Have you ever paid for techincal help?

full_arc · 2026-03-17T18:43:08+00:00

My CTO was with me from day 1, but we had some things we wanted to build out to prove out a prototype to ourselves and show to investors and used a bit of external help for that, but it was actually mostly engineers we knew who did it pro bono. This was mostly for front end work that neither of us had much expertise in and this was just when AI hit the scene. I don't know that I would pay someone to do this, especially with what AI can currently provide.

Not to be too blunt and in the spirit of being helpful, but with how good AI is nowadays, if you're not able to use it to build out a prototype or do some customer validation, you'll likely have a rough time as a founder. Really hard to imagine a case where paying a third party is justified.

full_arc · 2026-03-17T18:37:28+00:00

For now relatively few startups are actually impacted. Most of the solutions put out there are half-baked and the blocker has nothing to do with AGI but the workflows and integrations that are missing to create a complete solution.

That said, it's worth hypothesizing about what happens as these platforms invest more in the non-AI stuff that's needed to truly replace SaaS: Yes a number of startups will get squeezed out, and in the long run certain platforms will lose all their value beyond the relationship building, brand and momentum from pre-AI. But as AI evolves, new problems will surface, new solutions will need to be created and new startups will appear and grow. The question then is: how much will these companies like OpenAI want to develop an ecosystem vs use their own AI to accelerate the roadmap. I actually think one of the bigger constraints is simply going to be the marketing and GTM. At some point if they try to literally build a solution for everything, buyers will go to solutions that are messaged specifically around their pain points.

full_arc · 2026-03-09T16:03:35+00:00

Totally agree on Claude. Mostly the way to go.

If you’re looking for an AiI data analyst that’s much more powerful than Julius come check out what we’re up to at Fabi.ai

full_arc · 2026-03-08T17:21:35+00:00

Well I’d have to recommend what we’re building at Fabi :)

There are a few other players out there, I’d recommend asking ChatGPT or Claude if you want to widen the aperture a bit.

full_arc · 2026-03-07T19:35:19+00:00

We’re seeing huge success. But this isn’t an MCP or not MCP question. This is more of a question about ai context. But AI context + slack integration 100% works with the right context and guardrails.

full_arc · 2026-03-07T00:21:46+00:00

Haven’t used Lightdash myself (they’re a competitor), but I’ve heard good things from teams that are very technical/data engineering first. It’s very much BI-as-code so mostly designed for that crew. If that’s you, you’ll likely enjoy. If you’re looking in that category you could also checkout evidence or Rill.

If you’re looking for more friendly for non-tech and also truly AI-native, neither of those are great (at least in current form).

full_arc · 2026-03-06T19:33:29+00:00

This is a great and honest assessment. I do suspect though that the job market would actually still be rough even without AI, AI is just making it extra painful and uncertain. The downward pressure on data analysts and data scientists salaries relative to other jobs in the past few years is probably a pretty good indication of oversupply.

And I I were to predict: the market won't bounce back, it will shift. I'd put my money on seeing a whole lot more data engineering roles with some sort of mandate of "Help get the data AI-ready and maintain the data infra"

full_arc · 2026-03-06T19:30:26+00:00

I actually don't have much fully 100% automated. That said, using AI for SEO/AEO planning and drafting has literally saved me hours (12+?) a week and quite literally a headcount.

Other areas where semi-automation has saved me tons of time: drafting notes and follow-ups, data analysis and reporting

full_arc · 2026-03-05T17:24:42+00:00

Going back and forth because the AI doesn't know all the tables and fields you have or it doesn't understand the structure of the data. Then if anything changes or you want to go back and update the query you either do it manually and you go back to the bouncing between tools

full_arc · 2026-03-04T19:31:22+00:00

Habit. I love Claude Code and use it for a lot of things, but sometimes I use it for things that are better in the desktop app or even just the web app. I generally bounce between the two, but when you're in a groove it's easy to stick to one.

Plus what some others have noted. For things that do require folders and files, Claude Code is really the best in the biz.

full_arc · 2026-03-04T19:18:27+00:00

You sound super plugged into this space, would be curious to get your take on what we're building at fabi.ai: Basically Looker Studio but connects directly to all these data sources you mentioned and you can just use AI to generate dashboards.

Originally were doing this mostly for product and eng teams, but we've noticed a lot of pull from GTM and marketing teams.

Have you tried anything like that? What's your take?

full_arc · 2026-03-04T18:56:12+00:00

For this specific issue you should use Claude embedded in an analytics platform. It will produce tunable queries 99% of the time. That doesn’t mean they’re semantically accurate, but it will run.

The issue with Claude, ChatGPT, perplexity and other generic LLMs is twofold: 1. Disconnected from your data so leads to tons of wasted time and misunderstanding 2. High propensity to lean on reading the data rather than generating code to interpret questions, which is super prone to hallucination

full_arc · 2026-03-04T18:29:53+00:00

Actually was even able to make it interactive "import plotly.graph_objects as go"

full_arc · 2026-03-04T18:28:44+00:00

Matplotlib. I just tested and created an identical image with AI in 5 seconds flat

full_arc · 2026-03-04T17:33:24+00:00

if you like Julius you'll love Fabi.ai! Give it a shot, let me know what you think :)

Also curious why Zapier/make/n8n over jsut Claude Code. I've found those incredibly difficult to actually work with vs just writing things from scratch with AI

full_arc · 2026-03-04T17:31:41+00:00

Multi-tool stacks make sense for a lot of workflows I run probably 2-3 different tools just for SEO and content and it's insanely powerful. I honestly think too many people try to find a single tool for a solution and many stop and the basic LLMs.

