Explore Problems

A user reports that Canva downloaded image resolution is unexpectedly poor, low enough that a screenshot would look better, and suspects the quality cap is intentionally engineered to push free users toward a paid subscription; they also note core manual editing features have gotten clunkier as AI-generated suggestions take a larger role.

Meeting participants have no real-time sense of what the meeting is actually costing based on attendee salaries, making it hard to gauge in the moment whether the meeting is worth continuing.

Asana users managing larger workspaces find the platform's advanced features and configuration options overwhelming, particularly during initial setup. The learning curve makes it difficult to keep workspaces organized until users invest significant time learning the interface. This affects teams scaling up their usage across bigger organizations.

Households with more than one person caring for a pet lack a shared record of feeding, medication, and walks, leading to duplicated or missed care tasks. This affects multi-person households and informal pet sitters who otherwise rely on memory or sticky notes to track care.

A customer reports being misled during a carrier switch when a sales representative did not disclose that an unused line would be billed monthly for 36 months. This reflects a recurring transparency gap in telecom sales disclosure practices.

Analysis of AI-generated video subtitles finds that their perceived speed problem comes from how long each line is displayed relative to reading pace, not from verbose wording - a pacing flaw in how caption-generation tools time subtitle appearance and duration.

A founder spent two years manually conducting audience research before attempting to productize the process into a business, implying that no adequate self-serve tool existed to automate the discovery of audience insights at that depth.

A builder describes an AI agent that could detect a relevant fact during its run but never wrote it down, so the knowledge was lost once the session ended. This points to a gap between what an agent perceives and what it durably records for future use.

Google Play's closed testing requirement forces solo and indie app developers to recruit at least a dozen real testers to use their app for two weeks before public release. Developers describe this as unexpectedly difficult since they lack an existing user base or community to draw testers from.

Small shop owners in Kenya face business management software that assumes training, developer help and desktop hardware. Setting up a profile, adding stock and serving customers takes long enough that many owners never adopt a system. Cost and phone-only operation are the binding constraints for this segment.

Builders of real-time global chat products face a classic cold-start challenge: new users who join a room find it empty, which kills engagement and retention before a critical mass of participants is reached. This is a structural problem for any community or chat product before it reaches scale.

Most AI tools in video calls act only as silent notetakers, while users want an assistant that actively looks things up during the call, helps build documents in real time, and catches action items others missed. This reflects a structural gap between passive transcription tools and active in-meeting assistance.

Merchants and developers building on Shopify hit API rate limits when syncing large volumes of data, and maintaining complex Liquid templating logic in legacy themes becomes tedious over time. This affects developers managing custom Shopify integrations and theme customizations.

A small business is hiring an entry-level worker at $3 to $5 an hour to manually search for school coaches' names and emails and fill them into a lead-generation spreadsheet, revealing a gap in affordable automated data enrichment for niche B2B outreach lists.

Healthcare practices must track and complete initial and ongoing provider credentialing across numerous disconnected systems (CAQH, NPPES, PECOS, Availity) and payers (Medicare, Medicaid, HMOs, commercial insurers), each with its own requirements and renewal timelines. This recurring, expertise-heavy work is currently outsourced to a dedicated hourly specialist rather than handled by unified software.

People who make consequential calls, founders, parents, planners, investors, have no easy way to log what they predicted and how confident they were before an outcome resolves; by the time the result is known, hindsight has rewritten the memory of the original uncertainty, making it impossible to later see where their judgment was actually sharp or overconfident.

A customer needed a chandelier installed at a tall ceiling height, but two different contractors dispatched through the marketplace each arrived with only a 10-foot ladder when 15 feet was needed, despite the requirement being communicated in advance. After repeated failed visits and lost work time, the customer returned the fixture for a refund but was still charged $250 for an installation that never happened.

GEICO's DriveEasy telematics app reportedly misidentifies driving as walking and flags routine downhill braking as hard braking, using force thresholds far below what the driver's own in-vehicle accelerometer registers as normal. Since these readings feed directly into insurance discount eligibility and premiums, inaccurate sensor interpretation can unfairly penalize safe drivers.

A long-time customer with a clean driving record and full coverage on a $90,000 truck disputes State Farm's total-loss settlement following a six-car pileup, describing the payout as far below what the vehicle was worth despite maximum coverage.

Developers running many concurrent Claude/Codex sessions for both engineering and go-to-market work struggle to keep track of what's finished, what's abandoned, and how to get back into old sessions. The best current workaround is asking the assistant itself to search for a past conversation, which is unreliable and unstructured. This points to a missing session-management layer for people who work across many parallel AI agent threads.