Productivity · How-To

How to Actually Get Real Answers Out of Glean (Not Just Prettier Search Results)

Your company paid $45 a seat for a Work AI platform, and half your team is using it like a fancy search bar. Six habits that turn Glean from a link finder into an actual coworker.

By Lena Falk · Analyst, Productivity & Search · July 1, 2026

Here's the thing about Glean nobody tells you on day one: if you use it like Google, you get a better Google. Which is fine. But you paid enterprise money, reportedly around $45 to $50 per user per month with a 100-seat minimum, for something a lot more capable than "search across Slack and Confluence at once."

The 2026 version of Glean is a different animal from the one most orgs rolled out two years ago. Third-generation Assistant, an Enterprise Graph underneath it, Skills that codify repeatable workflows, Canvas for collaborative drafting, agent sandboxes for long-running analysis, and an Agent Builder that lets any employee spin up a task-specific coworker in natural language. Almost none of that shows up if you just type a question in the search box and hit enter.

I've spent the last few months watching teams use Glean well and use it badly, and the delta between the two isn't about prompt engineering. Glean specifically doesn't want you doing that anymore. It's about knowing which surface to reach for, and trusting the graph to do the work you used to do by hand. These six habits are the ones that consistently separate the people getting real leverage from the people who are still, essentially, searching.

1. Stop prompt-engineering. Describe the outcome you want.

This is the habit shift that unlocks everything else, and it’s the one people trained on ChatGPT resist the hardest.

Glean’s third-generation Assistant was explicitly designed to kill the multi-paragraph prompt. Glean unveiled the third-generation Assistant capable of deeply personalizing results and accomplishing complex agentic tasks without advanced prompt engineering. That’s not marketing fluff, it’s a design bet. Tasks that used to require multi-paragraph prompts or complex agent creation now just happen in Assistant. Users can simply describe the outcome they want and get the result, freeing users from the fatigue of having to create and iterate the perfect prompt.

Translation: stop writing “You are an expert analyst. Given the following context, please…” Just tell it what you want. “Draft a Q3 review deck for the growth team using the same structure as last quarter’s.” “Find every open Jira ticket blocking the Atlas launch and group them by owner.” That’s the whole prompt. If Glean doesn’t have enough context, it’ll ask. When Glean Assistant realizes that it does not have the proper context or cannot answer requests correctly, it evaluates its own response for completeness and accuracy and comes back with a clarifying question rather than a confidently wrong answer.

The people getting the least out of Glean are the ones still writing prompts like it’s GPT-4 in 2023. Cut it out. Talk to it like a new hire who already read your company wiki.

2. Use Assistant for research, Agents for repeatable work, and know which one you’re in

This is the single most common category error I see. People try to make Assistant do the same job twice a week by copy-pasting the same prompt. That’s what Agents are for.

The mental model Glean itself pushes is medical: the difference rests with the assignment. Assistant is like a general physician whom you would go to first to receive a diagnosis, and if that doctor orders blood tests or specialized examinations, that new healthcare professional would be the equivalent of an agent. Assistant is your first stop for an ad-hoc question or a one-off task. Agents are what you build when you catch yourself doing the same thing on Mondays.

The good news: you don’t need to be an engineer to build one. Glean Agents empowers everyone to create, use, and manage AI agents using natural language. Describe the job, point it at the connectors and actions it needs, and you’ve got a coworker that runs on a schedule or a trigger. Standing weekly competitive-intel roundup? Agent. New-hire onboarding checklist that pulls from HR, IT, and your team wiki? Agent. Anything you’d otherwise dread doing on a recurring calendar invite? Agent.

Rule of thumb: if you’re going to ask the same question a third time, you should have built an agent the second time.

3. Codify your workflow as a Skill instead of retyping it

Skills are the feature most Glean users don’t know exists, and they’re the one that turns Assistant from “smart search” into “actual leverage.”

You can now execute repetitive tasks faster and more precisely with Skills. Skills in Glean are personalized packages of reusable execution logic. Instead of trying to manually recreate the same workflow, Skills give Glean the instructions, structure, and tools to deliver consistent, higher-quality results calibrated to how you, your team, and your work.

Think of a Skill as the halfway point between a saved prompt and a full agent. It’s the “here’s how I like my weekly status memo formatted, here are the sources I want it drawn from, here’s the tone” bundle. Once. Then you just say “run my status memo” and it’s done, in your voice.

The killer detail is the personalization: whereas other skill builders require you to explicitly define your style and ways of working, Glean can generate skills more easily because it already understands how you operate. You don’t have to describe your writing style, it’s already read a year of your docs, Slack messages, and comment threads. It knows how you write. Let it use that.

If you’re a manager, build Skills for the four or five artifacts you produce every week. That’s a couple of hours of setup and it pays for itself in a fortnight.