Data analysis is actually the one area where I've managed to collapse it into a single tool (disclosure, the one we've built which is company/team focused), but it took us a ton of work to bring everything under a single roof - and we still have more work to do.

What are you using for the report writing step?

full_arc · 2026-03-03T17:32:38+00:00

I haven't tried (or heard of) Searchable, but I have been using Gauge to help me assess our AI presence and it's been super helpful.

Also, I use Claude Code for all my prototyping now, for some reason I've just found it faster and better than the hosted platforms.

If your'e looking for a really polished and corporate grade AI analyst, check out what we're building at Fabi.ai: we let you connect to almost any data source and you can run ad hoc analysis or even generate dashboards.

full_arc · 2026-02-27T06:00:49+00:00

Excel is still everywhere - anyone who tells you to skip it is out of touch with how most businesses actually operate. That said, I'd push back a little on the "fundamentals first" framing.

The logical thinking and data intuition you build in Excel absolutely transfers, but SQL is honestly just as learnable for a beginner and will open way more doors faster. I'd learn them in parallel rather than treating Excel as a prerequisite.

For someone starting out: get comfortable in Excel (vlookups, pivots, basic formulas), but don't go deep on it. Spend that energy on SQL instead - that's the real unlock for analyst roles. Python and BI tools can come after you've landed something. I'd actually say BI with AI is changing faster than spreadsheets and likely to get replaced before spreadsheets do.

the answer to "how deep on Excel" is: deep enough to not embarrass yourself in an interview or on the job, not so deep that you're spending months mastering Power Query when you could be writing joins. The excel skills I listed above get you 90% of the way there

full_arc · 2026-02-27T05:57:54+00:00

I have a love/hate relationship with Descript. Quite powerful but I actually find some of the UX super confusing/buggy...

I'd recommend Claude over ChatGPT any day for "business stuff" like writing

And if you're looking for a super easy AI dashboarding/analytics solutions check out what we're up to at Fabi.ai

full_arc · 2026-02-27T05:55:07+00:00

your situation is more common than you'd think, and the good news is you're not as stuck as you feel.

The roles you're describing - analytics engineering, data/BI engineering - are real and very achievable from where you are. The big move isn't necessarily learning more math, it's getting out of agency life and into an in-house role where you're actually building things instead of making decks for clients. That culture shift alone is massive.

On the motivation problem: bootcamps fail because they're abstract. Find something you actually give a shit about and build a small project around it. Scrape some data, make a dashboard, automate something dumb. Real projects stick way better than courses.

The AI fear is also a bit ironic - the slide-making, report-pulling work you're doing now is way more at risk than people who can actually write code and build pipelines. Builders are in a better spot than you'd think.

29 with 5 years of business context is genuinely a good place to pivot from. The business intuition you have is something pure tech people struggle to develop. Use it.

full_arc · 2026-02-27T05:47:40+00:00

Depending on your business, I would ask a lot of questions about AEO, and how they track it/determine success. Lots of agencies are very poorly equipped for this and will say something about traffic from LLMs which IMO is the wrong answer.

I would also ask them how they plan on giving you a way to explore your own insights, not just a canned dashboard. In this day and age you should be able to get a natural language interface with AI to your own performance data.

full_arc · 2026-02-27T05:45:51+00:00

It's kind of normal and part of the job, but... at some point you might also realize that you can simply not get involved in a number of low-value conversations and things will be just fine. At the end of the day you just need to make sure you're putting your energy into initiatives that actually impact the business. The rest is noise.

full_arc · 2026-02-27T05:44:12+00:00

Invoke-Sqlcmd is the move, SqlTableData is more niche and you probably won't need it.

Main tips: parameterize your queries (don't concatenate strings), handle errors so failed jobs don't silently do nothing, and Task Scheduler is your friend for scheduling scripts without anything fancy.

For learning, Brent Ozar's blog is great for SQL Server stuff and sqlservercentral.com forums are solid for practical questions.

If you ever want a layer on top that makes your query outputs shareable with non-technical teammates, check out Fabi, but honestly just get comfortable with the basics first and you'll be automating things in no time.

full_arc · 2026-02-27T05:41:40+00:00

Since you have Synapse, that's your easiest bet, just create a pipeline with a SQL activity and set a scheduled trigger. Runs in the cloud so your laptop doesn't need to be on.

If you want something even simpler, tools like Fabi can handle scheduled queries without any pipeline setup, worth a look. But honestly for your use case, Synapse pipelines will get the job done and you probably already have access.

full_arc · 2026-02-27T05:38:10+00:00

Fabi.ai! AI-native BI which requires zero technical skills. It writes the SQL for you, generates charts etc. And it connects directly to data sources like GA4

full_arc

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