/Tech54m ago

Ryan Hoover says querying Claude has replaced his custom analytics dashboards, sparking debate with Gokul Rajaram on data consistency

Story Overview

Ryan Hoover noticed his custom analytics dashboard gathering dust while direct questions to Claude delivered fresher insights on demand. The Product Hunt founder described feeding the AI context and goals instead of rigid instructions, letting it pull data, run analysis, and spin up temporary views. Investor Gokul Rajaram stepped in to note that such bespoke queries can still trip over inconsistent interpretations even when the raw numbers sit in the same place.

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Original post

Gokul Rajaram@gokulr#1176inTech

Great points by @ryancarson about dashboards not being as necessary as they used to be. I agree with Ryan’s POV but would offer two caveats (the classic “yes, and”)

1. Dashboards still have a place - for things you want to look at consistently and distribute widely.

2. The corollary to #1 above is that doing everything bespoke is costly and also more likely to be misinterpreted.

Ryan Carson@ryancarson

Every time you think you need a dashboard to look at data, stop yourself.

Do this instead:

1. Ask your agent to make sure that you have all the data to analyze something actually stored in the database.

2. Ask your agent to write a skill to gather that data.

3. Ask your agent to do the analysis and create a temp and throw-away HTML dashboard to answer the question(s) that you have

In my experience, every dashboard that I've created gets less and less use over time and decays.

It's much better to make sure your agent can get the data you need and answer the questions you have, on-demand.

6:17 AM · Jun 30, 2026 · 1.1K Views

Open Question

When recurring needs favor the old format

Rajaram points out that dashboards keep their edge for repeated team check-ins and broad distribution without each person crafting a fresh prompt. Hoover's experience shows the dashboard route went unused, yet the investor cautions that fully agent-driven flows leave room for subtle data misreads that a fixed view would surface every time.

Developer Impact

Prompting like a data teammate

The shift Hoover describes treats Claude more like a skilled analyst than a button-click tool: supply background and objectives, then iterate on what comes back. Research notes confirm Claude can generate interactive charts or throwaway HTML dashboards from uploads, though no public benchmarks yet track how often those outputs match the consistency of pre-built BI views across teams.

Sentiment

Users favor AI agents over static dashboards for data insights because the approach adds discipline by focusing analysis only on consistently important questions.

Pos

100.0%

Neg

0.0%

1 comments with sentiment.

Cluster Engagement

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Ryan Hoover@rrhoover

I recently built an analytics dashboard for a project I'm working on. I rarely use it.

Asking Claude questions has led to more insights. But the key is to ensure it has the context and understands the goal.

This underlines a mindset shift in how to talk to computers.

The old way: Be very prescriptive and thorough with instructions.

The new way: Provide context and state the goal clearly as if you were speaking to a skilled engineer/data scientist/etc.

Ryan Carson@ryancarson

Every time you think you need a dashboard to look at data, stop yourself.

Do this instead:

1. Ask your agent to make sure that you have all the data to analyze something actually stored in the database.

2. Ask your agent to write a skill to gather that data.

3. Ask your agent to do the analysis and create a temp and throw-away HTML dashboard to answer the question(s) that you have

In my experience, every dashboard that I've created gets less and less use over time and decays.

It's much better to make sure your agent can get the data you need and answer the questions you have, on-demand.

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Ryan Carson@ryancarson

@rrhoover It also introduces discipline in your analysis. If you're not asking a question consistently, then it probably isn't an important question and definitely doesn't deserve a dashboard. win win :)

23m861

Sheldon@Sheldonbishop01

@gokulr @ryancarson Somewhat in between your two points. Dashboards are a good way to remind everyone what is important.

To add another, "yes, and"

51m171

waqas@vixsheikh

Analytics dashboards feels like a perfect use-case where more just-in-time, ephemeral solutions can be valuable. Lots of dashboards today, similar to design prototypes, are intended to solve for temporal needs of understanding or alignment. But the infra and effort that goes into them is more commensurate with evergreen, foundational tooling - which can be overkill.

So as with most things, the use-case really matters i.e. "yes, and" :)

44m81

Mark Cornwell@mrcornwell

@rrhoover Stating the goal clearly and asking Claude to validate its understanding before it executes can be the difference between getting what you want and not.

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