When it comes to ai tools, chatbots are usually the first thing that comes to mind: conversation-based interfaces for users to type queries and receive responses. These dialog interfaces are certainly useful, but they are not always the most suitable for handling our daily work. Chatbots, often included outside our workflows, complement our processes, but often also add a lot of friction.
The next wave of ai tools is bringing autonomous actions to our daily work. Today, we're excited to introduce you to Height.app, a standalone project management tool that takes work away from you instead of adding work to it. Height uses real-time context of your team's interactions and workspace data to handle tedious tasks on your behalf, like triaging bugs, updating specifications, cleaning up your backlog, and more.
Height has a set of LLM-based features for all the time-consuming project management scripts we handle on a day-to-day basis. Let's review some below:
1. Real-time edits of product documentation.
As you build a feature, product documentation rarely stays the same. New ideas emerge, obstacles emerge, and scope is inevitably redefined. Accounting for each of those specification changes is notoriously tedious, especially on fast-moving projects. Height analyzes these situations in a granular way, treating each message, whether an idea or a blocker, as an event, and those events as contextual information about how an LLM should act.
By analyzing your team's project conversations as they unfold within the app, Height can discern when your team raises questions and decisions are made. It then maps those identified results to your product documentation, adding necessary context and updates without you having to lift a finger.
2. Autonomous cleaning of backlog
Staying on top of a pending job seems like a never-ending task. Tickets are often created without anyone else knowing and the appropriate tags are rarely applied consistently. But within each submitted ticket there is contextual data, such as name, description, and chat messages, which an LLM can use to infer the feature referenced within the ticket and what completing it may entail.
Height recognizes when tickets are added to the backlog and then uses contextual data from each ticket to apply the appropriate tags on its behalf. From feature tags to time estimates and even impact types, Height proactively keeps your backlog organized, making it easy for you to find the improvements and requests worth pursuing next.
3. Live project updates
Whether you're creating a new feature or updating your website, keeping track of completed tasks and open questions requires overwhelming mental effort. But for large, collaborative initiatives, it's especially important to keep everyone aligned on what's progressing and what's blocked. Conveniently, most of the project information you need to track (status changes, discussions between teammates, and blocked tasks) is contextual data that LLMs can analyze and understand in an instant.
Height processes all the data from this project to create a periodic and timed report of how the project is progressing and what remains to be worked on. Instead of manually sifting through activity to write your own updates, Height provides a detailed summary of what happened, tasks in progress, and what remains to accomplish (as well as any flagged blockers).
Height's core philosophy is that ai should reduce friction, rather than adding layers of complexity. With an intentional focus on making project data accessible to LLMs, Height is going beyond traditional chatbot implementations, focusing instead on real-time context processing to drive intelligent automation. The result is a tool that handles all the frustrating pain points of project management, so you can focus on building.
Asif Razzaq is the CEO of Marktechpost Media Inc.. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of artificial intelligence for social good. Their most recent endeavor is the launch of an ai media platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is technically sound and easily understandable to a wide audience. The platform has more than 2 million monthly visits, which illustrates its popularity among the public.
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