artifacts you review, export, or deliver together. | | **Hook** | An optional final delivery step — copy or export, draft an email, or draft and schedule a social post. | The visible flow is short and predictable: Select the material a Job should work from — call documents, uploaded files, URLs, or an artifact from earlier work. Pick an Offering that describes what you want to produce. You select the outcome; the workflow decides how to get there. At a review gate, the Job shows you what it found and asks for the decision that matters — which findings should drive the content. Approve, reject, or request refinement on each generated artifact before it counts as done. Copy, download, or hand off approved artifacts through an optional delivery Hook. Every Job streams its progress in a single, generic run console. There is no bespoke per-workflow screen to learn — the same review surface handles confirming sources, selecting findings, and approving artifacts across every outcome. When a Job reaches a review gate, it pauses and waits for your approval before continuing. ## Integrations and tools Agents don't only write. They reach into the systems your team's work already lives in, and Myra decides which tool a task needs, pulling in more on demand. These are the providers wired today; each is a tool package, so the set grows without reworking the app. Read records, tasks, and workspace members from Attio, and add notes or update tasks, so call insights and approved copy land on the right account. Read issues, teams, users, and projects from Linear as context for the collateral you're producing, and write back to it. This is a full read/write integration: alongside creating issues, commenting, and updating documents, projects, and milestones, it can archive and delete issues and manage webhooks. Each of those writes is authorized against a grant and held for your approval before it runs, unless you have auto-approved that specific tool. Deploy an approved HTML artifact to a public Vercel URL. Publishing is irreversible, so a deploy is held for your approval in a review gate before it runs, and defaults to a preview URL. Search the web (Exa), crawl and extract structured content from any site (Firecrawl), and run read-only searches across Hacker News, GitHub, Bluesky, and creator platforms. Myra doesn't carry a fixed toolbox. Skills aren't attached up front: she searches the library and loads only the ones a thread turns out to need. Long-tail tools work the same way (the CRM and the rest stay out of her way until she pulls them in), so new skills and integrations reach her without a change to the app. Every tool call is authorized against a grant, and write tools require your approval by default. Irreversible steps like a web deploy are held for your approval before they execute. See [Credentials and guardrails](/platform/guardrails). ## Skill Library Upload, browse, and version reusable AI instruction sets — the prompts, personas, and procedures that shape how agents respond. Inspect a skill's files, review its version history, and restore any prior version. Attach a skill to an agent to change its behavior. ## Insights and analytics A **Data & Insights** surface shows how the workspace is actually being used: who is running what, which workflows produce the most, and what it costs. Token and turn usage attributed to each member, so you can see who is getting value from the workspace. Activity and token usage grouped by workflow type, so the outcomes people run most are easy to spot. Input, cache, and output tokens are kept separate and priced from open [models.dev](https://models.dev) rates, for an honest read on spend. Open any run's full trace, or scan a workspace-wide activity timeline where every entity links into its own history. ## Built on the Corbits platform Workbench doesn't reinvent the hard parts. It relies on the Corbits agentic platform for the primitives every serious agentic product needs, enabling agents and agentic workflows to seamlessly integrate into the team's day-to-day operations. The platform provisions each user's personal Myra instance and manages the lifecycle of every agent and workspace worker. Workbench doesn't build its own identity or agent-runtime layer. Inference and tool credentials are stored and resolved by the platform, and every tool call is authorized against a grant. Members never enter API keys, and access is scoped by the platform rather than a hand-rolled permission model. Workflows are deployed definitions that run on the platform's native workflow runtime — durable runs, review-gate signals, and event logs included. Adding a new workflow is a new package and a push, not a rewrite of the app. The Skill Library is backed by the platform's asset substrate, which owns storage and versioning. Workbench never reimplements how skills are stored or versioned. See the agentic platform Workbench is built on. How credentials, grants, and delivery capabilities are governed. ## Why teams use it Select your sources, pick an outcome, and get draft collateral in minutes. Every stage is human-approved. No black-box automation deciding what ships. Jobs and sessions are saved, so you can step away and come back to iterate. Approved artifacts are ready to copy, download, or deliver through a Hook.