Glean
Glean is an AI-powered enterprise search platform that indexes content across workplace apps and tools for employees.
About this data
Updated June 29, 2026
Overall Pulse Score
-5 over this period
A 0-100 index summarizing the tone of 7 relevant public mentions gathered from public online communities across 5 weeks in the selected period. It measures online sentiment, not a rating of the product's quality.
Weekly Sentiment Trend
Pulse Score by week over the selected period. Each point is one complete week of mentions.
This week in public discussion
Recent discussion around Glean leaned negative, with bug reports making up the bulk of mentions over the past several weeks. Commenters flagged specific technical issues including a CLI hostname misconfiguration causing 401 errors, a silent data-dropping bug in the SDK, and repeated tool listings in the CLI output. A smaller number of mentions praised integrations and security features, but the complaint volume around reliability and missing documentation left the overall tone frustrated.
Read the deeper analysisAI-generated summary of public online discussion during this period. It reflects the tone of that discussion, not facts about the product or our views.
Sentiment mix by week
How the tone of public discussion splits each week.
Most-discussed praise
Most-discussed complaints
Themes across the selected period, with mention counts.
How Glean compares
Pulse Score over the selected period versus the top tracked competitors in Software.
Where the mentions come from
Share of the 7 relevant public mentions in the selected period, by source.
Sample public mentions
Showing 5 of 7 analyzed public mentions in this period, with links to the original source. We do not reproduce full threads.
“Investigate glean over-exploration on small codebases. Problem On small codebases (gin, simple rg tasks), glean consistently adds overhead without benefit: - gin_binding_tag: +61% ctx, +65% cost (baseline: 5 turns, glean: 7 turns) - gin_context_next: +55% ctx, +42% cost - rg_flag...”
“[databricks-iceberg] Skill should be recommending Iceberg V3. ## Category - [ ] Pattern not detected (the skill missed a classic-compute construct) - [x] Wrong fix suggested (the fix didn't work or was incorrect) - [ ] Migration succeeded but output differs (code runs, data is di...”
“GLEAN_HOST with custom backend URL gets "-be.glean.com" incorrectly appended, causing 401 errors. ## Bug When GLEAN_HOST is set to a full hostname that doesn't end in -be.glean.com (e.g. acmecorp-pl.glean.com), the CLI strips everything after the first dot and appends -be.glean.c...”
“Value model in AdditionalFieldDefinition is an empty class, thus silently drops all data. The Value class in additionalfielddefinition.py is defined as an empty Pydantic BaseModel with no fields: Because the SDK's BaseModel uses the default Pydantic extra = 'ignore' behavior, any...”
“glean tools list repeats the same tools several times. ❯ glean tools list { "tools": [ { "type": "READ", "name": "Gmail Search", "displayName": "Gmail Search", "description": "Searches Gmail inbox (Google Workspace) for emails, conversations, and attachments.\n\nUse for:\n- Findi...”
Deeper analysis
- Bug reports and reliability concerns dominated discussion, with commenters filing detailed, reproducible technical complaints far more often than praise.
- Sentiment trended sharply downward through early-to-mid 2026 before recovering in the most recent weeks, though the rebound follows a prolonged low period.
- Opinion on integration quality was split, with isolated praise contrasting against multiple accounts of broken behavior in specific configurations.
- Discussion volume was very low across the window, meaning sentiment readings are sensitive to individual mentions and should be interpreted with caution.
| Praise theme | Mentions |
|---|---|
| Strong features | 1 |
| Good integrations | 1 |
| Security praise | 1 |
| Complaint theme | Mentions |
|---|---|
| Bugs | 4 |
| Missing features | 2 |
| Reliability | 2 |
| Performance | 1 |
| Feels slow | 1 |
Public discussion of Glean over the recent multi-week window was dominated by frustration, with complaint-oriented mentions far outweighing praise. Commenters surfaced a cluster of technical grievances centered on bugs and reliability, and the volume of specific, reproducible issue reports gave the overall tone a weary, developer-facing quality rather than casual dissatisfaction. Several mentions described broken or incorrect behavior in core workflows, including a CLI environment variable that incorrectly appended backend suffixes and caused authentication failures, a data model silently dropping fields due to an empty class definition, and a tools-listing command that repeated entries. These were not vague complaints but detailed bug reports, which discussion suggested reflects a technically engaged user base running into friction at integration depth.
A secondary thread of concern involved documentation gaps, with at least one commenter noting that setup guides appeared written around a specific agent host and left users of alternative configurations without clear guidance. This fed into a broader sense among some commenters that the product assumes a narrower usage context than its actual deployment spread.
Praise was sparse but present, with individual mentions touching on a specific feature, integration quality, and security, suggesting pockets of genuine satisfaction that did not translate into volume.
The score trajectory tells a story of volatility rather than steady improvement or decline. After a period of low sentiment, scores climbed sharply in mid-2025 before retreating, then dropped further into early-to-mid 2026, bottoming in late April before recovering noticeably in the most recent two data points. The current window ends on an upswing, but the recovery sits against a backdrop of recent lows, and the mention counts remain thin enough that single posts can swing readings significantly.
Opinion was most divided around integration quality, where one commenter offered praise while others described specific breakdowns, suggesting experience may vary considerably by configuration or use case.
AI-generated summary of public online discussion during this period. It reflects the tone of that discussion, not facts about the product or our views.
Member perspectives
Individual opinions from Pro members, posted over time. These are personal member views, not aggregated sentiment data.
Overall Pulse Score
-5 over this period
A 0-100 index summarizing the tone of 7 relevant public mentions gathered from public online communities across 5 weeks in the selected period. It measures online sentiment, not a rating of the product's quality.
Data summary
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