4. Push heavy analysis into the agent sandbox, don’t paste giant spreadsheets into chat

If you’ve ever tried to get an assistant to reason across a 40MB CSV, you know how that goes. Truncation, hallucinations, “here are the first ten rows and a summary that’s structurally wrong.”

Glean quietly shipped a fix for this and it’s underused. Glean added a new, secure, lightweight virtual development environment equipped with a Command Line Interface, a code interpreter, a filesystem, and a tool index. This sandbox lets Glean Assistant analyze large datasets and run long-running tasks without being constrained by LLM context window limitations, while respecting enterprise permissions.

That’s a real code interpreter with real disk, wired into your permissions layer. When you’re asking Glean to do actual analysis, reconcile two exports, roll up a quarter’s worth of support tickets, diff two versions of a policy doc, you want it to route into the sandbox, not stuff everything into a chat window. Ask explicitly: “run this in the sandbox,” or hand it a file and describe an analysis task, and it’ll pick the right execution path.

The tell that you’re doing it wrong: your answers keep starting with “based on a sample of the data.” Stop sampling. Sandbox.

5. Draft in Canvas, not in chat, and let the Assistant edit alongside you

The chat window is fine for questions. It’s a bad place to write anything longer than a paragraph. Every revision buries the previous version, you lose track of what changed, and copy-pasting a draft into Docs breaks the loop with your source material.

Canvas fixes this. Glean Canvas, the feature for drafting, iterating, and refining written content, now lets employees work together with the Glean Assistant. Think of it as a shared document where the Assistant is the co-author sitting next to you. You write, it suggests, you accept or reject, and the citations to source documents stay live in the margin the whole time.

For anything longer than a Slack message (a memo, a spec, a briefing doc, a customer response) start in Canvas. You’ll get transparent revision review instead of a chat scrollback, and the finished artifact lives somewhere your teammates can find later. Glean’s May 2026 launch put a real emphasis on this: effective AI collaboration must fit how people actually work, with voice conversations, transparent revision review in Canvas, and a shared Library that preserves AI-generated outputs so teams can iterate faster, retain oversight, and compound institutional knowledge over time.

That Library point is the sleeper. Every good Canvas draft becomes a reference for the next one, and for the next person. Use it.

6. Curate your Personal Graph like it’s your résumé

Here’s the part almost nobody touches, and it’s the reason two people at the same company get wildly different results from the same prompt.

Glean Assistant is now more personalized for the worker, allowing them to view, edit, and delete personal graph details that reflect their role, projects, goals, and preferences. The Personal Graph is what Glean thinks it knows about you: the projects you’re on, the teams you work with, the docs you’re the go-to person for, the meetings you actually care about.

If you never look at it, Glean is guessing. It’s a good guess, but a guess. If you spend ten minutes correcting it (“I moved off the Atlas project in April,” “I’m not the DRI for pricing anymore, that’s Sam,” “these three docs are the source of truth for my team’s OKRs”) every answer you get for the next quarter gets sharper. Priority ranking, “what should I care about today,” proactive nudges, meeting prep, all of it rides on this graph.

The whole platform runs on it. Though invisible to users, the Enterprise Graph powers every experience in Glean, from personalization to agentic execution, and is what makes Glean’s AI truly enterprise-ready, delivering the context, structure, and nuance needed to achieve meaningful outcomes with AI. The Personal Graph is your slice of that. Curate it or accept the guess.

A bonus, because it matters: trust the citations, then verify one

Glean’s answers come with source links. Every claim, every summary, every recommendation traces back to a document, a ticket, a message, a meeting. That’s not decoration. Queries run against the graph, not against a flat vector store, which is why Glean’s answers are cited, traceable, and safe to expose inside a regulated enterprise.

Use them. Not for every answer, that defeats the point, but for the ones you’re about to act on. Click through on the citation behind “the pricing team decided X in April.” Confirm it says what Glean says it says. This does two things: it catches the occasional stale doc masquerading as current truth, and it teaches you which parts of your corpus Glean is drawing from, so you can spot the gaps.

The permissions story is the other reason to trust it more than a general-purpose chatbot: documents you cannot access never enter the prompt, so the model cannot leak them in the answer. You won’t accidentally surface something you weren’t supposed to see, and you won’t accidentally leak something in an answer a teammate reads later.

The one habit that ties it all together: stop treating Glean like a search box with better vibes. It’s a platform (Search, Assistant, Agents, Skills, Canvas, the Personal Graph, the sandbox) and each surface is designed to do a specific job better than the surface next to it. The people getting real leverage aren’t power users in some magical sense; they’ve just figured out which door to walk through for which task. Learn the six doors above and Glean stops being an expensive search bar and starts earning its seat price. Skip them, and you might as well be back on Ctrl-F.